@article{basnet_brill_ranjithan_mahinthakumar_2023, title={Supervised Machine Learning Approaches for Leak Localization in Water Distribution Systems: Impact of Complexities of Leak Characteristics}, volume={149}, ISSN={["1943-5452"]}, DOI={10.1061/JWRMD5.WRENG-6047}, abstractNote={Localizing pipe leaks is a significant challenge for water utilities worldwide. Pipe leaks in water distribution systems (WDSs) can cause the loss of a large amount of treated water, leading to pressure loss, increased energy costs, and contamination risks. What makes localizing pipe leaks challenging is the underground location of the water pipes and the similarity in impact on hydraulic properties (e.g., pressure, flow) due to leaks as compared to the effects of WDS operational changes. Physical methods to locate leaks are expensive, intrusive, and heavily localized. Computational approaches such as data-driven machine learning models provide an economical alternative to physical methods. Machine learning models are readily available and easily customizable to most problems; therefore, there is an increasing trend in their application for leak localization in WDSs. While several studies have applied machine learning models to localize leaks in single pipes and small test networks, these studies have yet to thoroughly test these models against the different complexities of leak localization problems, and hence their applicability to real-world WDSs is still unclear. The simplicity of the WDSs, the oversimplification of leak characteristics, and the lack of consideration of modeling and measuring device uncertainties adopted in most of these studies make the scalability of their proposed approaches questionable to real-world WDSs. Our study addresses this issue by devising four study cases of different complexity that account for realistic leak characteristics and model- and measuring device-related uncertainties. Two established machine learning models—multilayer perceptron (MLP) and convolutional neural network (CNN)—are trained and tested for their ability to localize the leaks and predict their sizes for each of the four study cases using different simulated hydraulic inputs. In addition, the potential benefit of combining different types of hydraulic data as inputs to the machine learning models in localizing leaks is also explored. Pressure and flow, two common hydraulic measurements, are used as inputs to the machine learning models. Further, the impact of single and multiple time point input in leak localization is also investigated. The results for the L-Town network indicate good accuracies for both the models for all study cases, with CNN consistently outperforming MLP.}, number={8}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Basnet, Lochan and Brill, Downey and Ranjithan, Ranji and Mahinthakumar, Kumar}, year={2023}, month={Aug} }
 @article{daniel_pesantez_letzgus_fasaee_alghamdi_berglund_mahinthakumar_cominola_2022, title={A Sequential Pressure-Based Algorithm for Data-Driven Leakage Identification and Model-Based Localization in Water Distribution Networks}, volume={148}, ISSN={["1943-5452"]}, url={https://doi.org/10.1061/(ASCE)WR.1943-5452.0001535}, DOI={10.1061/(ASCE)WR.1943-5452.0001535}, abstractNote={: Leakages in water distribution networks (WDNs) are estimated to globally cost 39 billion USD = year and cause water and revenue losses, infrastructure degradation, and other cascading effects. Their impacts can be prevented and mitigated with prompt identification and accurate leak localization. In this work, we propose the leakage identification and localization algorithm (LILA), a pressure-based algorithm for data-driven leakage identification and model-based localization in WDNs. First, LILA identifies potential leakages via semisupervised linear regression of pairwise sensor pressure data and provides the location of their nearest sensors. Second, LILA locates leaky pipes relying on an initial set of candidate pipes and a simulation-based optimization framework with iterative linear and mixed-integer linear programming. LILA is tested on data from the L-Town network devised for the Battle of Leakage Detection and Isolation Methods. Results show that LILA can identify all leakages included in the data set and locate them within a maximum distance of 374 m from their real location. Abrupt leakages are identified immediately or within 2 h, while more time is required to raise alarms on incipient leakages. DOI: 10.1061/(ASCE) WR.1943-5452.0001535. © 2022 American Society of Civil Engineers.}, number={6}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, publisher={American Society of Civil Engineers (ASCE)}, author={Daniel, Ivo and Pesantez, Jorge and Letzgus, Simon and Fasaee, Mohammad Ali Khaksar and Alghamdi, Faisal and Berglund, Emily and Mahinthakumar, G. and Cominola, Andrea}, year={2022}, month={Jun} }
 @article{kabaasha_zyl_mahinthakumar_2020, title={Correcting Power Leakage Equation for Improved Leakage Modeling and Detection}, volume={146}, ISSN={["1943-5452"]}, DOI={10.1061/(ASCE)WR.1943-5452.0001172}, abstractNote={AbstractFluid pressure influences leakage flow rate in water distribution pipe networks. Significant progress has been made in the use of pressure management techniques to control leakage. An empir...}, number={3}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Kabaasha, A. M. and Zyl, J. E. and Mahinthakumar, G. ''Kumar''}, year={2020}, month={Mar} }
 @article{xuan_ford_mahinthakumar_de souza filho_lall_sankarasubramanian_2020, title={GRAPS: Generalized Multi-Reservoir Analyses using probabilistic streamflow forecasts}, volume={133}, ISSN={1364-8152}, url={http://dx.doi.org/10.1016/j.envsoft.2020.104802}, DOI={10.1016/j.envsoft.2020.104802}, abstractNote={A multi-reservoir simulation-optimization model GRAPS, Generalized Multi-Reservoir Analyses using Probabilistic Streamflow Forecasts, is developed in which reservoirs and users across the basin are represented using a node-link representation. Unlike existing reservoir modeling software, GRAPS can handle probabilistic streamflow forecasts represented as ensembles for performing multi-reservoir prognostic water allocation and evaluate the reliability of forecast-based allocation with observed streamflow. GRAPS is applied to four linked reservoirs in the Jaguaribe Metropolitan Hydro-System (JMH) in Ceará, North East Brazil. Results from the historical simulation and the zero-inflow policy over the JMH system demonstrate the model's capability to support monthly water allocation and reproduce the observed monthly releases and storages. Additional analyses using streamflow forecast ensembles illustrate GRAP's abilities in developing storage-reliability curves under inflow-forecast uncertainty. Our analyses show that GRAPS is versatile and can be applied for 1) short-term operating policy studies, 2) long-term basin-wide planning evaluations, and 3) climate-information based application studies.}, journal={Environmental Modelling & Software}, publisher={Elsevier BV}, author={Xuan, Yi and Ford, Lucas and Mahinthakumar, Kumar and De Souza Filho, Assis and Lall, Upmanu and Sankarasubramanian, A.}, year={2020}, month={Nov}, pages={104802} }
 @article{ricca_patskoski_mahinthakumar_2020, title={Reducing error in water distribution network simulations with field measurements}, volume={8}, ISSN={["2324-9676"]}, DOI={10.1080/23249676.2020.1719218}, abstractNote={Reduction of error in water distribution network (WDN) models leads to simulations that are more representative of actual network conditions and allows for more realistic system responses. Technological improvements have resulted in data collection becoming more prevalent in WDNs. This study quantifies the reduction in model error when considering demand uncertainty by incorporating pressure reducing valve (PRV) monitoring, operational monitoring, and supervisory control and data acquisition (SCADA) system data. Model implementation procedures were developed for each of these data types. For this study, outputs obtained by the modeling software EPANET for a WDN model built with hourly measured demands were treated as actual network observations. Pressures simulated by the network model that incorporated all three types of data had less error than pressures simulated by a base model representative of what water managers would use without access to this data. Model improvement varies both spatially and temporally.}, number={1}, journal={JOURNAL OF APPLIED WATER ENGINEERING AND RESEARCH}, author={Ricca, Henry and Patskoski, Jason and Mahinthakumar, Gnanamanikam}, year={2020}, month={Jan}, pages={15–27} }
 @article{ricca_aravinthan_mahinthakumar_2019, title={Modeling chloramine decay in full-scale drinking water supply systems}, volume={91}, ISSN={["1554-7531"]}, DOI={10.1002/wer.1046}, abstractNote={Abstract}, number={5}, journal={WATER ENVIRONMENT RESEARCH}, author={Ricca, Henry and Aravinthan, Vasanthadevi and Mahinthakumar, Gnanamanikam}, year={2019}, month={May}, pages={441–454} }
 @article{pesantez_berglund_mahinthakumar_2019, title={Multiphase Procedure to Design District Metered Areas for Water Distribution Networks}, volume={145}, ISSN={["1943-5452"]}, url={https://doi.org/10.1061/(ASCE)WR.1943-5452.0001095}, DOI={10.1061/(ASCE)WR.1943-5452.0001095}, abstractNote={AbstractDividing a water distribution network into subsystems can improve the efficiency and ease of achieving management goals. Subsystems or district metered areas (DMAs) are isolated control zon...}, number={8}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, publisher={American Society of Civil Engineers (ASCE)}, author={Pesantez, Jorge E. and Berglund, Emily Zechman and Mahinthakumar, G.}, year={2019}, month={Aug} }
 @article{de queiroz_mulcahy_sankarasubramanian_deane_mahinthakumar_lu_decarolis_2019, title={Repurposing an energy system optimization model for seasonal power generation planning}, volume={181}, ISSN={0360-5442}, url={http://dx.doi.org/10.1016/j.energy.2019.05.126}, DOI={10.1016/j.energy.2019.05.126}, abstractNote={Seasonal climate variations affect electricity demand, which in turn affects month-to-month electricity planning and operations. Electricity system planning at the monthly timescale can be improved by adapting climate forecasts to estimate electricity demand and utilizing energy models to estimate monthly electricity generation and associated operational costs. The objective of this paper is to develop and test a computationally efficient model that can support seasonal planning while preserving key aspects of system operation over hourly and daily timeframes. To do so, an energy system optimization model is repurposed for seasonal planning using features drawn from a unit commitment model. Different scenarios utilizing a well-known test system are used to evaluate the errors associated with both the repurposed energy system model and an imperfect load forecast. The results show that the energy system optimization model using an imperfect load forecast produces differences in monthly cost and generation levels that are less than 2% compared with a unit commitment model using a perfect load forecast. The enhanced energy system optimization model can be solved approximately 100 times faster than the unit commitment model, making it a suitable tool for future work aimed at evaluating seasonal electricity generation and demand under uncertainty.}, journal={Energy}, publisher={Elsevier BV}, author={de Queiroz, A.R. and Mulcahy, D. and Sankarasubramanian, A. and Deane, J.P. and Mahinthakumar, G. and Lu, N. and DeCarolis, J.F.}, year={2019}, month={Aug}, pages={1321–1330} }
 @article{seo_das bhowmik_sankarasubramanian_mahinthakumar_kumar_2019, title={The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables}, volume={570}, ISSN={0022-1694}, url={http://dx.doi.org/10.1016/J.JHYDROL.2018.12.076}, DOI={10.1016/j.jhydrol.2018.12.076}, abstractNote={Uncertainty in climate forcings causes significant uncertainty in estimating streamflow and other land-surface fluxes in hydrologic model simulations. Earlier studies primarily analyzed the importance of reproducing cross-correlation between precipitation and temperature (P-T cross-correlation) using various downscaling and weather generator schemes, leaving out how such biased estimates of P-T cross-correlation impact streamflow simulation and other hydrologic variables. The current study investigates the impacts of biased P-T cross-correlation on hydrologic variables using a fully coupled hydrologic model (Penn-state Integrated Hydrologic Model, PIHM). For this purpose, a synthetic weather generator was developed to generate multiple realizations of daily climate forcings for a specified P-T cross-correlation. Then, we analyzed how reproducing/neglecting P-T cross-correlation in climate forcings affect the accuracy of a hydrologic simulation. A total of 50 synthetic data sets of daily climate forcings with different P-T cross-correlation were forced into to estimate streamflow, soil moisture, and groundwater level under humid (Haw River basin in NC, USA) and arid (Lower Verde River basin in AZ, USA) hydroclimate settings. Results show that climate forcings reproducing the P-T cross-correlation yield lesser root mean square errors in simulated hydrologic variables (primarily on the sub-surface variables) as compared to climate forcings that neglect the P-T cross-correlation. Impacts of P-T cross-correlation on hydrologic simulations were remarkable to low flow and sub-surface variables whereas less significant to flow variables that exhibit higher variability. We found that hydrologic variables with lower internal variability (for example: groundwater and soil-moisture depth) are susceptible to the bias in P-T cross-correlation. These findings have potential implications in using univariate linear downscaling techniques to bias-correct GCM forcings, since univariate linear bias-correction techniques reproduce the GCM estimated P-T cross-correlation without correcting the bias in P-T cross-correlation.}, journal={Journal of Hydrology}, publisher={Elsevier BV}, author={Seo, S.B. and Das Bhowmik, R. and Sankarasubramanian, A. and Mahinthakumar, G. and Kumar, M.}, year={2019}, month={Mar}, pages={304–314} }
