@article{rivas_delipei_davis_bhongale_yang_hou_2024, title={A component diagnostic and prognostic framework for pump bearings based on deep learning with data augmentation}, url={https://doi.org/10.1016/j.ress.2024.110121}, DOI={10.1016/j.ress.2024.110121}, abstractNote={To support the mission of providing safe electricity generation with a high capacity factor, a Predictive Maintenance (PdM) framework using Machine Learning Models (MLM) to optimize component maintenance operations is developed. Using sensor measurements to better predict the true component's Remaining Useful Life (RUL), the PdM framework has the potential to optimize maintenance costs by performing maintenance only when necessary. The PdM framework to pump bearings, the framework consists of a Convolutional Neural Network Autoencoder (CNN-AE) to detect component deviations from normality, a CNN to characterize component fault modes, and a Bayesian Neural Network (BNN) to estimate the component RUL with uncertainty. To increase the number of training samples, a synthetic data generation procedure was developed and includes procedures to recreate the fault-specific characteristic frequencies for diagnostics and the degradation trends for prognostics. The MLMs trained on the synthetic data are tested on the Center for Intelligent Maintenance Systems (IMS) dataset to showcase how well the synthetic data replicates measurement data. Utilizing this framework, the PdM was found to delay maintenance on average by a total of 8.92 years over 40 years and decrease the unexpected component failure rate from 10% to 0% when compared to traditional maintenance philosophies.}, journal={Reliability Engineering & System Safety}, author={Rivas, Andy and Delipei, Gregory Kyriakos and Davis, Ian and Bhongale, Satyan and Yang, Jinan and Hou, Jason}, year={2024}, month={Jul} }
 @article{rivas_delipei_davis_bhongale_hou_2024, title={A system diagnostic and prognostic framework based on deep learning for advanced reactors}, volume={170}, ISSN={["1878-4224"]}, DOI={10.1016/j.pnucene.2024.105114}, abstractNote={To meet the projected energy demand in the next 30 years, advanced reactor designers are looking to maximize system capacity factor to increase economic competitiveness. To maximize capacity factor, operators must minimize the system downtime due to forced shutdowns from transients. To accomplish this, the objective of this work is to develop a System level Diagnostic/Prognostic (SDP) framework based on state-of-the-art Machine Learning Models (MLM) to support operators by detecting and diagnosing anomalous behaviors and predicting the onset of exceeding safety limits. This Accident Management Support Tool (AMST) consists of a Long Short Term Memory Autoencoder (LSTM-AE) model to identify if an anomaly is present, a Convolutional Neural Network (CNN) diagnostic model to characterize that anomaly, and a Long Short Term Memory Dense layered (LSTM-D) model to provide Remaining Useful Life (RUL) predictions. These models were trained on data from various system wide transients that occur at different power levels and at different rates using a digital twin of the Xe-100 Pebble-Bed High Temperature Gas Reactor (PB-HTGR) developed in SimuPACT. This framework’s capability is showcased with a water ingress constant reactivity insertion event that caused the reactor outlet temperature to exceed its safety threshold. This study showed that as the transient progresses, the LSTM-AE detects an anomaly within 20 s of event initiation, the CNN characterization stays steady throughout the transient with a 60 s delay, and the LSTM-D is able to accurately predict the time to threshold as the reactor outlet temperature approaches its safety threshold 720 s after fault initiation.}, journal={PROGRESS IN NUCLEAR ENERGY}, author={Rivas, Andy and Delipei, Gregory Kyriakos and Davis, Ian and Bhongale, Satyan and Hou, Jason}, year={2024}, month={May} }
 @article{rollins_allan_hou_2024, title={Prototyping of a Machine Learning-Based Burnup Measurement Capability for Pebble Bed Reactor Fuel}, volume={4}, ISSN={["1943-748X"]}, url={https://doi.org/10.1080/00295639.2024.2328937}, DOI={10.1080/00295639.2024.2328937}, journal={NUCLEAR SCIENCE AND ENGINEERING}, author={Rollins, Nick and Allan, India and Hou, Jason}, year={2024}, month={Apr} }
 @article{chen_hou_ivanov_2023, title={A hybrid neutronics method with novel fission diffusion synthetic acceleration for criticality calculations}, volume={55}, ISSN={["1738-5733"]}, url={https://doi.org/10.1016/j.net.2022.12.022}, DOI={10.1016/j.net.2022.12.022}, abstractNote={A novel Fission Diffusion Synthetic Acceleration (FDSA) method is developed and implemented as a part of a hybrid neutronics method for source convergence acceleration and variance reduction in Monte Carlo (MC) criticality calculations. The acceleration of the MC calculation stems from constructing a synthetic operator and solving a low-order problem using information obtained from previous MC calculations. By applying the P1 approximation, two correction terms, one for the scalar flux and the other for the current, can be solved in the low-order problem and applied to the transport solution. A variety of one-dimensional (1-D) and two-dimensional (2-D) numerical tests are constructed to demonstrate the performance of FDSA in comparison with the standalone MC method and the coupled MC and Coarse Mesh Finite Difference (MC-CMFD) method on both intended purposes. The comparison results show that the acceleration by a factor of 3–10 can be expected for source convergence and the reduction in MC variance is comparable to CMFD in both slab and full core geometries, although the effectiveness of such hybrid methods is limited to systems with small dominance ratios.}, number={4}, journal={NUCLEAR ENGINEERING AND TECHNOLOGY}, author={Chen, Jiahao and Hou, Jason and Ivanov, Kostadin}, year={2023}, month={Apr}, pages={1428–1438} }
