@article{athe_dinh_gupta_2024, title={Knowledge representation to support EMDAP implementation in advanced reactor licensing applications}, volume={428}, ISSN={["1872-759X"]}, url={https://doi.org/10.1016/j.nucengdes.2024.113526}, DOI={10.1016/j.nucengdes.2024.113526}, journal={NUCLEAR ENGINEERING AND DESIGN}, author={Athe, Paridhi and Dinh, Nam and Gupta, Abhinav}, year={2024}, month={Nov} }
 @inproceedings{knowledge representation to support emdap implementation in advanced reactor licensing applications_2023, url={https://www.ans.org/meetings/nureth20/session/view-1883/}, booktitle={20th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-20)}, year={2023}, month={Aug} }
 @article{athe_athe_srivastava_athe_shukla_2022, title={Design of Multiple Resonant Reflectance Filter Using One-Dimensional Fibonacci Superconductor Photonic Crystal}, volume={35}, ISSN={["1557-1947"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85132587348&partnerID=MN8TOARS}, DOI={10.1007/s10948-022-06318-1}, number={10}, journal={JOURNAL OF SUPERCONDUCTIVITY AND NOVEL MAGNETISM}, author={Athe, Pallavi and Athe, Pratik and Srivastava, Sanjay and Athe, Paridhi and Shukla, Surendra Kumar}, year={2022}, month={Jun} }
 @article{athe_jones_dinh_2021, title={Assessment of the Predictive Capability of VERA-CS for CASL Challenge Problems}, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85127455143&partnerID=MN8TOARS}, DOI={10.1115/1.4050248}, abstractNote={Abstract
               This paper describes the process for assessing the predictive capability of the Consortium for the advanced simulation of light-water reactors (CASL) virtual environment for reactor applications code suite (VERA—CS) for different challenge problems. The assessment process is guided by the two qualitative frameworks, i.e., phenomena identification and ranking table (PIRT) and predictive capability maturity model (PCMM). The capability and credibility of VERA codes (individual and coupled simulation codes) are evaluated. Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements (based on PIRT) against which the VERA software is evaluated. This approach, in turn, enables the focused assessment of only those capabilities that are relevant to the challenge problem. The credibility assessment using PCMM is based on different decision attributes that encompass verification, validation, and uncertainty quantification (VVUQ) of the CASL codes. For each attribute, a maturity score from zero to three is assigned to ascertain the acquired maturity level of the VERA codes with respect to the challenge problem. Credibility in the assessment is established by mapping relevant evidence obtained from VVUQ of codes to the corresponding PCMM attribute. The illustration of the proposed approach is presented using one of the CASL challenge problems called chalk river unidentified deposit (CRUD) induced power shift (CIPS). The assessment framework described in this paper can be considered applicable to other M & S code development efforts.}, number={2}, journal={Journal of Verification, Validation and Uncertainty Quantification}, author={Athe, P. and Jones, C. and Dinh, N.}, year={2021} }
 @article{lee_lin_athe_dinh_2021, title={Development of the Machine Learning-based Safety Significant Factor Inference Model for Diagnosis in Autonomous Control System}, volume={162}, ISSN={["1873-2100"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85109449538&partnerID=MN8TOARS}, DOI={10.1016/j.anucene.2021.108443}, abstractNote={As a critical component to the autonomous control system, Digital Twin for Diagnosis (DT-D) is a virtual replica of physical systems for an accurate understanding of reactor states. Since the physical damage state cannot be measured directly in transient or accident conditions, safety significant factor (SSF) is introduced as a surrogate index for physical damage states to support safety-related decision making. This study develops a machine learning (ML) based SSF inference model (SSFIM) using the Recurrent Neural Network (RNN) with acceptable accuracy, generalization capability, effectiveness, and robustness against sensor errors. To demonstrate the capability of the ML-based SSFIM, case studies are implemented on a plant simulator for Experimental Breeder Reactor – II. For partial loss of flow accident scenarios, the SSFIM is able to infer the peak fuel centerline temperature with minimally one sensor. Meanwhile the SSFIM is also found to be robust against manipulated sensor drifts and/or random noises.}, journal={ANNALS OF NUCLEAR ENERGY}, author={Lee, Joomyung and Lin, Linyu and Athe, Paridhi and Dinh, Nam}, year={2021}, month={Nov} }
 @article{lin_athe_rouxelin_avramova_gupta_youngblood_lane_dinh_2022, title={Digital-twin-based improvements to diagnosis, prognosis, strategy assessment, and discrepancy checking in a nearly autonomous management and control system}, volume={166}, ISSN={["1873-2100"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85115958204&partnerID=MN8TOARS}, DOI={10.1016/j.anucene.2021.108715}, abstractNote={The Nearly Autonomous Management and Control System (NAMAC) is a comprehensive control system that assists plant operations by furnishing control recommendations to operators in a broad class of situations. This study refines a NAMAC system for making reasonable recommendations during complex loss-of-flow scenarios with a validated Experimental Breeder Reactor II simulator, digital twins improved by machine-learning algorithms, a multi-attribute decision-making scheme, and a discrepancy checker for identifying unexpected recommendation effects. We assess the performance of each NAMAC component, while we demonstrate and evaluated the capability of NAMAC in a class of loss-of-flow scenarios.}, journal={ANNALS OF NUCLEAR ENERGY}, author={Lin, Linyu and Athe, Paridhi and Rouxelin, Pascal and Avramova, Maria and Gupta, Abhinav and Youngblood, Robert and Lane, Jeffrey and Dinh, Nam}, year={2022}, month={Feb} }