 @article{al-amin_berglund_mahinthakumar_larson_2018, title={Assessing the effects of water restrictions on socio-hydrologic resilience for shared groundwater systems}, volume={566}, ISSN={0022-1694}, url={http://dx.doi.org/10.1016/j.jhydrol.2018.08.045}, DOI={10.1016/j.jhydrol.2018.08.045}, abstractNote={Groundwater resources are shared across management boundaries. Multiple management units that differ in scale, constraints and objectives may manage a shared resource in a decentralized approach. The interactions among water managers, water users, and the water resource components influence the performance of management strategies and the resilience of community-level water supply and groundwater availability. This research develops an agent-based modeling (ABM) framework to capture the dynamic interactions among household-level consumers and policy makers to simulate water demands. The ABM is coupled with a groundwater model to evaluate effects on the groundwater table. The framework is applied to explore trade-offs between improvements in water supply sustainability for local resources and water table changes at the basin-level. A group of municipalities are simulated as agents who share access to a groundwater aquifer in Verde River Basin, Arizona. The framework provides a holistic approach to incorporate water user, municipal, and basin level objectives in evaluating water reduction strategies for long-term water resilience.}, journal={Journal of Hydrology}, publisher={Elsevier BV}, author={Al-Amin, Shams and Berglund, Emily Z. and Mahinthakumar, G. and Larson, Kelli L.}, year={2018}, month={Nov}, pages={872–885} }
 @article{seo_mahinthakumar_sankarasubramanian_kumar_2018, title={Assessing the restoration time of surface water and groundwater systems under groundwater pumping}, volume={32}, ISSN={1436-3240 1436-3259}, url={http://dx.doi.org/10.1007/S00477-018-1570-9}, DOI={10.1007/S00477-018-1570-9}, number={9}, journal={Stochastic Environmental Research and Risk Assessment}, publisher={Springer Science and Business Media LLC}, author={Seo, S. B. and Mahinthakumar, G. and Sankarasubramanian, A. and Kumar, M.}, year={2018}, month={Jun}, pages={2741–2759} }
 @article{seo_mahinthakumar_sankarasubramanian_kumar_2018, title={Conjunctive Management of Surface Water and Groundwater Resources under Drought Conditions Using a Fully Coupled Hydrological Model}, volume={144}, ISSN={["1943-5452"]}, DOI={10.1061/(asce)wr.1943-5452.0000978}, abstractNote={AbstractA conjunctive management model has been developed to obtain optimal allocation of surface water and groundwater under different constraints during a drought. Two simulation models—a fully d...}, number={9}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Seo, S. B. and Mahinthakumar, G. and Sankarasubramanian, A. and Kumar, M.}, year={2018}, month={Sep} }
 @article{salomons_skulovich_ostfeld_2017, title={Battle of Water Networks DMAs: Multistage Design Approach}, volume={143}, ISSN={["1943-5452"]}, DOI={10.1061/(asce)wr.1943-5452.0000830}, abstractNote={AbstractLooped water distribution system (WDS) repartitioning to district metering areas (DMAs) gained popularity as an effective technique to manage the system and detect and reduce system leakage...}, number={10}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Salomons, Elad and Skulovich, Olya and Ostfeld, Avi}, year={2017}, month={Oct} }
 @article{bhowmik_sankarasubramanian_sinha_patskoski_mahinthakumar_kunkel_2017, title={Multivariate Downscaling Approach Preserving Cross Correlations across Climate Variables for Projecting Hydrologic Fluxes}, volume={18}, ISSN={1525-755X 1525-7541}, url={http://dx.doi.org/10.1175/JHM-D-16-0160.1}, DOI={10.1175/jhm-d-16-0160.1}, abstractNote={Abstract}, number={8}, journal={Journal of Hydrometeorology}, publisher={American Meteorological Society}, author={Bhowmik, Rajarshi Das and Sankarasubramanian, A. and Sinha, Tushar and Patskoski, Jason and Mahinthakumar, G. and Kunkel, Kenneth E.}, year={2017}, month={Aug}, pages={2187–2205} }
 @article{berglund_areti_brill_mahinthakumar_2017, title={Successive linear approximation methods for leak detection in water distribution systems}, volume={143}, DOI={10.1061/(asce)wr.1943-5452.0000784}, abstractNote={AbstractIn many modern water networks, an emerging trend is to measure pressure at various points in the network for operational reasons. Because leaks typically induce a signature on pressure, the...}, number={8}, journal={Journal of Water Resources Planning and Management}, author={Berglund, A. and Areti, V. S. and Brill, D. and Mahinthakumar, G.}, year={2017} }
 @article{sankarasubramanian_sabo_larson_seo_sinha_bhowmik_vidal_kunkel_mahinthakumar_berglund_et al._2017, title={Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls}, volume={5}, ISSN={2328-4277 2328-4277}, url={http://dx.doi.org/10.1002/2016EF000511}, DOI={10.1002/2016ef000511}, abstractNote={Abstract}, number={7}, journal={Earth's Future}, publisher={American Geophysical Union (AGU)}, author={Sankarasubramanian, A. and Sabo, J. L. and Larson, K. L. and Seo, S. B. and Sinha, T. and Bhowmik, R. and Vidal, A. Ruhi and Kunkel, K. and Mahinthakumar, G. and Berglund, E. Z. and et al.}, year={2017}, month={Jul}, pages={771–788} }
 @inproceedings{al-amin_berglund_mahinthakumar_2016, title={Coupling agent-based and groundwater modeling to explore demand management strategies for shared resources}, DOI={10.1061/9780784479858.016}, abstractNote={Municipal water demands in growing population centers in the arid southwest U.S. are typically met through increased groundwater withdrawals. Hydro-climatic uncertainties attributed to climate change and land use conversions may also alter demands and impact the replenishment of groundwater supply. Groundwater aquifers are not necessarily confined within municipal and management boundaries, and multiple diverse agencies may manage a shared resource in a decentralized approach, based on individual concerns and resources. The interactions among water managers, consumers, and the environment influence the performance of local management strategies and regional groundwater resources. This research couples an agent-based modeling (ABM) framework and a groundwater model to analyze the effects of different management approaches on shared groundwater resources. The ABM captures the dynamic interactions between household-level consumers and policy makers to simulate water demands under climate change and population growth uncertainties. The groundwater model is used to analyze the relative effects of management approaches on reducing demands and replenishing groundwater resources. The framework is applied for municipalities located in the Verde River Basin, Arizona that withdraw groundwater from the Verde Formation-Basin Fill-Carbonate aquifer system. Insights gained through this simulation study can be used to guide groundwater policy-making under changing hydro-climatic scenarios for a long-term planning horizon.}, booktitle={World Environmental and Water Resources Congress 2016: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management}, author={Al-Amin, S. and Berglund, E. Z. and Mahinthakumar, K.}, year={2016}, pages={141–150} }
 @article{abdul_vigneswaran_kandasamy_mahinthakumar_2016, title={Fenton Oxidation of Metsulfuron-Methyl with Application to Permeable Reactive Barriers}, volume={21}, ISSN={["1573-2967"]}, DOI={10.1007/s10666-015-9475-1}, number={1}, journal={ENVIRONMENTAL MODELING & ASSESSMENT}, author={Abdul, Javeed M. and Vigneswaran, S. and Kandasamy, Jaya and Mahinthakumar, G.}, year={2016}, month={Jan}, pages={149–158} }
 @article{seo_sinha_mahinthakumar_sankarasubramanian_kumar_2016, title={Identification of dominant source of errors in developing streamflow and groundwater projections under near-term climate change}, volume={121}, ISSN={["2169-8996"]}, DOI={10.1002/2016jd025138}, abstractNote={Abstract}, number={13}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Seo, S. B. and Sinha, T. and Mahinthakumar, G. and Sankarasubramanian, A. and Kumar, M.}, year={2016}, month={Jul}, pages={7652–7672} }
 @inproceedings{ayub_obenour_messier_serre_mahinthakumar_2016, title={Non-point source evaluation of groundwater contamination from agriculture under geologic and hydrologic uncertainty}, DOI={10.1061/9780784479865.035}, abstractNote={The long-term effect of non-point source pollution on groundwater from agricultural practices is a major concern globally. Non-point source pollutants such as nitrate that occur through fertilizers and animal waste eventually make their way into the aquifer by infiltrating soil. The goal of this study is to characterize the probability distributions of non-point source locations and time release history of nitrate contamination into groundwater resources. A Bayesian framework using a Markov Chain Monte Carlo approach (MCMC) is developed to estimate posterior distributions of non-point sources by incorporating groundwater nitrate concentration data as well as geologic and hydrologic uncertainties. Hypothetical scenarios are used to test the approach and then apply it to a basin in North Carolina.The likelihood function computation involves a mechanistic model that simulates nitrate transport in groundwater from non-point agricultural sources and predicts nitrate concentrations at observation wells. Effectiveness of the proposed approach is tested through a convergence analysis of the MCMC algorithm. The Bayesian inference analysis methodology developed in this research will help decision makers and water managers identify potential source containment areas and to decide if further sampling is required.}, booktitle={World Environmental and Water Resources Congress 2016: Environmental, Sustainability, Groundwater, Hydraulic Fracturing, and Water Distribution Systems analysis}, author={Ayub, R. and Obenour, D. R. and Messier, K. P. and Serre, M. L. and Mahinthakumar, K.}, year={2016}, pages={329–336} }
 @article{shafiee_berglund_berglund_brill_mahinthakumar_2016, title={Parallel Evolutionary Algorithm for Designing Water Distribution Networks to Minimize Background Leakage}, volume={142}, ISSN={0733-9496 1943-5452}, url={http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000601}, DOI={10.1061/(asce)wr.1943-5452.0000601}, abstractNote={AbstractLeaks in water distribution systems waste energy and water resources, increase damage to infrastructure, and may allow contamination of potable water. This research develops an evolutionary algorithm-based approach to minimize the cost of water loss, new infrastructure, and operations that reduce background leakage. A new design approach is introduced that minimizes capital and operational costs, including energy and water loss costs. Design decisions identify a combination of infrastructure improvements, including pipe replacement and valve installment, and operation rules for tanks and pumps. Solution approaches are developed to solve both a single-objective and multiobjective problem formulation. A genetic algorithm and a nondominated sorting genetic algorithm are implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure-reducing valves, and pipe diameters for replacing pipes. The evolutionary algorithm approaches identif...}, number={5}, journal={Journal of Water Resources Planning and Management}, publisher={American Society of Civil Engineers (ASCE)}, author={Shafiee, M. Ehsan and Berglund, Andrew and Berglund, Emily Zechman and Brill, E. Downey, Jr. and Mahinthakumar, G.}, year={2016}, month={May} }
 @article{jin_ranjithan_mahinthakumar_2014, title={A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification}, volume={15}, ISSN={["1527-5930"]}, DOI={10.1080/15275922.2013.873095}, abstractNote={Finding the location and concentration of contaminant sources is an important step in groundwater remediation and management. This discovery typically requires the solution of an inverse problem. This inverse problem can be formulated as an optimization problem where the objective function is the sum of the square of the errors between the observed and predicted values of contaminant concentration at the observation wells. Studies show that the source identification accuracy is dependent on the observation locations (i.e., network geometry) and frequency of sampling; thus, finding a set of optimal monitoring well locations is very important for characterizing the source. The objective of this study is to propose a sensitivity-based method for optimal placement of monitoring wells by incorporating two uncertainties: the source location and hydraulic conductivity. An optimality metric called D-optimality in combination with a distance metric, which tends to make monitoring locations as far apart from each other as possible, is developed for finding optimal monitoring well locations for source identification. To address uncertainty in hydraulic conductivity, an integration method of multiple well designs is proposed based on multiple hydraulic conductivity realizations. Genetic algorithm is used as a search technique for this discrete combinatorial optimization problem. This procedure was applied to a hypothetical problem based on the well-known Borden Site data in Canada. The results show that the criterion-based selection proposed in this paper provides improved source identification performance when compared to uniformly distributed placement of wells.}, number={1}, journal={ENVIRONMENTAL FORENSICS}, author={Jin, Xin and Ranjithan, Ranji S. and Mahinthakumar, G.}, year={2014}, month={Jan}, pages={78–96} }