 @article{ni_hou_2023, title={An Efficient High-to-Low Iterative Method for Light Water Reactor Analysis Based on NEAMS Tools}, volume={197}, ISSN={0029-5639 1943-748X}, url={http://dx.doi.org/10.1080/00295639.2022.2158706}, DOI={10.1080/00295639.2022.2158706}, abstractNote={Abstract The so-called two-step method involving the consecutive lattice physics and core simulation has been successfully and widely used in large-scale nuclear reactor calculations thanks to its superior computational efficiency and a satisfactory level of accuracy. However, its performance is challenged by the ever-increasing level of heterogeneity in core designs due to the use of infinite lattice approximation in the lattice calculation and its inability to update cross-section sets according to the core environment change. This paper introduces an alternative approach for light water reactor steady-state core analysis. During the core calculation process, iterations between the local lattice transport calculation and the global core nodal calculation are conducted. These iterations continuously update the boundary condition applied to the lattice model and generate updated cross-section sets. This is done through the iteration between the local lattice transport calculation and the global core nodal simulation. The neutronics high-to-low (Hi2Lo) scheme was formulated using Nuclear Energy Advanced Modeling and Simulation or NEAMS codes, in particular, with the modified PROTEUS-MOC and PROTEUS-NODAL serving as the transport lattice solver and full-core nodal solver, respectively. The verification of the implemented Hi2Lo iterative scheme on the two-dimensional C5G7-TD benchmark problem shows that the Hi2Lo scheme outperforms the two-step approach in terms of prediction accuracy for the key responses of interest (e.g., the system eigenvalue and power distribution) at a computational cost lower than that of the direct full-core transport calculation. To further improve its efficiency, an acceleration method has been developed and implemented for the Hi2Lo approach, and the results indicate that the acceleration method can significantly reduce the run time of a full-core transport solution by a factor of 14 while generating solutions with comparable accuracy.}, number={8}, journal={Nuclear Science and Engineering}, publisher={Informa UK Limited}, author={Ni, Kan and Hou, Jason}, year={2023}, month={Feb}, pages={1700–1716} }
 @article{andersen_hou_godfrey_kropaczek_2022, title={A Novel Method for Controlling Crud Deposition in Nuclear Reactors Using Optimization Algorithms and Deep Neural Network Based Surrogate Models}, url={https://doi.org/10.3390/eng3040036}, DOI={10.3390/eng3040036}, abstractNote={This work presents the use of a high-fidelity neural network surrogate model within a Modular Optimization Framework for treatment of crud deposition as a constraint within light-water reactor core loading pattern optimization. The neural network was utilized for the treatment of crud constraints within the context of an advanced genetic algorithm applied to the core design problem. This proof-of-concept study shows that loading pattern optimization aided by a neural network surrogate model can optimize the manner in which crud distributes within a nuclear reactor without impacting operational parameters such as enrichment or cycle length. Several analysis methods were investigated. Analysis found that the surrogate model and genetic algorithm successfully minimized the deviation from a uniform crud distribution against a population of solutions from a reference optimization in which the crud distribution was not optimized. Strong evidence is presented that shows boron deposition in crud can be optimized through the loading pattern. This proof-of-concept study shows that the methods employed provide a powerful tool for mitigating the effects of crud deposition in nuclear reactors.}, journal={Eng}, author={Andersen, Brian and Hou, Jason and Godfrey, Andrew and Kropaczek, Dave}, year={2022}, month={Nov} }
 @article{delipei_rouxelin_abarca_hou_avramova_ivanov_2022, title={CTF-PARCS Core Multi-Physics Computational Framework for Efficient LWR Steady-State, Depletion and Transient Uncertainty Quantification}, volume={15}, ISSN={["1996-1073"]}, url={https://doi.org/10.3390/en15145226}, DOI={10.3390/en15145226}, abstractNote={Best Estimate Plus Uncertainty (BEPU) approaches for nuclear reactor applications have been extensively developed in recent years. The challenge for BEPU approaches is to achieve multi-physics modeling with an acceptable computational cost while preserving a reasonable fidelity of the physics modeled. In this work, we present the core multi-physics computational framework developed for the efficient computation of uncertainties in Light Water Reactor (LWR) simulations. The subchannel thermal-hydraulic code CTF and the nodal expansion neutronic code PARCS are coupled for the multi-physics modeling (CTF-PARCS). The computational framework is discussed in detail from the Polaris lattice calculations up to the CTF-PARCS coupling approaches. Sampler is used to perturb the multi-group microscopic cross-sections, fission yields and manufacturing parameters, while Dakota is used