 @inproceedings{application of predictive capability maturity model for assessment of vera-cs for casl challenge problems_2020, url={https://www.ans.org/pubs/proceedings/article-49246/}, booktitle={The Consortium for Advanced Simulation of Light Water Reactors Virtual Meeting, 2020 ANS Virtual Winter Meeting}, year={2020}, month={Nov} }
 @inproceedings{lin_athe_rouxelin_dinh_lane_2020, title={Development and assessment of a nearly autonomous management and control system during a single loss of flow accident}, volume={1}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85095760160&partnerID=MN8TOARS}, DOI={10.1115/ICONE2020-16908}, abstractNote={Abstract
               In this work, a Nearly Autonomous Management and Control (NAMAC) system is designed to diagnose the reactor state and provide recommendations to the operator for maintaining the safety and performance of the reactor. A three layer-hierarchical workflow is suggested to guide the design and development of the NAMAC system. The three layers in this workflow corresponds to knowledge base, digital twin developmental layer (for different NAMAC functions), and NAMAC operational layer. Digital twin in NAMAC is described as knowledge acquisition system to support different autonomous control functions. Therefore, based on the knowledge base, a set of digital twin models is trained to determine the plant state, predict behavior of physical components or systems, and rank available control options. The trained digital twin models are assembled according to NAMAC operational workflow to support decision-making process in selecting the optimal control actions during an accident scenario.
               To demonstrate the capability of the NAMAC system, a case study is designed, where a baseline NAMAC is implemented for operating a simulator of the Experimental Breeder Reactor II (EBR-II) during a single loss of flow accident. Training database for development of digital twin models is obtained by sampling the control parameters in the GOTHIC data generation engine. After the training and testing, the digital twins are assembled into a NAMAC system according to the operational workflow. This NAMAC system is coupled with the GOTHIC plant simulator, and a confusion matrix is generated to illustrate the accuracy and robustness of implemented NAMAC system. It is found that within the training databases, NAMAC can make reasonable recommendations with zero confusion rate. However, when the scenario is beyond the training cases, the confusion rate increases, especially when the scenarios are more severe. Therefore, a discrepancy checker is added to detect unexpected reactor states and alert operators for safety-minded actions.}, booktitle={International Conference on Nuclear Engineering, Proceedings, ICONE}, author={Lin, L. and Athe, P. and Rouxelin, P. and Dinh, N. and Lane, J.}, year={2020} }
 @article{lin_athe_rouxelin_avramova_gupta_youngblood_lane_dinh_2021, title={Development and assessment of a nearly autonomous management and control system for advanced reactors}, volume={150}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85091738050&partnerID=MN8TOARS}, DOI={10.1016/j.anucene.2020.107861}, abstractNote={This paper develops a Nearly Autonomous Management and Control (NAMAC) system for advanced reactors. The development process of NAMAC is characterized by a three layer-layer architecture: knowledge base, the Digital Twin (DT) developmental layer, and the NAMAC operational layer. The DT is described as a knowledge acquisition system from the knowledge base for intended uses in the NAMAC system. A set of DTs with different functions is developed with acceptable performance and assembled according to the NAMAC operational workflow to furnish recommendations to operators. To demonstrate the capability of the NAMAC system, a case study is designed, where a baseline NAMAC is implemented for operating a simulator of the Experimental Breeder Reactor II during a single loss of flow accident. When NAMAC is operated in the training domain, it can provide reasonable recommendations that prevent the peak fuel centerline temperature from exceeding a safety criterion.}, journal={Annals of Nuclear Energy}, author={Lin, L. and Athe, P. and Rouxelin, P. and Avramova, M. and Gupta, A. and Youngblood, R. and Lane, J. and Dinh, N.}, year={2021} }
 @inproceedings{lin_rouxelin_athe_dinh_lane_2020, title={Development and assessment of data-driven digital twins in a nearly autonomous management and control system for advanced reactors}, volume={1}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85095750870&partnerID=MN8TOARS}, DOI={10.1115/ICONE2020-16813}, abstractNote={Abstract
               A critical component of the autonomous control system is the implementation of digital twin (DT) for diagnosing the conditions and prognosing the future transients of physical components or systems. The objective is to achieve an accurate understanding and prediction of future behaviors of the physical components or systems and to guide operating decisions by an operator or an autonomous control system. With specific requirements in the functional, interface, modeling, and accuracy, DTs are developed based on operational and simulation databases. As one of the modeling methods, data-driven methods have been used for implementing DTs since they have more adaptive forms and are able to capture interdependencies that can be overlooked in model-based DTs.