 @article{marchi_salomons_ostfeld_kapelan_simpson_zecchin_maier_wu_elsayed_song_et al._2014, edition={+59 co-authors}, title={Battle of the Water Networks II}, volume={140}, ISSN={0733-9496 1943-5452}, url={http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000378}, DOI={10.1061/(ASCE)WR.1943-5452.0000378}, abstractNote={The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems. (C) 2014 American Society of Civil Engineers.}, number={7}, journal={Journal of Water Resources Planning and Management}, publisher={American Society of Civil Engineers (ASCE)}, author={Marchi, Angela and Salomons, Elad and Ostfeld, Avi and Kapelan, Zoran and Simpson, Angus R. and Zecchin, Aaron C. and Maier, Holger R. and Wu, Zheng Yi and Elsayed, Samir M. and Song, Yuan and et al.}, year={2014}, month={Jul}, pages={04014009} }
 @article{shafiee_berglund_berglund_brill_mahinthakumar_2014, title={Evolutionary Computation-based Decision-making Framework for Designing Water Networks to Minimize Background Leakage}, volume={89}, ISSN={1877-7058}, url={http://dx.doi.org/10.1016/J.PROENG.2014.11.167}, DOI={10.1016/J.PROENG.2014.11.167}, abstractNote={Abstract This research minimizes the impact of leaks on the operation of the system to reduce lost water while meeting typical management goals. A genetic algorithm approach is implemented within a high-performance computing platform to select tank sizes, pump placement and operations, placement of pressure control valves, and pipe diameters for replacing pipes. It identifies solutions that minimize water loss, operational costs, and capital costs, while maintaining pressure at nodes and operational feasibility for tanks. Multiple problem formulations are solved that use alternative objective functions and allow varying degrees of freedom in the decision space. The methodology is demonstrated to identify a water distribution system re-design for the C-Town case study.}, journal={Procedia Engineering}, publisher={Elsevier BV}, author={Shafiee, M.E. and Berglund, A. and Berglund, E. Zechman and Brill, E. Downey, Jr. and Mahinthakumar, G.}, year={2014}, pages={118–125} }
 @inproceedings{jasper_mahinthakumar_ranjithan_brill_2013, title={A Sensitivity Analysis of Data Measurement Types for Leak Detection in Water Distribution Systems}, ISBN={9780784412947}, url={http://dx.doi.org/10.1061/9780784412947.059}, DOI={10.1061/9780784412947.059}, abstractNote={It is estimated that 15-40% of water is unaccounted for in urban water systems. This is mostly caused by small leaks, which are difficult to locate. Routinely measured pressure, flow, and water quality data can be used to locate leaks in the water network using an inverse modeling approach. For a known sensor configuration, the leak locations can be found by minimizing the difference between real and simulated measurements. However, when comparing measurement types (pressure, flow, or quality), some may be more sensitive to leak location than others. Furthermore, some measurement types may be more or less sensitive depending on the leak magnitude or the proximity of the leak to the sensors. The measurements types that are more sensitive to location will have a stronger signature and would need to be weighted more in an inverse modeling approach, especially in the presence of noise. Preliminary research suggests that water quality measurements are more sensitive to leak location when a leak is small, and that flow measurements are more sensitive when a leak is large. In this research, a series of sensitivity analyses are conducted on different networks to investigate the sensitivity of these measurements with respect to leak location, magnitude, and proximity of sensors to the leak location. 1. Motivation Water distribution systems are a vital part of modern infrastructure, yet they are susceptible to leaks and contaminant intrusion. High pressure, freezing water, or aging can cause cracks in the distribution pipes that lead to small, gradual leaks into the ground that are difficult to detect. In some aging systems, up to 40% of water is lost to leaks [1]. Utilities typically monitor locations that are prone to leak, based on a history of previous leaks or the age of the pipes. A leak can be detected, for example, by using acoustic listening devices that pick up on the sound of water escaping from the pipe, among other methods. However, it is expensive and time intensive to manually check the suspected pipes. There are routinely collected measurements of pressure, flow, and water quality at sensor locations. These measurements can carry a signature that will help identify the leak location and}, booktitle={World Environmental and Water Resources Congress 2013}, publisher={American Society of Civil Engineers}, author={Jasper, Micah N. and Mahinthakumar, Gnanamanikam (Kumar) and Ranjithan, Sanmugavadivel (Ranji) and Brill, Earl Downey}, year={2013}, month={May} }
 @article{jung_mahinthakumar_ranjithan_2013, title={Development of a simultaneous search-based pilot point method for subsurface characterization}, volume={27}, ISSN={["1436-3259"]}, DOI={10.1007/s00477-013-0734-x}, number={8}, journal={STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT}, author={Jung, Yong and Mahinthakumar, G. and Ranjithan, Ranji}, year={2013}, month={Dec}, pages={2003–2013} }
 @article{pradhan_mahinthakumar_2013, title={Finding All-Pairs Shortest Path for a Large-Scale Transportation Network Using Parallel Floyd-Warshall and Parallel Dijkstra Algorithms}, volume={27}, ISSN={["1943-5487"]}, DOI={10.1061/(asce)cp.1943-5487.0000220}, abstractNote={AbstractParallel computing has become a powerful approach for solving real-time decisions about large-scale, computing-intensive transportation problems. A frequently encountered transportation problem is the “shortest path problem;” that is, finding the shortest path between any two nodes in a transportation network. For the large transportation networks encountered in major metropolitan areas, this problem can be computationally demanding, especially if shortest paths between all the nodes in the network need to be dynamically updated (e.g., evolving traffic conditions). In such a situation, one may wish to harness parallel computing to solve this problem. However, the parallel implementations of commonly used shortest-path algorithms are computationally demanding because of the inherent sequential nature of the search process used by the algorithms. This paper describes parallel implementations and includes performance analyses of two prominent graph algorithms (i.e., Floyd-Warshall and Dijkstra) used ...}, number={3}, journal={JOURNAL OF COMPUTING IN CIVIL ENGINEERING}, author={Pradhan, Anu and Mahinthakumar, G.}, year={2013}, pages={263–273} }
 @inproceedings{jasper_mahinthakumar_ranjithan_brill_2013, title={Leak Detection in Water Distribution Systems Using the Dividing Rectangles (DIRECT) Search}, ISBN={9780784412947}, url={http://dx.doi.org/10.1061/9780784412947.078}, DOI={10.1061/9780784412947.078}, abstractNote={Leak detection and management is an important problem in water distribution systems since it has been documented that up to 40% of the water may be lost to leaks in many aging systems. Small gradual leaks, which represent more than half of all leaks, are difficult to locate. Routinely measured pressure, flow, and water quality data in combination with a simulation-optimization inverse modeling approach could be used to characterize leakage. In this approach, the leak locations are found by minimizing the difference between real and simulated measurements for a known sensor configuration. Simulation-optimization approaches are computationally demanding because millions of simulations of a network simulator (e.g., EPANET) may be required to achieve a satisfactory solution. This problem is alleviated using a high performance computing (HPC) framework that enables many parallel simulations of the water system using EPANET. This research is modifying an existing global search algorithm, called the Dividing Rectangles (DIRECT) Search that is traditionally used for continuous functions, to enable parallel simulations and a mix of discrete variables (for leak locations) and continuous variables (for leak magnitudes). The modified algorithm is being tested with traditional continuous test functions, discrete test functions, and test water distribution networks. 1. Motivation Water distribution systems are a vital part of modern infrastructure, yet they are susceptible to leaks and contaminant intrusion. High pressure, freezing water, or aging can cause cracks in the distribution pipes that lead to small, gradual leaks into the ground that are difficult to detect. In some aging systems, up to 40% of water is lost to leaks [1]. Utilities typically monitor locations that are prone to leak, based on a history of previous leaks or the age of the pipes. A leak can be detected, for example, by using acoustic listening devices that pick up on the sound of water escaping from the pipe, among other methods. However, it is expensive and time intensive to manually check the suspected pipes. There are routinely collected measurements of pressure, flow, and water quality at sensor locations. These measurements can carry a signature that will help identify the leak location and}, booktitle={World Environmental and Water Resources Congress 2013}, publisher={American Society of Civil Engineers}, author={Jasper, Micah N. and Mahinthakumar, Gnanamanikam (Kumar) and Ranjithan, Sanmugavadivel (Ranji) and Brill, Earl Downey}, year={2013}, month={May} }
 @article{kumar_brill_mahinthakumar_ranjithan_2012, title={Contaminant source characterization in water distribution systems using binary signals}, volume={14}, ISSN={1464-7141 1465-1734}, url={http://dx.doi.org/10.2166/hydro.2012.073}, DOI={10.2166/hydro.2012.073}, abstractNote={This paper presents a simulation–optimization-based method for identification of contamination source characteristics in a water distribution system using filtered data from threshold-based binary water quality signals. The effects of quality and quantity of the data on the accuracy of the source identification methodology are investigated. This study also addresses the issue of non-uniqueness in contaminant source identification under various data availability conditions. To establish the robustness and applicability of the methodology, numerous scenarios are investigated for a wide range of contamination incidents associated with two different networks. Results indicate that, even though use of lower resolution sensors lead to more non-unique solutions, the true source location is always included among these solutions.}, number={3}, journal={Journal of Hydroinformatics}, publisher={IWA Publishing}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G. and Ranjithan, S. Ranji}, year={2012}, month={Jul}, pages={585–602} }
 @article{liu_zechman_mahinthakumar_ranji ranjithan_2012, title={Coupling of logistic regression analysis and local search methods for characterization of water distribution system contaminant source}, volume={25}, ISSN={0952-1976}, url={http://dx.doi.org/10.1016/j.engappai.2011.10.009}, DOI={10.1016/j.engappai.2011.10.009}, abstractNote={Accidental or intentional drinking water contamination has long been and remains a major threat to water security throughout the world. An inverse problem can be constructed, given sensor measurements in a water distribution system (WDS), to identify the contaminant source characteristics by integrating a WDS simulation model with an optimization method. However, this approach requires numerous compute-intensive simulation runs to evaluate potential solutions; thus, determining the best source characteristic within a reasonable computational time is challenging. In this paper, we describe the development of a WDS contamination characterization algorithm by coupling a statistical model with a heuristic search method. The statistical model is used to identify potential source locations of contamination and a local search aims at further refining contaminant source characteristics. Application of the proposed approach to two illustrative example water distribution networks demonstrates its capability of adaptively discovering contaminant source characteristics as well as evaluating the degree of non-uniqueness of solutions. The results also showed that the local search as an optimizer has better performance than a standard evolutionary algorithm (EA).}, number={2}, journal={Engineering Applications of Artificial Intelligence}, publisher={Elsevier BV}, author={Liu, Li and Zechman, Emily M. and Mahinthakumar, G. and Ranji Ranjithan, S.}, year={2012}, month={Mar}, pages={309–316} }