to sample the CTF input parameters and the boundary conditions. Python scripts were developed to automatize and modularize both pre- and post-processing. The current state of the framework allows the consistent perturbation of inputs across neutronics and thermal-hydraulics modeling. Improvements to the standard thermal-hydraulics modeling for such coupling approaches have been implemented in CTF to allow the usage of 3D burnup distribution, calculation of the radial power and the burnup profile, and the usage of Santamarina effective Doppler temperature. The uncertainty quantification approach allows the treatment of both scalar and functional quantities and can estimate correlation between the multi-physics outputs of interest and up to the originally perturbed microscopic cross-sections and yields. The computational framework is applied to three exercises of the LWR Uncertainty Analysis in Modeling Phase III benchmark. The exercises cover steady-state, depletion and transient calculations. The results show that the maximum fuel centerline temperature across all exercises is 2474K with 1.7% uncertainty and that the most correlated inputs are the 238U inelastic and elastic cross-sections above 1 MeV.}, number={14}, journal={ENERGIES}, author={Delipei, Gregory K. and Rouxelin, Pascal and Abarca, Agustin and Hou, Jason and Avramova, Maria and Ivanov, Kostadin}, year={2022}, month={Jul} }
 @article{rivas_martin_bays_palmiotti_xu_hou_2022, title={Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design}, volume={392}, ISSN={["1872-759X"]}, url={http://dx.doi.org/10.1016/j.nucengdes.2022.111744}, DOI={10.1016/j.nucengdes.2022.111744}, abstractNote={The Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance–covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U-238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance–covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.}, journal={NUCLEAR ENGINEERING AND DESIGN}, publisher={Elsevier BV}, author={Rivas, Andy and Martin, Nicolas P. and Bays, Samuel E. and Palmiotti, Giuseppe and Xu, Zhiwen and Hou, Jason}, year={2022}, month={Jun} }
 @article{rivas_delipei_hou_2022, title={Predictions of component Remaining Useful Lifetime Using Bayesian Neural Network}, volume={146}, ISSN={["1878-4224"]}, url={http://dx.doi.org/10.1016/j.pnucene.2022.104143}, DOI={10.1016/j.pnucene.2022.104143}, abstractNote={The Machine Prognostics and Health Management (PHM) are concerned with the prediction of the Remaining Useful Lifetime (RUL) of assets. Accurate real-time RUL predictions are necessary when developing an efficient predictive maintenance (PdM) framework for equipment health assessment. If correctly implemented, a PdM framework can maximize the interval between maintenance operations, minimize the cost and number of unscheduled maintenance operations, and improve overall availability of the large facilities like nuclear power plants (NPPs). This is especially important for nuclear power facilities to maximize capacity factor and reliability. In this work, we propose a data-driven approach to make predictions of both the RUL and its uncertainty using a Bayesian Neural Network (BNN). The BNN utilizes the Bayes by backprop algorithm with variational inference to estimate the posterior distribution for each trainable parameter so that the model output is also a PDF from which one can draw the mean prediction and the associated uncertainty. To learn the correlations between various time-series sensor data measurements, a time window approach is implemented with a two-stage noise filtering process for incoming sensor measurements to enhance the feature extraction and overall model performance. As a proof of concept, the NASA Commercial Modular Aero Propulsion System Simulation (C-MAPPS) datasets are utilized to assess the performance of the BNN model. The modeled system can be treated as a surrogate for turbine generators used in NPPs due to the similar mode of operation, degradation, and measurable variables. Comparisons against other state-of-the-art algorithms on the same datasets indicate that the BNN model can not only make predictions with comparable level of accuracy, but also offer the benefit of estimating uncertainty associated with the prediction. This additional uncertainty, which can be continuously updated as more measurement data are collected, can facilitate the decision-making process with a quantifiable confidence level within a PdM framework. Additional advantages of the BNN are showcased, such as providing component maintenance ranges and model executing frequency, with an example of how the BNN estimated uncertainty can be used to support the continuous predictive maintenance. A PdM framework based on a BNN will allow for utilities to make more informed decisions on the optimal time for maintenance so that the loss of revenue can be minimized from planned and unplanned maintenance outages.}, journal={PROGRESS IN NUCLEAR ENERGY}, publisher={Elsevier BV}, author={Rivas, Andy and Delipei, Gregory Kyriakos and Hou, Jason}, year={2022}, month={Apr} }