               To demonstrate the capabilities of DTs, a case study is designed for the control of the EBR-II sodium-cooled fast reactor during a single loss of flow accident, where either a complete or a partial loss of flow in one of the two primary sodium pumps is considered. Based on the definition of DTs and the design of autonomous control system, DTs for diagnosis and prognosis are implemented by training feedforward neural networks with suggested inputs, training parameters, and knowledge base. Furthermore, inspired by the validation and uncertainty quantification scheme for scientific computing, a list of sources of uncertainty in input variables, training parameters, and knowledge base is formulated. The objective is to assess qualitative impacts of different sources of uncertainty on the DT errors. It is found that the performance of DT for diagnosis and prognosis satisfies the acceptance criteria within the training databases. Meanwhile, the accuracy of DTs for diagnosis and prognosis is highly affected by multiple sources of uncertainty.}, booktitle={International Conference on Nuclear Engineering, Proceedings, ICONE}, author={Lin, L. and Rouxelin, P. and Athe, P. and Dinh, N. and Lane, J.}, year={2020} }
 @article{athe_dinh_2019, title={A framework for assessment of predictive capability maturity and its application in nuclear thermal hydraulics}, volume={354}, ISSN={["1872-759X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85070311923&partnerID=MN8TOARS}, DOI={10.1016/j.nucengdes.2019.110201}, abstractNote={This work presents a formalized and computerized framework for the assessment of decision regarding the adequacy of a simulation tool for a nuclear reactor application. The decision regarding a code’s adequacy for an application is dependent on the assessment of different attributes that govern verification, validation, and uncertainty quantification of the code. In this work, the focus is on code validation. Therefore, the framework is developed and illustrated from the perspective of decision regarding the validation assessment of a code. Code validation assessment is performed based on the validation test results, data applicability, and process quality assurance factors. The process quality assurance factors warrant the trustworthiness of the evidence and help in checking people and process compliance with respect to the standard requirements. The proposed framework is developed using an argument modeling technique called Goal Structuring Notation (GSN). Goal structuring notation facilitates structural knowledge representation, information abstraction, evidence incorporation, and provides a skeletal structure for quantitative maturity assessment. The decision schema for the development of the decision model is based on the Predictive Capability Maturity Model (PCMM) and Analytic Hierarchy Process (AHP) and formalized using Goal structuring notation. Each decision attribute is formulated as a claim, where the degree of validity of the claim (attribute’s assessment) is expressed using different maturity levels. The GSN representation of the decision model is transformed into a confidence network to provide evidence-based quantitative maturity assessment using the Bayesian network. A metric based on the expected utility of maturity levels, called expected distance metric, is proposed to measure the distance between target maturity and achieved maturity on a scale of zero to one. Expected distance metric helps in comparing the assessment of different attributes and identification of major areas of concern in terms of modeling capability, data needs, and quality of assessment process. The practical application of the framework is demonstrated by a case study on validation assessment of a thermal-hydraulic code for a challenge problem called Departure from Nucleate Boiling (DNB).}, journal={NUCLEAR ENGINEERING AND DESIGN}, publisher={Elsevier BV}, author={Athe, Paridhi and Dinh, Nam}, year={2019}, month={Dec} }
 @inproceedings{athe_dinh_abdel-khalik_2016, title={Investigation of similarity metrics for simulation based scaling analysis}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84992126794&partnerID=MN8TOARS}, booktitle={International Topical Meeting on Advances in Thermal Hydraulics 2016, ATH 2016}, author={Athe, P. and Dinh, N. and Abdel-Khalik, H.}, year={2016}, pages={409–425} }
 @inproceedings{athe_abdel-khalik_2014, title={Are modeling uncertainties properly considered in neutronics data assimilation analysis?}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85014738422&partnerID=MN8TOARS}, booktitle={Proceedings of the International Conference on Physics of Reactors, PHYSOR 2014}, author={Athe, P. and Abdel-Khalik, H.S.}, year={2014} }