 @article{mirghani_zechman_ranjithan_mahinthakumar_2012, title={Enhanced Simulation-Optimization Approach Using Surrogate Modeling for Solving Inverse Problems}, volume={13}, ISSN={1527-5922 1527-5930}, url={http://dx.doi.org/10.1080/15275922.2012.702333}, DOI={10.1080/15275922.2012.702333}, abstractNote={This study investigates and discusses groundwater system characterization problem utilizing surrogate modeling. In this inverse problem, the contaminant signals at monitoring wells are recorded to recreate the pollution profiles. In this study, simulation-optimization approach is a technique utilized to solve inverse problems by formulating them as an optimization model, where evolutionary computation algorithms are used to perform the search. In this approach, the partial differential equations (PDE) groundwater transport simulation model is solved iteratively during the evolutionary search, which in general can be computationally expensive since thousands of simulation model evaluations will be evaluated. To overcome this limitation, the simulation model is replaced by a surrogate model, which is computationally much faster than the simulation model and yet is relatively accurate. Artificial neural networks (ANN) is used to construct surrogate models that provide acceptable accuracy performances. The ANN surrogate model, which replaces the PDE groundwater transport simulation model, is then coupled with a genetic algorithm (GA) search procedure to solve the source identification problem. The results will present the quality solution of the ANN surrogate model versus the groundwater simulation model, the solution of the inverse problem for different experiment scenarios and finally a timing study analysis conducted to measure the surrogate model performance.}, number={4}, journal={Environmental Forensics}, publisher={Informa UK Limited}, author={Mirghani, Baha Y. and Zechman, Emily M. and Ranjithan, Ranji S. and Mahinthakumar, G. (Kumar)}, year={2012}, month={Jan}, pages={348–363} }
 @article{liu_zechman_mahinthakumar_ranji ranjithan_2012, title={Identifying contaminant sources for water distribution systems using a hybrid method}, volume={29}, ISSN={1028-6608 1029-0249}, url={http://dx.doi.org/10.1080/10286608.2012.663360}, DOI={10.1080/10286608.2012.663360}, abstractNote={The rapid discovery of the contaminant source in a water distribution system (WDS) is vital for generating an efficient control strategy during a contamination event. An inverse problem can be constructed, given sensor measurements in a WDS, to identify the contaminant source characteristics by integrating a WDS simulation model with an optimisation method. However, this approach requires numerous compute-intensive simulation runs to evaluate potential solutions. This paper reports the findings of an investigation by introducing a hybrid method for the real-time characterisation of a contaminant source. This new method integrates a simulation-optimisation approach with a logistic regression and a local improvement method to expedite the convergence and possibly solve the problem quickly. The results of numerical experiments on two example WDS networks demonstrate the efficiency of the proposed hybrid method for contaminant source characterisation. Effects of various hybrid strategies on the algorithm performance are discussed.}, number={2}, journal={Civil Engineering and Environmental Systems}, publisher={Informa UK Limited}, author={Liu, Li and Zechman, Emily M. and Mahinthakumar, G. and Ranji Ranjithan, S.}, year={2012}, month={Jun}, pages={123–136} }
 @inproceedings{sreepathi_brill_ranjithan_mahinthakumar_2012, title={Parallel Multi-Swarm Optimization Framework for Search Problems in Water Distribution Systems}, ISBN={9780784412312}, url={http://dx.doi.org/10.1061/9780784412312.323}, DOI={10.1061/9780784412312.323}, abstractNote={Population based heuristic search methods such as evolutionary algorithms (EA) and particle swarm optimization (PSO) methods are widely used for solving optimization problems especially when classical techniques are inadequate. A parallel optimization framework using multiple concurrent particle swarms is developed and applied to water distribution problems. Details of the enabling framework that couples the optimization methods with a parallel simulator built around EPANET will be discussed. In addition, algorithmic and computational performance results using ORNL’s and ANL’s leadership class parallel architectures will be presented for leakage detection and contaminant source characterization problems for two water distribution networks with 1,834 and 12,457 nodes respectively.}, booktitle={World Environmental and Water Resources Congress 2012}, publisher={American Society of Civil Engineers}, author={Sreepathi, Sarat and Brill, Downey and Ranjithan, Ranji and Mahinthakumar, Gnanamanikam (Kumar)}, year={2012}, month={May} }
 @inproceedings{barandouzi_mahinthakumar_ranjithan_brill_2012, title={Probabilistic Mapping of Water Leakage Characterizations Using a Bayesian Approach}, ISBN={9780784412312}, url={http://dx.doi.org/10.1061/9780784412312.326}, DOI={10.1061/9780784412312.326}, abstractNote={Water Distribution Systems are one of the most substantial and vulnerable part of civil infrastructure systems. For the reason that many large water distribution systems are old, which results in more leakage and expenses (e.g., increasing pump head, pipe burst, constituents’ replacement), a significant portion of water produced by the utilities never passes through the consumers’ meters. Due to the complex nature and vast spatial extent of a water distribution system it may be difficult for the utility personnel to identify and fix the leaks, therefore it is imperative to develop software frameworks for modeling and analyzing leakage in water distribution system during ordinary operational conditions as well as unexpected events. In this paper a Bayesian approach with Markov chain Monte Carlo method is implemented to map probabilistic characterizations of water leakage. If for this purpose physical parameters such as pipe vintage, material, and loading are available, they can be are used to develop prior information; otherwise, a uniform prior may be assumed. Routinely measured water quality, pressure, and flow measurements together with the uncertainty in demand are used to develop the likelihood function. The analyses are facilitated through the EPANET water distribution simulation tool. The efficiency and versatility of the proposed methodology is examined using water distribution network.}, booktitle={World Environmental and Water Resources Congress 2012}, publisher={American Society of Civil Engineers}, author={Barandouzi, M. A. and Mahinthakumar, G. and Ranjithan, R. and Brill, E. D.}, year={2012}, month={May} }
 @article{abdul_kumar_vigneswaran_kandasamy_2012, title={Removal of metsulfuron methyl by Fenton reagent}, volume={18}, ISSN={["1876-794X"]}, DOI={10.1016/j.jiec.2011.11.004}, abstractNote={The removal of metsulfuron methyl (MeS)—a sulfonyl urea herbicide from contaminated water was investigated by advanced oxidation process (AOP) using Fenton method. The optimum dose of Fenton reagent (Fe2+/H2O2) was 10 mg/L Fe2+ and 60 mg/L H2O2 for an initial MeS concentration ([MeS]0) range of 0–80 mg/L. The Fenton process was effective under pH 3. The degradation efficiency of MeS decreased by more than 70% at pH > 3 (pH 4.5 and 7). The initial Fe2+ concentration ([Fe2+]0) in the Fenton reagent affected the degradation efficiency, rate and kinetics. The degradation of MeS at optimum dose of Fenton reagent was more than 95% for [MeS] 0 of 0–40 mg/L and the degradation time was less than 30 min. The determination of residual MeS concentration after Fenton oxidation by UV spectrophotometry was affected by the interferences from Fenton reagent. The estimation of residual MeS concentration after Fenton oxidation by high pressure/performance liquid chromatograph (HPLC) was interference free and represented the actual concentration of MeS and does not include the by-products of Fenton oxidation. The degradation kinetics of MeS was modelled by second order reactions involving 8 rate constants. The two reaction constants directly involving MeS were fitted using the experimental data and the remaining constants were selected from previously reported values. The model fit for MeS and the subsequent prediction of H2O2 were found to be within experimental error tolerances.}, number={1}, journal={JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY}, author={Abdul, Javeed Mohammed and Kumar, Mahintha and Vigneswaran, Saravanamuthu and Kandasamy, Jaya}, year={2012}, month={Jan}, pages={137–144} }
 @article{liu_ranjithan_mahinthakumar_2011, title={Contamination Source Identification in Water Distribution Systems Using an Adaptive Dynamic Optimization Procedure}, volume={137}, ISSN={["1943-5452"]}, DOI={10.1061/(asce)wr.1943-5452.0000104}, abstractNote={Contamination source identification involves the characterization of the contaminant source based on observations that stream from a set of sensors in a water distribution system (WDS). The streaming data can be processed adaptively to provide an estimate of the source characteristics at any time once the contamination event is detected. In this paper, an adaptive dynamic optimization technique (ADOPT) is proposed for providing a real-time response to a contamination event. A new multiple population–based search that uses an evolutionary algorithm (EA) is investigated. To address nonuniqueness in the initial stages of the search and prevent premature convergence of the EA to an incorrect solution, the multiple populations are designed to maintain a set of alternative solutions that represent various nonunique solutions. As more observations are added, the EA solutions not only migrate to better solution states but the number of solutions decreases as the degree of nonuniqueness diminishes. This new algori...}, number={2}, journal={JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT}, author={Liu, Li and Ranjithan, S. Ranji and Mahinthakumar, G.}, year={2011}, pages={183–192} }
 @article{jung_ranjithan_mahinthakumar_2011, title={Subsurface characterization using a D-optimality based pilot point method}, volume={13}, ISSN={["1465-1734"]}, DOI={10.2166/hydro.2010.111}, abstractNote={Detailed hydraulic conductivity estimation is a difficult problem as the number of direct measurements available at a typical field site is relatively few and sparse. A common approach to estimate hydraulic conductivity is to combine direct hydraulic conductivity measurements with secondary measurements such as hydraulic head and tracer concentrations in an inverse modeling approach. Even with secondary measurements this may constitute an underdetermined (or over-parameterized) inverse problem giving rise to ‘non-unique’ and incorrect estimates. One approach to reduce over-parameterization is to estimate hydraulic conductivity at a few carefully chosen points called ‘pilot points’ (i.e. reduction in parameter space). This paper develops a D-optimality based criterion method (DBM) for pilot point selection and tests its effectiveness for estimating hydraulic conductivity fields using several synthetic cases. Results show that the selected pilot points using this approach lead to a more accurate hydraulic conductivity characterization than either random or sequential pilot point location selection methods.}, number={4}, journal={JOURNAL OF HYDROINFORMATICS}, author={Jung, Yong and Ranjithan, Ranji S. and Mahinthakumar, G.}, year={2011}, pages={775–793} }
 @article{tryby_mirghani_mahinthakumar_ranjithan_2010, title={A SOLUTION FRAMEWORK FOR ENVIRONMENTAL CHARACTERIZATION PROBLEMS}, volume={24}, ISSN={["1741-2846"]}, DOI={10.1177/1094342009350886}, abstractNote={ This paper describes experiences developing a grid-enabled framework for solving environmental inverse problems. The solution approach taken here couples environmental simulation models with global search methods and requires readily available computational resources of the grid for computational tractability. The solution framework developed by the authors uses a master—worker strategy for task distribution and a pool for task mapping. Solution and computational performance results are presented for groundwater source identification and release history reconstruction problems. They indicate that high-quality solutions and significant raw performance improvements were attained for a deployment of the solution framework on the TeraGrid. }, number={3}, journal={INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS}, author={Tryby, M. E. and Mirghani, B. Y. and Mahinthakumar, G. K. and Ranjithan, S. R.}, year={2010}, month={Aug}, pages={265–283} }
 @inproceedings{kumar_sreepathi_brill_ranjithan_mahinthakumar_2010, title={Detection of Leaks in Water Distribution System Using Routine Water Quality Measurements}, ISBN={9780784411148}, url={http://dx.doi.org/10.1061/41114(371)426}, DOI={10.1061/41114(371)426}, abstractNote={Water distributions systems are primary means of safe drinking water supply to the public. Water produced and delivered to the distribution system is intended for the customer. However, a significant amount of the water is lost in the distribution system before even reaching the customers. Water customers are metered for the usage at end connection but a significant portion of water produced by the utilities never passes through the meters. This leads to wastage of valuable water and loss of revenues for the utilities. The occurrence of leaks depends on the factors like material, composition, age and joining methods of the distribution systems components. Due to the complex nature and vast spatial extent of a water distribution system it may be difficult for the utility personnel to identify and fix the leaks. Traditionally, the method of inverse transient analysis (ITA) has been used by the researchers for identifying the leaks in a distribution system. While transient analysis is an efficient method for leak detection, it often requires that a series of hydraulic transients (or pressure pulses) be injected into the system in order to detect the leaks (e.g., controlled opening/closing of a fire hydrant). In contrast to ITA, this work attempts to use routinely measured water quality and pressure measurements for the detection of leaks. Distribution systems are routinely monitored for several water quality parameters such as Chlorine, pH, and turbidity. Water loss due to any leaks present in the system would impact the flow characteristics of the system and would have an impact on the water quality. In this study a methodology has been developed to use the water quality data along with available pressure measurements for the improved detection of leaks in a water distribution system. Leak detection is formulated as an inverse problem and solved using a simulation-optimization approach.}, booktitle={World Environmental and Water Resources Congress 2010}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Sreepathi, Sarat and Brill, E. Downey and Ranjithan, Ranji and Mahinthakumar, G.}, year={2010}, month={May} }