 @article{avramova_abarca_hou_ivanov_2021, title={Innovations in Multi-Physics Methods Development, Validation, and Uncertainty Quantification}, url={https://doi.org/10.3390/jne2010005}, DOI={10.3390/jne2010005}, abstractNote={This paper provides a review of current and upcoming innovations in development, validation, and uncertainty quantification of nuclear reactor multi-physics simulation methods. Multi-physics modelling and simulations (M&S) provide more accurate and realistic predictions of the nuclear reactors behavior including local safety parameters. Multi-physics M&S tools can be subdivided in two groups: traditional multi-physics M&S on assembly/channel spatial scale (currently used in industry and regulation), and novel high-fidelity multi-physics M&S on pin (sub-pin)/sub-channel spatial scale. The current trends in reactor design and safety analysis are towards further development, verification, and validation of multi-physics multi-scale M&S combined with uncertainty quantification and propagation. Approaches currently applied for validation of the traditional multi-physics M&S are summarized and illustrated using established Nuclear Energy Agency/Organization for Economic Cooperation and Development (NEA/OECD) multi-physics benchmarks. Novel high-fidelity multi-physics M&S allow for insights crucial to resolve industry challenge and high impact problems previously impossible with the traditional tools. Challenges in validation of novel multi-physics M&S are discussed along with the needs for developing validation benchmarks based on experimental data. Due to their complexity, the novel multi-physics codes are still computationally expensive for routine applications. This fact motivates the use of high-fidelity novel models and codes to inform the low-fidelity traditional models and codes, leading to improved traditional multi-physics M&S. The uncertainty quantification and propagation across different scales (multi-scale) and multi-physics phenomena are demonstrated using the OECD/NEA Light Water Reactor Uncertainty Analysis in Modelling benchmark framework. Finally, the increasing role of data science and analytics techniques in development and validation of multi-physics M&S is summarized.}, journal={Journal of Nuclear Engineering}, author={Avramova, Maria and Abarca, Agustin and Hou, Jason and Ivanov, Kostadin}, year={2021}, month={Mar} }
 @article{xu_hou_ivanov_2021, title={Methodology for Discontinuity Factors Generation for Simplified P-3 Solver Based on Nodal Expansion Formulation}, volume={14}, ISSN={["1996-1073"]}, url={https://doi.org/10.3390/en14206478}, DOI={10.3390/en14206478}, abstractNote={The Simplified Spherical Harmonic (SPN) approximation was first introduced as a three-dimensional (3D) extension of the plane-geometry Spherical Harmonic (PN) equations. A third order SPN (SP3) solver, recently implemented in the Nodal Expansion Method (NEM), has shown promising performance in the reactor core neutronics simulations. This work is focused on the development and implementation of the transport-corrected interface and boundary conditions in an NEM SP3 solver, following recent published work on the rigorous SPN theory for piecewise homogeneous regions. A streamlined procedure has been developed to generate the flux zero and second order/moment discontinuity factors (DFs) of the generalized equivalence theory to minimize the error introduced by pin-wise homogenization. Moreover, several colorset models with varying sizes and configurations are later explored for their capability of generating DFs that can produce results equivalent to that using the whole-core homogenization model for more practical implementations. The new developments are tested and demonstrated on the C5G7 benchmark. The results show that the transport-corrected SP3 solver shows general improvements to power distribution prediction compared to the basic SP3 solver with no DFs or with only the zeroth moment DF. The complete equivalent calculations using the DFs can almost reproduce transport solutions with high accuracy. The use of equivalent parameters from larger size colorset models show a slightly reduced prediction error than that using smaller colorset models in the whole-core calculations.}, number={20}, journal={ENERGIES}, publisher={MDPI AG}, author={Xu, Yuchao and Hou, Jason and Ivanov, Kostadin}, year={2021}, month={Oct} }
 @article{rivas_stauff_sumner_hou_2021, title={Propagating neutronic uncertainties for FFTF LOFWOS Test #13}, volume={375}, ISSN={["1872-759X"]}, DOI={10.1016/j.nucengdes.2020.111047}, abstractNote={The safety evaluation conducted for licensing a Sodium-cooled Fast Reactor (SFR) may require modeling transients with best-estimate calculation tools that must first be validated against real-world measurements. To provide the community with a valuable benchmarking opportunity for validating SFR analysis tools and methods, the International Atomic Energy Agency (IAEA) initiated a coordinated research project (CRP) in 2018 for the analysis of the Fast Flux Test Facility (FFTF) Loss of Flow Without Scram (LOFWOS) Test #13. The impact of nuclear data uncertainties on neutronics parameters was previously investigated based on the COMMARA-2.0 covariance matrix. Since the transient simulation results are very sensitive to certain reactivity coefficients, it was decided to employ rigorous uncertainty propagation methods to quantify the impact of nuclear data uncertainties on the best-estimate predication of FFTF LOFWOS Test #13. The DAKOTA code is used to propagate neutronic uncertainties through SAS4A/SASSYS-1 transient simulations, while taking into account spatial and reaction-wise correlations within these uncertainties. This study shows that the remaining discrepancies observed between the Argonne National Laboratory (ANL) best-estimate results and the experimental measurements can be partly explained by the uncertainty associated with Gas Expansion Module (GEM) worth, which contributes the majority of the overall nuclear data uncertainty on the output from the FFTF LOFWOS Test #13 transient simulation. This study also confirmed the importance of including spatial and reaction-wise correlations of nuclear data uncertainties on feedback coefficients in the uncertainty propagation to avoid under-estimating their impact during the transient simulations.}, journal={NUCLEAR ENGINEERING AND DESIGN}, publisher={Elsevier BV}, author={Rivas, Andy and Stauff, Nicolas and Sumner, Tyler and Hou, Jason}, year={2021}, month={Apr} }