 @inproceedings{athe_mertyurek_abdel-khalik_2014, title={Determination of bias, bias uncertainty, and coverage using data assimilation}, volume={111}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84939206281&partnerID=MN8TOARS}, booktitle={Transactions of the American Nuclear Society}, author={Athe, P. and Mertyurek, U. and Abdel-Khalik, H.S.}, year={2014}, pages={1299–1302} }
 @inproceedings{athe_abdel-khalik_2014, title={Mutual information: A generalization of similarity indices}, volume={111}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84939167247&partnerID=MN8TOARS}, booktitle={Transactions of the American Nuclear Society}, author={Athe, P. and Abdel-Khalik, H.}, year={2014}, pages={751–754} }
 @article{athe_shakya_munshi_luke_mewes_2013, title={Characterization of multiphase flow in bubble columns using KT-1 signature and fractal dimension}, volume={33}, ISSN={["1873-6998"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84880359015&partnerID=MN8TOARS}, DOI={10.1016/j.flowmeasinst.2013.05.005}, abstractNote={This work presents the analysis of phase fraction distribution in bubble column reactor using KT-1 signature and fractal dimension. The experiment was carried out using X-ray CT scanner at Leibniz University Hannover. Convolution back projection algorithm is used to obtain the cross-sectional attenuation coefficient distribution. Individual phase distributions of the three phases (air, water and PVC), across the column cross-section, have been obtained using dual energy X-ray tomography. This paper reports measurement of phase fraction distribution at a cross-section level located at 3.2 m from the inlet. The effect of variation of PVC concentration on phase fraction distribution of air and PVC has been investigated. Analysis of reconstructed phase fraction using KT-1 signature and fractal dimension reveals interesting information regarding the flow regime transition and mixing phenomenon in the bubble column.}, journal={FLOW MEASUREMENT AND INSTRUMENTATION}, author={Athe, Paridhi and Shakya, Snehlata and Munshi, Prabhat and Luke, A. and Mewes, D.}, year={2013}, month={Oct}, pages={122–137} }
 @inproceedings{analysis of multiphase flow in bubble column reactor using kt-1 signature and fractal dimension_2012, booktitle={6th International symposium on Process Tomography}, year={2012} }
 @inproceedings{athe_dasgupta_2009, title={A comparative study of 6T, 8T and 9T decanano SRAM cell}, volume={2}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-76249091290&partnerID=MN8TOARS}, DOI={10.1109/ISIEA.2009.5356318}, abstractNote={Data retention and leakage current reduction are among the major area of concern in today's CMOS technology. In this paper 6T, 8T and 9T SRAM cell have been compared on the basis of read noise margin (RNM), write noise margin (WNM), read delay, write delay, data retention voltage (DRV), layout and parasitic capacitance. Corner and statistical simulation of the noise margin has been carried out to analyze the effect of intrinsic parameter fluctuations. Both 8T SRAM cell and 9T SRAM cell provides higher read noise margin (around 4 times increase in RNM) as compared to 6T SRAM cell. Although the size of 9T SRAM cell is around 1.35 times higher than that of the 8T SRAM cell but it provides higher write stability. Due to single ended bit line sensing the write stability of 8T SRAM cell is greatly affected. The 8T SRAM cell provides a write “1” noise margin which is approximately 3 times smaller than that of the 9T SRAM cell. The data retention voltage for 8T SRAM cell was found to be 93.64mV while for 9T SRAM cell it was 84.5mV and for 6T SRAM cell it was 252.3mV. Read delay for 9T SRAM cell is 98.85ps while for 6T SRAM cell it is 72.82ps and for 8T SRAM cell it is 77.72ps. The higher read delay for 9T SRAM cell is attributed to the fact that dual threshold voltage technology has been in it in order to reduce the leakage current. Write delay for 9T SRAM cell was found to be 10ps, 45.47ps for 8T SRAM cell and 8.97ps for 6T SRAM cell. The simulation has been carried out on 90nm CMOS technology. .}, booktitle={2009 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2009 - Proceedings}, author={Athe, P. and Dasgupta, S.}, year={2009}, pages={889–894} }
 @inproceedings{trusting machine learning in nuclear plant control: a reasoning-based discrepancy checker, url={https://www.ans.org/pubs/proceedings/article-49752/}, booktitle={12th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies (NPIC&HMIT 2021)} }