 @article{mirghani_tryby_ranjithan_karonis_mahinthakumar_2010, title={Grid-Enabled Simulation-Optimization Framework for Environmental Characterization}, volume={24}, ISSN={["1943-5487"]}, DOI={10.1061/(asce)cp.1943-5487.0000052}, abstractNote={Many engineering and environmental problems that involve the determination of unknown system characteristics from observation data can be categorized as inverse problems. A common approach undertaken to solve such problems is the simulation-optimization approach where simulation models are coupled with optimization or search methods. Simulation-optimization approaches, particularly in environmental characterization involving natural systems, are computationally expensive due to the complex three-dimensional simulation models required to represent these systems and the large number of such simulations involved. Emerging grid computing environments (e.g., TeraGrid) show promise for improving the computational tractability of these approaches. However, harnessing grid resources for most computational applications is a nontrivial problem due to the complex hierarchy of heterogeneous and geographically distributed resources involved in a grid. This paper reports and discusses the development and evaluation of ...}, number={6}, journal={JOURNAL OF COMPUTING IN CIVIL ENGINEERING}, author={Mirghani, Baha Y. and Tryby, Michael E. and Ranjithan, Ranji S. and Karonis, Nicholas T. and Mahinthakumar, Kumar G.}, year={2010}, pages={488–498} }
 @inproceedings{kumar_brill_mahinthakumar_ranjithan_2010, title={Identification of Reactive Contaminant Sources in a Water Distribution System under the Conditions of Data Uncertainties}, ISBN={9780784411148}, url={http://dx.doi.org/10.1061/41114(371)442}, DOI={10.1061/41114(371)442}, abstractNote={Water distribution systems are designed for fast and efficient transport of the drinking water and mixing of chlorine to maintain the required disinfectant levels in the system. Thus, any contaminant if injected in the system would also spread quickly through the network and can have serious impact on public health if consumed. Contaminant injected during any intentional contamination event can be chemical or biological, the nature of which may remain unknown. Practically it's not possible to monitor any system for the presence of all possible chemical or biological contaminants. However, the distribution systems are routinely monitored for several water quality parameters like chlorine, pH, etc. Any contaminant injected in the system would react with water and chlorine leading to the increased degradation of the chlorine levels in the system. In our past work we developed methodology to use routine chlorine measurements as a surrogate to identify a contamination event in a WDS. An evolutionary algorithm based approach simulation-optimization was developed to identify the contaminant source characteristics (i.e., location of the contaminant source, time of start of injection and injection pattern) during a contamination event under conditions of uncertainty about the reaction kinetics of the contaminant in the system. The investigation was extended to study the source characterization problem under different uncertain reaction conditions. We present here a detailed analysis of source characterization problem for the reactive contaminants and the simulation-optimization methodology developed. Case studies carried out on a number of water distributions systems will be reported.}, booktitle={World Environmental and Water Resources Congress 2010}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G. and Ranjithan, Ranji}, year={2010}, month={May} }
 @article{ho_senthilnanthan_mohammad_vigneswaran_ngo_mahinthakumar_kandasamy_2010, title={The application of photocatalytic oxidation in removing pentachlorophenol from contaminated water}, volume={13}, DOI={10.1515/jaots-2010-0103}, abstractNote={Abstract}, number={1}, journal={Journal of Advanced Oxidation Technologies}, author={Ho, D. P. and Senthilnanthan, M. and Mohammad, J. A. and Vigneswaran, S. and Ngo, H. H. and Mahinthakumar, G. and Kandasamy, J.}, year={2010}, pages={21–26} }
 @inproceedings{liu_brill_mahinthakumar_ranjithan_2009, title={A Hybrid Heuristic Search Approach for Contaminant Source Characterization}, ISBN={9780784410363}, url={http://dx.doi.org/10.1061/41036(342)63}, DOI={10.1061/41036(342)63}, abstractNote={The rapid discovery of the contaminant source and its mass loading characteristics in a water distribution system (WDS) is vital for generating an efficient control strategy during a contamination event. Previous work on the Adaptive Dynamic Optimization Technique (ADOPT), which was developed as an Evolution Strategy (ES) based procedure, presents an approach to estimate the source characteristics adaptively, given dynamically updated observation data. Although this simulation-optimization approach is promising, it is computationally expensive, which poses challenges in the context of real-time solutions. This paper reports the findings of an investigation that builds upon the prior work by introducing a hybrid heuristic search method for the real-time characterization of a contaminant source. This new method integrates the ES-based ADOPT with a logistic regression (LR) analysis and a local improvement method to expedite the convergence and possibly solve the problem quickly. As a prescreening technique, a LR analysis step is performed prior to ADOPT; this step reduces the search space by eliminating unnecessary source nodes as potential source locations. Then, a local search (LS) approach is embedded into some of the algorithmic steps in ADOPT to serve as a postscreening step that potentially speeds up the convergence in localized regions in the solution space. Numerical experiments for the proposed hybrid approach are performed on an example water distribution network, and the results are compared with those of the standard implementation of ADOPT.}, booktitle={World Environmental and Water Resources Congress 2009}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, E. Downey and Mahinthakumar, G. (Kumar) and Ranjithan, S. Ranji}, year={2009}, month={May} }
 @article{jin_mahinthakumar_zechman_ranjithan_2009, title={A genetic algorithm-based procedure for 3D source identification at the Borden emplacement site}, volume={11}, ISSN={1464-7141 1465-1734}, url={http://dx.doi.org/10.2166/hydro.2009.002}, DOI={10.2166/hydro.2009.002}, abstractNote={Finding the location and concentration of groundwater contaminant sources typically requires the solution of an inverse problem. A parallel hybrid optimization framework that uses genetic algorithms (GA) coupled with local search approaches (GA-LS) has been developed previously to solve groundwater inverse problems. In this study, the identification of an emplaced source at the Borden site is carried out as a test problem using this optimization framework by using a Real Genetic Algorithm (RGA) as the GA approach and a Nelder–Mead simplex as the LS approach. The RGA results showed that the minimum objective function did not always correspond to the minimum solution error, indicating a possible non-uniqueness issue. To address this problem, a procedure to identify maximally different starting points for LS is introduced. When measurement or model errors are non-existent or minimal it is shown that one of these starting points leads to the true solution. When these errors are significant, this procedure leads to multiple possible solutions that could be used as a basis for further investigation. Metrics of mean and standard deviation of objective function values was adopted to evaluate the possible solutions. A new selection criterion based on these metrics is suggested to find the best alternative. This suggests that this alternative generation procedure could be used to address the non-uniqueness of similar inverse problems. A potential limitation of this approach is the application to a wide class of problems, as verification has not been performed with a large number of test cases or other inverse problems. This remains a topic for future work.}, number={1}, journal={Journal of Hydroinformatics}, publisher={IWA Publishing}, author={Jin, Xin and Mahinthakumar, G. (Kumar) and Zechman, Emily M. and Ranjithan, Ranji S.}, year={2009}, month={Jan}, pages={51–64} }
 @article{mirghani_mahinthakumar_tryby_ranjithan_zechman_2009, title={A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems}, volume={32}, ISSN={0309-1708}, url={http://dx.doi.org/10.1016/j.advwatres.2009.06.001}, DOI={10.1016/j.advwatres.2009.06.001}, abstractNote={Groundwater characterization involves the resolution of unknown system characteristics from observation data, and is often classified as an inverse problem. Inverse problems are difficult to solve due to natural ill-posedness and computational intractability. Here we adopt the use of a simulation–optimization approach that couples a numerical pollutant-transport simulation model with evolutionary search algorithms for solution of the inverse problem. In this approach, the numerical transport model is solved iteratively during the evolutionary search. This process can be computationally intensive since several hundreds to thousands of forward model evaluations are typically required for solution. Given the potential computational intractability of such a simulation–optimization approach, parallel computation is employed to ease and enable the solution of such problems. In this paper, several variations of a groundwater source identification problem is examined in terms of solution quality and computational performance. The computational experiments were performed on the TeraGrid cluster available at the National Center for Supercomputing Applications. The results demonstrate the performance of the parallel simulation–optimization approach in terms of solution quality and computational performance.}, number={9}, journal={Advances in Water Resources}, publisher={Elsevier BV}, author={Mirghani, Baha Y. and Mahinthakumar, Kumar G. and Tryby, Michael E. and Ranjithan, Ranji S. and Zechman, Emily M.}, year={2009}, month={Sep}, pages={1373–1385} }
 @inproceedings{kumar_brill_mahinthakumar_ranjithan_2009, title={Characterizing Reactive Contaminant Sources in a Water Distribution System}, ISBN={9780784410363}, url={http://dx.doi.org/10.1061/41036(342)65}, DOI={10.1061/41036(342)65}, abstractNote={Accurate knowledge of the characteristics of the contamination source during a contamination event is necessary for development of any mitigation and control strategy. Contaminant injected in a system is most likely to be reactive with chlorine; however, it is impractical for water quality monitoring systems to be able to monitor for the presence of all possible contaminants. In any distribution system, chlorine levels and other water quality parameters (pH, conductance, etc.) are routinely monitored to maintain the prescribed disinfection capacity. Any reactive contaminant would affect the chlorine levels resulting in deviations in the expected chlorine levels from those expected under normal operating conditions. Anomalies in the chlorine concentration from that of the expected value can be used as a surrogate to characterize the contaminant source in the system. In the absence of knowing the reactive characteristics of the contaminants, the location of injection, and injection pattern, source identification becomes a difficult problem to solve. Source identification can be posed as an inverse problem. In earlier work authors investigated the effect of the order of reaction kinetics of the contaminant with chlorine and its impact on source identification problem assuming the reaction kinetics to be known. That work is extended to investigate a methodology to address the source identification problem based on chlorine measurements, and the effects of different uncertain contamination conditions. Findings from a range of scenarios will be presented and discussed.}, booktitle={World Environmental and Water Resources Congress 2009}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, G and Ranjithan, Ranji}, year={2009}, month={May} }