 @article{delipei_hou_avramova_rouxelin_ivanov_2021, title={Summary of comparative analysis and conclusions from OECD/NEA LWR-UAM benchmark Phase I}, volume={384}, ISSN={["1872-759X"]}, url={http://dx.doi.org/10.1016/j.nucengdes.2021.111474}, DOI={10.1016/j.nucengdes.2021.111474}, abstractNote={In recent years, large efforts have been devoted to Light Water Reactor (LWR) Uncertainty Quantification (UQ). In 2006, the LWR Uncertainty Analysis in Modeling (UAM) benchmark was launched with an aim to investigate the uncertainty propagation in all modeling stages of the LWRs and guide uncertainty and sensitivity analysis methodology development. This article summarizes the benchmark activities for the standalone neutronics phase (Phase I), which includes three main exercises: Exercise I-1: “Cell Physics,” Exercise I-2: “Lattice Physics,” and Exercise I-3: “Core Physics.” A comparative analysis of the Phase I results is performed in this article for all the considered LWRs types: Three Mile Island – 1 Pressurized Water Reactor (PWR), Peach Bottom – 2 Boiling Water Reactor (BWR), Kozloduy – 6 Water - Water Energetic Reactor (VVER) and a Generation-III reactor. It was found, for all major exercises, that the predicted uncertainty of the system eigenvalue is highly dependent on the choice of the covariance libraries used in the UQ process and is less sensitive to the solution method, nuclear data library and UQ method. For all four reactor types, the observed relative standard deviation across all exercises is approximately 0.5% for the UO2 fuel. In the pin cell and lattice calculations with MOX fuel this uncertainty increases to 1%. The main reason is the larger Pu-239 nu-bar uncertainty compared to the U-235 nu-bar. The largest contributors to the eigenvalue uncertainties are the U-235 nu-bar and the U-238 capture in the UO2 fuel and the Pu-239 nu-bar in the MOX fuel. In the assembly lattice exercises, higher uncertainties are predicted for the fast group than the thermal group constants with differences up to one order of magnitude. This is attributed to the larger uncertainties of most cross-sections at high energies. The obtained correlation matrices share some common major trends but also exhibit strong differences in case by case comparisons indicating an impact of the selected neutronics modeling and nuclear data library. In the core exercises, the predicted relative standard deviation of the radial and axial power, for most of the cores, is below 10%. An exception is the radial power profile of the Generation-III core, when a mixture of UOX/MOX assemblies is considered. Finally, it is important to note that the bias in most of the studies is significant and up to the same order of the estimated uncertainty. This indicates a need for better quantification of the bias/variance through more code to code and code to experiments comparisons.}, journal={NUCLEAR ENGINEERING AND DESIGN}, publisher={Elsevier BV}, author={Delipei, Gregory Kyriakos and Hou, Jason and Avramova, Maria and Rouxelin, Pascal and Ivanov, Kostadin}, year={2021}, month={Dec} }
 @article{hou_avramova_ivanov_2020, title={Best-Estimate Plus Uncertainty Framework for Multiscale, Multiphysics Light Water Reactor Core Analysis}, url={https://doi.org/10.1155/2020/7526864}, DOI={10.1155/2020/7526864}, abstractNote={Tremendous work has been done in the Light Water Reactor (LWR) Modelling and Simulation (M&S) uncertainty quantification (UQ) within the framework of the Organization for Economic Cooperation and Development (OECD)/Nuclear Energy Agency (NEA) LWR Uncertainty Analysis in Modelling (UAM) benchmark, which aims to investigate the uncertainty propagation in all M&S stages of the LWRs and to guide uncertainty and sensitivity analysis methodology development. The Best-Estimate Plus Uncertainty (BEPU) methodologies have been developed and implemented within the framework of the LWR UAM benchmark to provide a realistic predictive simulation capability without compromising the safety margins. This paper describes the current status of the methodological development, assessment, and integration of the BEPU methodology to facilitate the multiscale, multiphysics LWR core analysis. The comparative analysis of the results in the stand-alone multiscale neutronics phase (Phase I) is first reported for understanding the general trend of the uncertainty of core parameters due to the nuclear data uncertainty. It was found that the predicted uncertainty of the system eigenvalue is highly dependent on the choice of the covariance libraries used in the UQ process and is less sensitive to the solution method, nuclear data library, and UQ method. High-to-Low (Hi2Lo) model information approaches for multiscale M&S are introduced for the core single physics phase (Phase II). In this phase, the other physics (fuel and moderator), providing feedback to neutronics M&S in a LWR core, and time-dependent phenomena are considered. Phase II is focused on uncertainty propagation in single physics models which are components of the LWR core coupled multiphysics calculations. The paper discusses the link and interactions between