 @article{vankayala_sankarasubramanian_ranjithan_mahinthakumar_2009, title={Contaminant Source Identification in Water Distribution Networks Under Conditions of Demand Uncertainty}, volume={10}, ISSN={["1527-5930"]}, DOI={10.1080/15275920903140486}, abstractNote={Water distribution systems are susceptible to accidental and intentional chemical or biological contamination that could result in adverse health impact to the consumers. This study focuses on a water distribution forensics problem, contaminant source identification, subject to water demand uncertainty. Due to inherent variability in water consumption levels, demands at consumer nodes remain one of the major sources of uncertainty. In this research, the nodal demands are considered to be stochastic in nature and are varied using Gaussian and Autoregressive models. A hypothetical source identification problem is constructed by simulating observations at the sensor nodes from an arbitrary contaminant source. A simulation-optimization approach is used to solve the source identification problem with EPANET tool as the simulator and Genetic Algorithm (GA) as the optimizer. The goal is to find the source location and concentration by minimizing the difference between the simulated and observed concentrations at the sensor nodes. Two variations of GA, stochastic GA and noisy GA are applied to the same problem for comparison. Results show that noisy GA is more robust and is less computationally expensive than stochastic GA in solving the source identification problem. Moreover, the autoregressive demand uncertainty model better represents the uncertainty in the source identification process than the Gaussian model.}, number={3}, journal={ENVIRONMENTAL FORENSICS}, author={Vankayala, Praveen and Sankarasubramanian, A. and Ranjithan, S. Ranji and Mahinthakumar, G.}, year={2009}, pages={253–263} }
 @inproceedings{liu_zechman_brill, jr._mahinthakumar_ranjithan_uber_2008, title={Adaptive Contamination Source Identification in Water Distribution Systems Using an Evolutionary Algorithm-based Dynamic Optimization Procedure}, ISBN={9780784409411}, url={http://dx.doi.org/10.1061/40941(247)123}, DOI={10.1061/40941(247)123}, abstractNote={Accidental drinking water contamination has long been and remains a major threat to water security throughout the world. Consequently, contamination source identification is an important and difficult problem in the managing safety in water distribution systems. This problem involves the characterization of the contaminant source based on observations that are streaming from a set of sensors in the distribution network. Since contamination spread in a water distribution network is relatively quick and unpredictable, rapid identification of the source location and related characteristics is important to take contaminant control and containment actions. As the contaminant event unfolds, the streaming data could be processed over time to adaptively estimate the source characteristics. This provides an estimate of the source characteristics at any time after a contamination event is detected, and this estimate is continually updated as new observations become available. We pose and solve this problem using a dynamic optimization procedure that could potentially provide a real-time response. As time progresses, additional data is observed at a set of sensors, changing the vector of observations that should be predicted. Thus, the prediction error function is updated dynamically, changing the objective function in the optimization model. We investigate a new multi population-based search using an evolutionary algorithm (EA) that at any time represents the solution state that best matches the available observations. The set of populations migrates to represent updated solution states as new observations are added over time. At the initial detection period, non-uniqueness is inherent in the source-identification due to inadequate information, and, consequently, several solutions may predict similarly well. To address nonuniqueness at the initial stages of the search and prevent premature convergence of the EA to an incorrect solution, the multiple populations in the proposed methodology are designed to maintain a set of alternative solutions representing different non-unique solutions. As more observations are added, the EA solutions not only migrate to better solution states, but also reduce the number of solutions as the degree of non-uniqueness diminishes. This new dynamic optimization algorithm adaptively converges to the best solution(s) to match the observations available at any time. The new method will be demonstrated for a contamination source identification problem in an illustrative water distribution network.}, booktitle={Water Distribution Systems Analysis Symposium 2006}, publisher={American Society of Civil Engineers}, author={Liu, Li and Zechman, Emily M. and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S. and Uber, James}, year={2008}, month={Mar} }
 @inproceedings{zechman_brill, jr._mahinthakumar_ranjithan_uber_2008, title={Addressing Non-uniqueness in a Water Distribution Contaminant Source Identification Problem}, ISBN={9780784409411}, url={http://dx.doi.org/10.1061/40941(247)126}, DOI={10.1061/40941(247)126}, abstractNote={The source of contamination in a water distribution system may be identified through a simulation-optimization approach. The optimization method searches for the contaminant source characteristics by iteratively estimating the contaminant plume concentrations until they match observations at sensors. The amount of information available for characterizing the source depends on the number and spatial locations of the sensors, as well as on the temporally varying stream of sensed data. The accuracy of the source characterization depends on the amount of observations available. A major factor affecting this accuracy is the degree of non-uniqueness present in the problem, which may cause misidentification of the source characteristics. As more sensors are added to the network, the non-uniqueness may be reduced and a unique solution may be identified. Thus, a key consideration when solving these problems is to assess whether the solution identified is unique, and if not, what other possible solutions are present. A systematic search for a set of alternatives that are maximally different in solution characteristics can be used to address and quantify non-uniqueness. For example, if the most different set of solutions that are identified by a search procedure are very similar, then that solution will be considered as the unique solution with a higher degree of certainty. Alternatively, identification of a set of maximally different solutions that vary widely in solution characteristics will indicate that nonuniqueness is present in the problem, and the range of solutions can be used as a general representation of the amount of non-uniqueness. This paper investigates the use of evolutionary algorithm (EA)-based alternatives generation procedures to quantify and address non-uniqueness present in a contaminant source identification problem for a water distribution network. As additional sensors may decrease the amount of non-uniqueness, several sensor configurations will be tested to investigate and quantify the improvement in uniqueness as more information is used in the source characterization.}, booktitle={Water Distribution Systems Analysis Symposium 2006}, publisher={American Society of Civil Engineers}, author={Zechman, Emily M. and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S. and Uber, James}, year={2008}, month={Mar} }
 @inproceedings{liu_brill, jr._mahinthakumar_ranjithan_2008, title={Contaminant Source Characterization Using Logistic Regression and Local Search Methods}, ISBN={9780784409763}, url={http://dx.doi.org/10.1061/40976(316)503}, DOI={10.1061/40976(316)503}, abstractNote={Given a set of contaminant concentration observations at sensors in a water distribution network, an inverse problem can be constructed to identify the contaminant source characteristics (including location, strength and release history) by coupling a water distribution simulation model with an optimization method. This approach, however, requires a large number of time-consuming simulation runs to evaluate potential solutions, and it may be difficult to converge on the best solution or set of possible solutions within a reasonable computational time. For this reason, it is desirable to appropriately reduce the decision space over which the optimization procedure must search to reduce the computational burden and to potentially produce faster convergence. We propose a method to reduce the decision space by efficiently identifying the probability of each point or demand node being a contaminant source location using mostly off-line computations. Then, the most likely source locations are used as a good starting point for local search methods to obtain the optimal injection profile(s) to match the observed concentration profile(s) over time. The proposed approach is demonstrated for a contamination source identification problem using an illustrative water distribution network.}, booktitle={World Environmental and Water Resources Congress 2008}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, Jr., E. Downey and Mahinthakumar, G. and Ranjithan, S.}, year={2008}, month={May} }
 @inproceedings{kumar_brill_ranjithan_mahinthakumar_uber_2008, title={Source Identification for Contamination Events Involving Reactive Contaminants}, ISBN={9780784409763}, url={http://dx.doi.org/10.1061/40976(316)504}, DOI={10.1061/40976(316)504}, abstractNote={The problem of contaminant source identification in a water distribution system can be solved as an inverse problem using a simulation-optimization approach. The optimization method searches for contaminant source characteristics which lead to matching observations at the sensors. Accuracy of identification depends on the quantity and quality of data available at the sensors. The present state of the art in water quality monitoring sensors does not always allow for the detection of different kinds of contaminants in the system and they do not provide continuous contaminant concentration measurements. Some sensors provide an event detection trigger based on a specific concentration threshold yielding a binary detection/no-detection signal. Sensors also routinely monitor water quality parameters such as chlorine and pH. For example, a contaminant present in the system may react with chlorine leading to changes in chlorine-based water quality indicators. These anomalies (or deviations) in the observed water quality in the distribution system can be used as indicators of presence of contaminants in the system. A methodology for identifying the source characteristics using sensors outputting binary signals was presented by the authors recently. In the present study we investigate the interaction of reactive contaminants with chlorine in the system and its effect on water quality indicators. These anomalies indicating the presence or absence of contaminants will be used for determination of source characteristics using an evolutionary algorithm-based simulation-optimization approach.}, booktitle={World Environmental and Water Resources Congress 2008}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Brill, E. Downey and Ranjithan, S. Ranji and Mahinthakumar, G. and Uber, J.}, year={2008}, month={May} }
 @inproceedings{liu_brill, jr._mahinthakumar_uber_zechman_ranjithan_2007, title={Considering Demand Variability and Measurement Uncertainties in Adaptive Source Characterization in Water Distribution Networks}, ISBN={9780784409275}, url={http://dx.doi.org/10.1061/40927(243)502}, DOI={10.1061/40927(243)502}, abstractNote={Characterizing the sources of contamination in water distribution networks continues to be a challenging problem. Several methods have been reported to address this problem. The authors previously presented and continue to investigate an adaptive search procedure that attempts to solve this problem under dynamic conditions. Since demand variability and measurement errors contribute significantly to the quality of the solutions obtained as well as the time to solve the problem, we investigate these effects on the adaptive dynamic optimization procedure. First, the effects of these variabilities and uncertainties on the solutions obtained under deterministic conditions are evaluated. Second, we incorporate them such that the search for the source characterization is conducted under noisy conditions. This paper reports the results from these investigations based on an investigation conducted for an illustrative water distribution network.}, booktitle={World Environmental and Water Resources Congress 2007}, publisher={American Society of Civil Engineers}, author={Liu, Li and Brill, Jr., E. Downey and Mahinthakumar, G. and Uber, James and Zechman, Emily M. and Ranjithan, S.}, year={2007}, month={May} }
 @inproceedings{kumar_zechman_brill_mahinthakumar_ranjithan_uber_2007, title={Evaluation of Non-Uniqueness in Contaminant Source Characterization Based on Sensors with Event Detection Methods}, ISBN={9780784409275}, url={http://dx.doi.org/10.1061/40927(243)513}, DOI={10.1061/40927(243)513}, abstractNote={Due to the present state of sensor technology, during a water distribution contamination event, sensors may be able to detect only the presence of a contaminant and not necessarily the complete concentration profile. Some sensors trigger a detection based on a specified threshold concentration of observation, yielding a binary detection/no-detection signal. Event detection can also be based on observed concentrations of water quality parameters, such as pH and chlorine, which are routinely measured. These concentration observations are then processed through event detection algorithms to yield a detection/no-detection signal. These event detection techniques filter the measured concentrations at sensors to produce a discrete signal. When using this filtered information to characterize the contamination source, the certainty of identifying a unique solution is likely reduced, i.e., a set of widely different source characteristics may provide a match for the sensor observations. The authors previously presented an evolutionary algorithm-based procedure for source characterization and for assessing nonuniqueness by generating a set of maximally different alternatives. The procedure is extended here to characterize a contaminant source and any non-uniqueness arising by using sensor information processed through different event detection methods.}, booktitle={World Environmental and Water Resources Congress 2007}, publisher={American Society of Civil Engineers}, author={Kumar, Jitendra and Zechman, E. M. and Brill, E. D. and Mahinthakumar, G. and Ranjithan, S. and Uber, J.}, year={2007}, month={May} }