Phase II to the multiphysics core and system phase (Phase III), that is, the link between uncertainty propagation in single physics on local scale and multiphysics uncertainty propagation on the core scale. Particularly, the consistency in uncertainty assessment between higher-fidelity models implemented in fuel performance codes and the rather simplified models implemented in thermal-hydraulics codes, to be used for coupling with neutronics in Phase III is presented. Similarly, the uncertainty quantification on thermal-hydraulic models is established on a relatively small scale, while these results will be used in Phase III at the core scale, sometimes with different codes or models. Lastly, the up-to-date UQ method for the coupled multiphysics core calculation in Phase III is presented, focusing on the core equilibrium cycle depletion calculation with associated uncertainties.}, journal={Science and Technology of Nuclear Installations}, author={Hou, Jason and Avramova, Maria and Ivanov, Kostadin}, year={2020}, month={Jul} }
 @article{zeng_stauff_hou_kim_2020, title={Development of multi-objective core optimization framework and application to sodium-cooled fast test reactors}, url={https://doi.org/10.1016/j.pnucene.2019.103184}, DOI={10.1016/j.pnucene.2019.103184}, abstractNote={The optimization of a Sodium-cooled Fast Reactor (SFR) core is a challenging process, due to the large number of design parameters, the nonlinearities among inputs and outputs, and the complicated correlation among output parameters. This study attempts to develop a generalized framework for the SFR core optimization by coupling the sensitivity analysis, advanced optimization algorithm, and optionally the surrogate modeling. The framework is built based on the fast reactor modeling capability of the Argonne Reactor Computation (ARC) suite and the sensitivity analysis and optimization modules embedded in the DAKOTA code, both have been integrated within the NEAMS Workbench. The genetic algorithm is selected as the optimization method for its robustness, while the option of surrogate modeling is also explored to alleviate the computational burden caused by employing the ARC direct core physics simulation and thus enhance the efficiency of the optimization. Finally, the normalized deviations of performance parameters of the near-optimal solution from those of the ideal core are calculated and used as criteria to down select the final core design. The developed framework is applied to the Advanced Burner Test Reactor (ABTR) core, and optimal solutions are determined by balancing various objectives simultaneously, including peak fast flux, core volume, power, reactivity swing, plutonium mass feed, while at the same time satisfying the predefined constraints due to safety or economics considerations. The optimal ABTR core design obtained using the direct physical simulation and surrogated model are compared and discussed. It is found that using the accurately constructed surrogate models can significantly reduce the required computational time while maintaining satisfactory accuracy.}, journal={Progress in Nuclear Energy}, author={Zeng, Kaiyue and Stauff, Nicolas E. and Hou, Jason and Kim, Taek K.}, year={2020}, month={Feb} }
 @article{trivedi_hou_grasso_ivanov_franceschini_2020, title={Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors}, url={https://doi.org/10.1155/2020/3961095}, DOI={10.1155/2020/3961095}, abstractNote={In this study, the Best Estimate Plus Uncertainty (BEPU) approach is developed for the systematic quantification and propagation of uncertainties in the modelling and simulation of lead-cooled fast reactors (LFRs) and applied to the demonstration LFR (DLFR) initially investigated by Westinghouse. The impact of nuclear data uncertainties based on ENDF/B-VII.0 covariances is quantified on lattice level using the generalized perturbation theory implemented with the Monte Carlo code Serpent and the deterministic code PERSENT of the Argonne Reactor Computational (ARC) suite. The quantities of interest are the main eigenvalue and selected reactivity coefficients such as Doppler, radial expansion, and fuel/clad/coolant density coefficients. These uncertainties are then propagated through safety analysis, carried out using the MiniSAS code, following the stochastic sampling approach in DAKOTA. An unprotected transient overpower (UTOP) scenario is considered to assess the effect of input uncertainties on safety parameters such as peak fuel and clad temperatures. It is found that in steady state, the multiplication factor shows the most sensitivity to perturbations in 235U fission, 235U ν, and 238U capture cross sections. The uncertainties of 239Pu and 238U capture cross sections become more significant as the fuel is irradiated. The covariance of various reactivity feedback coefficients is constructed by tracing back to common uncertainty contributors (i.e., nuclide-reaction pairs), including 238U inelastic, 238U capture, and 239Pu capture cross sections. It is also observed that nuclear data uncertainty propagates to uncertainty on peak clad and fuel temperatures of 28.5 K and 70.0 K, respectively. Such uncertainties do not impose per se threat to the integrity of the fuel rod; however, they sum to other sources of uncertainties in verifying the compliance of the assumed safety margins, suggesting the developed BEPU method necessary to provide one of the required insights on the impact of uncertainties on core safety characteristics.}, journal={Science and Technology of Nuclear Installations}, author={Trivedi, Ishita and Hou, Jason and Grasso, Giacomo and Ivanov, Kostadin and Franceschini, Fausto}, year={2020}, month={Aug} }