 @article{sayeed_mahinthakumar_karonis_2007, title={GRID-enabled solution of groundwater inverse problems on the TeraGrid network}, volume={83}, ISSN={["0037-5497"]}, DOI={10.1177/0037549707084936}, abstractNote={ Grid-computing environments are becoming increasingly popular for scientific computing due to the significant increase in capacity that they represent when compared to a single computational resource (e.g., a single cluster), their ubiquitous availability and advances in grid middleware components. Several such specialized grid environments are now available for users in the commercial and research sectors. One such effort for research is the TeraGrid, consisting of a collection of geographically distributed heterogeneous supercomputer resources including data storage resources. Parallel implementations for these environments are inherently multilevel and obtaining efficient mapping of work to processors can be eXtremely challenging. This paper eXtends an eXisting MPI application to the grid via the use of grid-enabled MPI libraries. The application uses a simulation-optimization framework involving coarse-grained parallelism in the optimizer and fine-grained parallelism in the finite-element-based simulator. Using parallelism at both these levels is essential for problems involving computationally intensive simulation steps. A hierarchical grid architecture consisting of a collection of supercomputers is ideally suited for these types of problems as a good application-to-architecture mapping can be obtained with a proper implementation. This paper presents the performance results of our implementation on the TeraGrid network consisting of three geographically distributed supercomputers. }, number={6}, journal={SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL}, author={Sayeed, Mohamed and Mahinthakumar, Kumar and Karonis, Nicholas T.}, year={2007}, month={Jun}, pages={437–448} }
 @article{raghavachar_mahinthakumar_worley_zechman_ranjithan_2007, title={Parallel Performance Modeling using a Genetic Programming-based Error Correction Procedure}, volume={83}, ISSN={0037-5497 1741-3133}, url={http://dx.doi.org/10.1177/0037549707084691}, DOI={10.1177/0037549707084691}, abstractNote={ Performance models of high performance computing (HPC) applications are important for several reasons. First, they provide insight to designers of HPC systems on the role of subsystems such as the processor or the network in determining application performance. Second, they allow HPC centers more accurately to target procurements to resource requirements. Third, they can be used to identify application performance bottlenecks and to provide insights about scalability issues. The suitability of a performance model, however, for a particular performance investigation is a function of both the accuracy and the cost of the model. }, number={7}, journal={SIMULATION}, publisher={SAGE Publications}, author={Raghavachar, Kavitha and Mahinthakumar, G. and Worley, Patrick and Zechman, Emily and Ranjithan, Ranji}, year={2007}, month={Jul}, pages={515–527} }
 @inbook{mahinthakumar_von laszewski_ranjithan_brill_uber_harrison_sreepathi_zechman_2006, place={Berlin Heidelberg}, series={Lecture Notes in Computer Science}, title={An Adaptive Cyberinfrastructure for Threat Management in Urban Water Distribution Systems}, volume={3993}, ISBN={9783540343837 9783540343844}, ISSN={0302-9743 1611-3349}, url={http://dx.doi.org/10.1007/11758532_54}, DOI={10.1007/11758532_54}, abstractNote={Threat management in drinking water distribution systems involves real-time characterization of any contaminant source and plume, design of control strategies, and design of incremental data sampling schedules. This requires dynamic integration of time-varying measurements along with analytical modules that include simulation models, adaptive sampling procedures, and optimization methods. These modules are compute-intensive, requiring multi-level parallel processing via computer clusters. Since real-time responses are critical, the computational needs must also be adaptively matched with available resources. This requires a software system to facilitate this integration via a high-performance computing architecture such that the measurement system, the analytical modules and the computing resources can mutually adapt and steer each other. This paper describes the development of such an adaptive cyberinfrastructure system facilitated by a dynamic workflow design.}, booktitle={Computational Science – ICCS 2006}, publisher={Springer}, author={Mahinthakumar, Kumar and von Laszewski, Gregor and Ranjithan, Ranji and Brill, Downey and Uber, Jim and Harrison, Ken and Sreepathi, Sarat and Zechman, Emily}, editor={Alexandrov, V.N. and Albada, G.D. and Sloot, P.M.A. and Dongarra, J.Editors}, year={2006}, pages={401–408}, collection={Lecture Notes in Computer Science} }
 @article{mahinthakumar_2006, title={Parallel computing in civil engineering}, volume={20}, DOI={10.1061/(asce)0887-3801(2006)20:2(75)}, abstractNote={This issue marks the beginning of a new initiative in parallel computing. I would like to start with the statement by Grace Hopper 1910–1992 , pioneer computer scientist and U.S. Navy admiral, “In pioneer days they used oxen for heavy pulling, and when one ox couldn’t budge a log, they didn’t try to grow a larger ox but used more oxen. We shouldn’t be trying for bigger computers, but for more systems of computers.” The essence of this message is that it is very difficult to build a single processor computer that can handle the processing needs of any application. In other words, no matter how powerful a single processor computer is, there are always applications that require the power of parallel processing. The problems that we face as civil engineers are rapidly changing with increasing emphasis on homeland security, civil infrastructure protection, sustainability, and smart designs. These changing focuses put a premium on large-scale computation and real-time processing for many applications. Enabling parallel computation for these applications is not trivial due to inherent complexities of emerging parallel computing environments, lack of easily usable software libraries for these environments, and the dynamic nature of data and computation needs for some real-time processing applications. Consumer needs and economic reality have changed the face of parallel computing dramatically over the last two decades with the infusion of a new generation of supercomputers with hierarchical memory subsystems, nonuniform processor configurations, and heterogeneous geographically distributed grid computing environments. Obtaining good performance on these environments for real-world applications is extremely challenging even with available middleware tools such as MPI, Globus, Matlab distributed computing toolbox, and parallel numerical software such as PETSc, SCALAPACK, DAKOTA, ParMETIS, and Aztec. Therefore, prospective users such as civil engineers are forced to develop their own algorithms and/or implementations for their application needs. Despite the fact that parallel computing has been an active research area for the last two decades and that the demand for parallel computing is increasing in civil engineering, the leading computing journal in civil engineering, JCCE, has seen very few papers in this area averaging about one article per year . This editorial’s purpose is to change this trend by issuing a call to the civil engineering community to support an initiative in parallel computing. I will next address the type of parallel computing articles we would like to publish in JCCE, i.e., what do we want in a parallel computing article for JCCE? Prospective authors may consider the following questions:}, number={2}, journal={Journal of Computing in Civil Engineering}, author={Mahinthakumar, K.}, year={2006}, pages={75} }
 @article{mahinthakumar_sayeed_2006, title={Reconstructing groundwater source release histories using hybrid optimization approaches}, volume={7}, ISSN={["1527-5930"]}, DOI={10.1080/15275920500506774}, abstractNote={Reconstructing release histories of contaminant sources in groundwater is an important environmental forensics problem for identifying responsible parties and allocating remediation costs in a contamination incident. Such problems typically require the solution of an inverse problem. This paper investigates and compares several hybrid optimization approaches that combine genetic algorithms with a number of local search approaches for solving these problems. Previous studies in this area have focused on simple two-dimensional and/or single-source release history problems. The problems solved in this article address both single- and multiple-source releases in three-dimensional heterogeneous flow fields. A parallel computing environment is used to handle the heavy computational needs of these problems. The results indicate that hybrid optimization methods, especially those that combine an initial global heuristic approach (e.g., genetic algorithms) with a subsequent gradient-based local search approach (e.g., conjugate gradients) are very effective in solving these problems.}, number={1}, journal={ENVIRONMENTAL FORENSICS}, author={Mahinthakumar, GK and Sayeed, M}, year={2006}, month={Mar}, pages={45–54} }
 @inproceedings{zechman_mirghani_clayton_mahinthakumar_ranji ranjithan_2006, title={Use of Surrogate Models for a Groundwater Pollutant Source Characterization Problem}, ISBN={9780784408568}, url={http://dx.doi.org/10.1061/40856(200)117}, DOI={10.1061/40856(200)117}, abstractNote={This paper investigates a groundwater source identification problem in which concentrations at observation wells are used to reconstruct the pollution loading scenario. This inverse problem is solved using a simulation-optimization approach using evolutionary algorithms to conduct the search. Varying levels of complexity may be modeled, leading to different levels of accuracy in predictions of source location, size, and concentration. More complex models will increase the computational effort needed to model pollutant transport as part of a search procedure. In addition, the amount of non-uniqueness will typically increase as the complexity of the problem increases. This paper describes an investigation of surrogate modeling procedures and methods to generate very different solutions to characterize groundwater pollutant source under varying degrees of problem complexity.}, booktitle={World Environmental and Water Resource Congress 2006}, publisher={American Society of Civil Engineers}, author={Zechman, Emily M. and Mirghani, Baha and Clayton, Matthew and Mahinthakumar, G. and Ranji Ranjithan, S.}, year={2006}, month={May} }
 @inproceedings{zechman_mirghani_mahinthakumar_ranjithan_2005, title={A Genetic Programming-Based Surrogate Model Development and Its Application to a Groundwater Source Identification Problem}, ISBN={9780784407929}, url={http://dx.doi.org/10.1061/40792(173)341}, DOI={10.1061/40792(173)341}, abstractNote={This paper investigates a groundwater source identification problem in which chemical signals at observation wells are used to reconstruct the pollution loading scenario. This inverse problem is solved using a simulation-optimization approach that uses a genetic algorithm to conduct the search. As the numerical pollution-transport model is solved iteratively during the heuristic search, the evolutionary search can be in general computationally intensive. This is addressed by constructing a surrogate modeling approach that is able to predict quickly the concentration profiles at the observation wells. A genetic program is used in the development of the surrogate models that provides an acceptable prediction performance. The surrogate model, which replaces the numerical simulation model, is then coupled with the evolutionary search procedure to solve the inverse problem. The results will illustrate 1) the performance of the surrogate model in predicting the concentration compared with the predictions using the original numerical model, and 2) the quality of the solution to the inverse problem obtained using the surrogate model to that obtained using the numerical model.}, booktitle={Impacts of Global Climate Change}, publisher={American Society of Civil Engineers}, author={Zechman, Emily and Mirghani, Baha and Mahinthakumar, G. and Ranjithan, S. Ranji}, year={2005}, month={Jul} }
 @article{mahinthakumar_moline_webb_2005, title={An analysis of periodic tracers for subsurface characterization}, volume={41}, ISSN={["1944-7973"]}, DOI={10.1029/2005wr004190}, abstractNote={This paper investigates the feasibility of periodic tracers (i.e., tracers injected in a periodic waveform) for subsurface characterization using numerical simulations. From a theoretical point of view, periodic tracers offer many advantages over conventional pulse or continuous tracers. For example, periodic tracers are more sensitive to various transport and reaction processes and are less susceptible to corruption by environmental noise. With the recent advances in computer‐controlled injection technologies, time is now ripe for investigating the feasibility of these tracers for laboratory and field tracer tests. A series of numerical sensitivity analyses are performed in this study for assessing the sensitivity of these signals for various transport and reaction phenomena in the subsurface. Sensitivity coefficients are calculated and compared for conventional and periodic tracers for various transport phenomena. An inverse modeling case study is performed to evaluate the potential of periodic tracers for detecting the location and concentration of biological active zones. The results indicate that periodic tracers have the potential to perform significantly better than conventional tracers.}, number={12}, journal={WATER RESOURCES RESEARCH}, author={Mahinthakumar, GK and Moline, GR and Webb, OF}, year={2005}, month={Dec} }