 @article{wan_sui_wang_cao_liu_hou_2020, title={Nuclear-data uncertainty propagation in transient simulation for the C5G7-TD benchmark problem}, volume={140}, url={https://doi.org/10.1016/j.anucene.2019.107122}, DOI={10.1016/j.anucene.2019.107122}, abstractNote={In this study, uncertainty analysis has been performed to the time-dependent transient simulation of the C5G7-TD benchmark problem, propagating the nuclear-data uncertainties to the key parameters of interest. The detailed material compositions and geometries of C5G7-TD have been applied for the time-dependent transient simulation. For uncertainty analysis of the transient simulation, multigroup cross-section covariance library has been generated based on ENDF/B-VII.1 using the NJOY code. Our home-developed uncertainty-analysis code named UNICORN has been utilized for the uncertainty analysis, using the statistical sampling method. For the steady-state and transient simulations, our home-developed high-fidelity neutronics code NECP-X has been utilized. The relative uncertainties of the fuel-assembly normalized power and pin-wise power have been quantified as function of time. The numerical results show that the maximum relative uncertainties for the assembly normalized power can up to be about 2.14% and the value for the pin-wise power distributions can be about 3.54%.}, journal={Annals of Nuclear Energy}, publisher={Elsevier BV}, author={Wan, Chenghui and Sui, Zhuojie and Wang, Bo and Cao, Liangzhi and Liu, Zhouyu and Hou, Jason}, year={2020}, month={Jun}, pages={107122} }
 @article{ramzy altahhan_bhaskar_ziyad_balestra_fiorina_hou_smith_avramova_2020, title={Preliminary design and analysis of Liquid Fuel Molten Salt Reactor using multi-physics code GeN-Foam}, volume={369}, url={http://dx.doi.org/10.1016/j.nucengdes.2020.110826}, DOI={10.1016/j.nucengdes.2020.110826}, abstractNote={In this study, a hypothetical fast spectrum Liquid Fuel Molten Salt Reactor (LFMSR) core is modeled using the multiphysics C++ code GeN-Foam (General Nuclear Foam). GeN-Foam is based on OpenFOAM, a C++ open-source library for solution of continuum mechanics problems. The code utilizes a unified fine/coarse mesh approach, modeling different physics such as neutron kinetics, thermal-hydraulics based on porous fluid equations, and structural thermal-mechanics. A steady state analysis of a simplified two-dimensional (2D) LFMSR model has been performed assuming rotational symmetry to cross verify the code with the commercial ANSYS Computational Fluid Dynamics (CFD) code Fluent. The calculations showed very good agreement between the two codes allowing progression to a three-dimensional (3D) model simulation. A coupled neutron kinetics and CFD steady state analysis of a right-cylindrical 3D LFMSR core has been performed modeling one quarter of the core while using symmetry boundaries to reduce the computational time. Mixed uranium and plutonium chloride fuel has been selected in this preliminary study. Both 2D and 3D simulations showed appearance of recirculation zones within the right-cylinder core. These zones can be a challenge for LFMSR control and materials. A new hyperboloid design is proposed to remove recirculation zones, which is based on eight symmetrical loops. An Unprotected Loss of Flow accident (ULOF), in which the pump head is instantaneously reduced to zero, has been selected to demonstrate the safety characteristics of the reactor in one of the most challenging possible situations for LFMSR. The obtained results (e.g., reduced total precursors concentration at the core inlet and reduction of the core nominal power following the transient) confirm that GeN-Foam is capable of performing coupled LFMSR transient analysis and can be used for design analysis and optimization. Although the current design needs further assessment and development, it shows encouraging performance under ULOF conditions paving the way to the next step in the optimization process.}, journal={Nuclear Engineering and Design}, author={Ramzy Altahhan, Muhammad and Bhaskar, Sandesh and Ziyad, Devshibhai and Balestra, Paolo and Fiorina, Carlo and Hou, Jason and Smith, Nicholas and Avramova, Maria}, year={2020}, month={Dec}, pages={110826} }
 @article{sihlangu_naicker_hou_reitsma_2019, title={Further development of methodology to model TRISO fuel and BISO absorber particles and related uncertainty quantification using SCALE 6}, volume={56}, url={https://doi.org/10.1080/00223131.2019.1617204}, DOI={10.1080/00223131.2019.1617204}, abstractNote={ABSTRACT In the 350 MW Modular High Temperature Gas-Cooled Reactor (MHTGR-350), not only is the fuel double heterogeneous but so are the lumped burnable poisons (LBPs). The LBPs are composed of Bi-Structural Isotropic (BISO) particles and the fuel is composed of Tri-Structural Isotropic (TRISO) particles. This work investigates different methods to model coated particles using KENO-VI and NEWT of SCALE 6. The most efficient way of modelling TRISO particles in terms of packing and randomization is established in continuous energy (CE) mode and its impact on is investigated. In the multi-group (MG) treatment, coated particles are modelled with the DOUBLEHET function which is only designed for particles that contain fuel. The LBP BISO particles could therefore not be modelled. Hence a method called the LBP Trace method is developed to model the LBP BISO particles using the DOUBLEHET function. It was found that changed by 1500 pcm compared to the conventional (homogenized) case, when using the LBP Trace method. However, no significant change was observed in the macroscopic absorption cross section that would be passed to a nodal core calculation. Furt hermore, the LBP Trace method showed small changes in the nuclear data uncertainty when compared to conventional case.}, number={8}, journal={Journal of Nuclear Science and Technology}, publisher={Informa UK Limited}, author={Sihlangu, S.F. and Naicker, V.V. and Hou, J. and Reitsma, F.}, year={2019}, month={Aug}, pages={690–709} }