 @article{sayeed_mahinthakumar_2005, title={Efficient parallel implementation of hybrid optimization approaches for solving groundwater inverse problems}, volume={19}, DOI={10.1061/(ASCE)0887-3801(2005)19:4(329)}, abstractNote={Inverse problems that are constrained by large-scale partial differential equation (PDE) systems demand very large computational resources. Solutions to these problems generally require the solution of a large number of complex PDE systems. Three-dimensional groundwater inverse problems fall under this category. In this paper, we describe the implementation of a parallel simulation-optimization framework for solving PDE-based inverse problems and demonstrate it for the solution of groundwater contaminant source release history reconstruction problems that are of practical importance. The optimization component employs several optimization algorithms, including genetic algorithms (GAs) and several local search (LS) approaches that can be used in a hybrid mode. This hybrid GA-LS optimizer is used to drive a parallel finite-element (FEM) groundwater forward transport simulator. Parallelism is exploited within the transport simulator (fine grained parallelism) as well as the optimizer (coarse grained parallelism) through the exclusive use of the Message Passing Interface (MPI) communication library. Algorithmic and parallel performance results are presented for an IBM SP3 supercomputer. Simulation and performance results presented in this paper illustrate that an effective combination of efficient optimization algorithms and parallel computing can enable solution to three-dimensional groundwater inverse problems of a size and complexity not attempted before.}, number={4}, journal={Journal of Computing in Civil Engineering}, author={Sayeed, M. and Mahinthakumar, G. K.}, year={2005}, pages={329–340} }
 @article{gupta_kripakaran_mahinthakumar_baugh_2005, title={Genetic algorithm-based decision support for optimizing seismic response of piping systems}, volume={131}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-14544294041&partnerID=MN8TOARS}, DOI={10.1061/(asce)0733-9445(2005)131:3(389)}, abstractNote={This paper describes computational approaches used in a prototype decision support system (DSS) for seismic design and performance evaluation of piping supports. The DSS is primarily based on a genetic algorithm (GA) that uses finite element analyses, and an existing framework for high performance distributed computing on workstation clusters. A detailed discussion is presented on various issues related to the development of an efficient GA implementation for evaluating the trade-off between the number of supports and cost. An integer string representation of the type used in some existing studies, for instance, is shown to be inferior to a binary string representation, which is appropriate when supports are modeled as axially rigid. A novel seeding technique, which overcomes the inefficiencies of conventional methods in the context of pipe support optimization, is also presented. Finally, an efficient crossover scheme is proposed for generating trade-off curves and the approach is validated with respect ...}, number={3}, journal={Journal of Structural Engineering}, author={Gupta, A. and Kripakaran, P. and Mahinthakumar, G. K. and Baugh, J. W.}, year={2005}, pages={389–398} }
 @article{mahinthakumar_sayeed_2005, title={Hybrid genetic algorithm - Local search methods for solving groundwater source identification inverse problems}, volume={131}, DOI={10.1061/(ASCE)0733-9496(2005)131:1(45)}, abstractNote={Identifying contaminant sources in groundwater is important for developing effective remediation strategies and identifying responsible parties in a contamination incident. Groundwater source identification problems require solution of an inverse problem. Gradient-based local optimization approaches are among the most popular approaches for solving these inverse problems. While these methods are sometimes appropriate, they are not effective for problems that contain several local minima and for problems where the decision space is highly discontinuous or convoluted. For these types of problems, heuristic global search approaches such as genetic algorithms (GAs) are more effective. But methods such as GAs are inefficient for fine-tuning solutions once a near global minimum is found. For problems that contain several local minima, a hybrid approach starting with a global method and then fine-tuning with a local method may be more attractive, especially if the decision space is reasonably well behaved near t...}, number={1}, journal={Journal of Water Resources Planning and Management}, author={Mahinthakumar, G. K. and Sayeed, M.}, year={2005}, pages={45–57} }
 @inproceedings{zechman_mahinthakumar_ranjithan_2005, title={Investigation and Demonstration of an Evolutionary Computation-Based Model Correction Procedure for a Numerical Simulation Model}, ISBN={9780784407929}, url={http://dx.doi.org/10.1061/40792(173)346}, DOI={10.1061/40792(173)346}, abstractNote={Traditional model calibration attempts to correct a model so that the model output will match a set of system observations by tweaking a set of model parameters. Potential model structural error limits, however, the effectiveness and accuracy of calibration, undermining the predictive capabilities of the calibrated model. An evolutionary computation-based model error correction procedure that couples an evolutionary algorithm and a genetic program was previously developed and tested for two analytical models. Due to nonuniqueness in the solution space, numerous forms of correction terms that similarly fit the observation data were found. This procedure is further investigated to explore and identify alternative correction terms that not only provide a good fit but also results in good prediction performance. This approach is then demonstrated using a numerical groundwater contaminant transport simulation model.}, booktitle={Impacts of Global Climate Change}, publisher={American Society of Civil Engineers}, author={Zechman, Emily and Mahinthakumar, G. and Ranjithan, S. Ranji}, year={2005}, month={Jul} }
 @article{narasimhan_ward_kruse_guddati_mahinthakumar_2004, title={A high resolution computer model for sound propagation in the human thorax based on the Visible Human data set}, volume={34}, ISSN={["1879-0534"]}, DOI={10.1016/S0010-4825(03)00044-1}, abstractNote={A parallel supercomputer model based on realistic tissue data is developed for sound propagation in the human thorax and the sound propagation behavior is analyzed under various conditions using artificial sound sources. The model uses the Visible Human®1 male data set for a realistic representation of the human thorax. The results were analyzed in time and frequency domains. The analysis suggests that lower frequencies of around 100Hz are more effectively transmitted through the thorax and that the spatial confinement of sound waves within the thorax results in a resonance effect at around 1500Hz. The results confirm previous studies that show the size of the thorax plays a significant role in the type of sound generated at the chest wall.}, number={2}, journal={COMPUTERS IN BIOLOGY AND MEDICINE}, author={Narasimhan, C and Ward, R and Kruse, KL and Guddati, M and Mahinthakumar, G}, year={2004}, month={Mar}, pages={177–192} }
 @article{shin_garanzuay_yiacoumi_tsouris_gu_mahinthakumar_2004, title={Kinetics of soil ozonation: an experimental and numerical investigation}, volume={72}, DOI={10.1016/j.conhyd.2003.11.003}, abstractNote={This study investigates the use of ozone for soil remediation. Batch experiments, in which ozone-containing gas was continuously recycled through a soil bed, were conducted to quantify the rate of ozone self-decomposition and the rates of ozone interaction with soil organic and inorganic matter. Column experiments were conducted to measure ozone breakthrough from a soil column. Parameters such as ozone flow rate, soil mass, and ozonation time were varied in these experiments. After ozone concentration had reached steady state, the total organic carbon concentration was measured for all soil samples. The ozonation efficiency, represented by the ratio of soil organic matter consumed to the total ozone input, was quantified for each experiment. Numerical simulations were conducted to simulate experimentally obtained column breakthrough curves. Experimentally obtained kinetic rate constants were used in these simulations, and the results were in good agreement with experimental data. In contrast to previous studies in which soil inorganic matter was completely ignored, our experiments indicate that soil inorganic matter may also promote depletion of ozone, thus reducing the overall ozonation efficiency. Three-dimensional numerical simulations were conducted to predict the efficacy of ozonation for soil remediation in the field. These simulations indicate that such ozonation can be very effective, provided that effective circulation of ozone is achieved through appropriately placed wells.}, number={04-Jan}, journal={Journal of Contaminant Hydrology}, author={Shin, W. T. and Garanzuay, X. and Yiacoumi, S. and Tsouris, C. and Gu, B. H. and Mahinthakumar, G. K.}, year={2004}, pages={227–243} }
 @article{shin_garanzuay_yiacoumi_tsouris_gu_mahinthakumar_2004, title={Kinetics of soil ozonation: an experimental and numerical investigation}, volume={72}, ISSN={0169-7722}, url={http://dx.doi.org/10.1016/j.jconhyd.2003.11.003}, DOI={10.1016/j.jconhyd.2003.11.003}, abstractNote={This study investigates the use of ozone for soil remediation. Batch experiments, in which ozone-containing gas was continuously recycled through a soil bed, were conducted to quantify the rate of ozone self-decomposition and the rates of ozone interaction with soil organic and inorganic matter. Column experiments were conducted to measure ozone breakthrough from a soil column. Parameters such as ozone flow rate, soil mass, and ozonation time were varied in these experiments. After ozone concentration had reached steady state, the total organic carbon concentration was measured for all soil samples. The ozonation efficiency, represented by the ratio of soil organic matter consumed to the total ozone input, was quantified for each experiment. Numerical simulations were conducted to simulate experimentally obtained column breakthrough curves. Experimentally obtained kinetic rate constants were used in these simulations, and the results were in good agreement with experimental data. In contrast to previous studies in which soil inorganic matter was completely ignored, our experiments indicate that soil inorganic matter may also promote depletion of ozone, thus reducing the overall ozonation efficiency. Three-dimensional numerical simulations were conducted to predict the efficacy of ozonation for soil remediation in the field. These simulations indicate that such ozonation can be very effective, provided that effective circulation of ozone is achieved through appropriately placed wells.}, number={1-4}, journal={Journal of Contaminant Hydrology}, publisher={Elsevier BV}, author={Shin, Won-Tae and Garanzuay, Xandra and Yiacoumi, Sotira and Tsouris, Costas and Gu, Baohua and Mahinthakumar, G.(Kumar)}, year={2004}, month={Aug}, pages={227–243} }
 @article{mahinthakumar_saied_2002, title={A hybrid MPI-OpenMP implementation of an implicit finite-element code on parallel architectures}, volume={16}, ISSN={["1094-3420"]}, DOI={10.1177/109434200201600402}, abstractNote={Summary The hybrid MPI-OpenMP model is a natural parallel programming paradigm for emerging parallel architectures that are based on symmetric multiprocessor (SMP) clusters. This paper presents a hybrid implementation adapted for an implicit finite-element code developed for groundwater transport simulations. The original code was parallelized for distributed memory architectures using MPI (Message Passing Interface) using a domain decomposition strategy. OpenMP directives were then added to the code (a straightforward loop-level implementation) to use multiple threads within each MPI process. To improve the OpenMP performance, several loop modifications were adopted. The parallel performance results are compared for four modern parallel architectures. The results show that for most of the cases tested, the pure MPI approach outperforms the hybrid model. The exceptions to this observation were mainly due to a limitation in the MPI library implementation on one of the architectures. A general conclusion is that while the hybrid model is a promising approach for SMP cluster architectures, at the time of this writing, the payoff may not be justified for converting all existing MPI codes to hybrid codes. However, improvements in OpenMP compilers combined with potential MPI limitations in SMP nodes may make the hybrid approach more attractive for a broader set of applications in the future. }, number={4}, journal={INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS}, author={Mahinthakumar, G and Saied, F}, year={2002}, pages={371–393} }