 @article{zeng_hou_ivanov_jessee_2019, title={Uncertainty Quantification and Propagation of Multiphysics Simulation of the Pressurized Water Reactor Core}, volume={205}, ISSN={0029-5450 1943-7471}, url={http://dx.doi.org/10.1080/00295450.2019.1580533}, DOI={10.1080/00295450.2019.1580533}, abstractNote={Abstract In recent years, the demand to provide best-estimate predictions with confident bounds is increasing for the nuclear reactor performance and safety analysis. The Organisation for Economic Co-operation and Development Nuclear Energy Agency has been developing an international benchmark of the light water reactor (LWR) uncertainty analysis in modeling (UAM) for the examination of uncertainty quantification and propagation methodologies with various modeling and simulation code systems. The objective of the present work is to develop an uncertainty propagation mechanism based on the stochastic sampling method by taking into account the uncertainties of both basic nuclear data and fuel modeling parameters in the simulation of pressurized water reactors (PWRs) that can be incorporated in the conventional LWR simulation approach. More specifically, the Three Mile Island Unit 1–related exercises from the LWR-UAM benchmark have been modeled using the coupled TRACE/PARCS code system in the three-dimensional core representation. The input uncertainties of the neutronics simulation include few-group cross sections and kinetics parameters generated using the Sampler/Polaris sequence of SCALE 6.2.1. Several heat transfer–related variables for the fuel modeling were considered as sources of input uncertainty of the thermal-hydraulics simulations, including the thermal conductivity of fuel and cladding, fuel heat capacity, and the gap conductance. Dakota was used to sample input parameters of the coupled code system and to perform the uncertainty analysis. Two types of simulations were conducted: steady-state calculation at hot full-power condition and transient scenario initiated by the spatially asymmetric rod ejection accident. Quantities of interest for the steady-state calculation, including core multiplication factor and power peaking factors, were calculated with associated uncertainties. For transient calculations, best-estimate plus uncertainty results of the time evolution of core reactivity, core power, and peak fuel temperature were generated and analyzed. The Wilks’ formula was used to determine the necessary sample size to achieve a 95% confidence of the 95% limit of output quantities of interest. Although the uncertainty propagation and quantification method presented in this paper was developed for PWRs, it could be in general applicable to the multiphysics uncertainty quantification of other types of LWR cores.}, number={12}, journal={Nuclear Technology}, publisher={Informa UK Limited}, author={Zeng, Kaiyue and Hou, Jason and Ivanov, Kostadin and Jessee, Matthew Anderson}, year={2019}, month={Mar}, pages={1618–1637} }
 @article{li_jiao_avramova_chen_yu_chen_hou_2018, title={Development, verification and application of a new model for active nucleation site density in boiling systems}, volume={328}, url={http://www.sciencedirect.com/science/article/pii/S0029549317306180}, DOI={https://doi.org/10.1016/j.nucengdes.2017.12.027}, abstractNote={A new model for active nucleation site density in boiling systems has been developed and preliminarily applied in Computational Fluid Dynamics (CFD) simulations of subcooled boiling in a vertical heated tube. The new model is based on a parametric analysis of existing experimental data. It is a function of three variables: wall superheat, pressure, and contact angle; and is applicable in a wide range of pressures: 0.101 MPa–19.8 MPa. A preliminary study of the temperature dependence of the contact angle has been performed during the development process. The new model is intended to improve the predictions of: (i) interfacial area concentration in two-fluid models, and (ii) wall temperature in subcooled boiling simulations. For the active nucleation site density itself, the verification results showed that the values predicted by the newly developed model are in good agreement with various published experimental data. The model also demonstrated improvements of other existing models. The new model was utilized in CFD simulations of subcooled boiling in a vertical heated tube. The predicted void fraction and wall temperature in subcooled boiling flow agree well with the experimental data.}, journal={Nuclear Engineering and Design}, author={Li, Quan and Jiao, Yongjun and Avramova, Maria and Chen, Ping and Yu, Junchong and Chen, Jie and Hou, Jason}, year={2018}, pages={1–9} }
 @article{wang_guo_li_hou_ivanov_2017, title={Effect of Nuclear Data on Fuel Element Neutronic Characteristics of Pebble-bed High Temperature Gas-cooled Reactor}, volume={51}, number={9}, journal={Atomic Energy Science and Technology}, author={Wang, L. and Guo, J. and Li, F. and Hou, J. and Ivanov, K.}, year={2017}, month={Sep}, pages={1591–1598} }
 @article{hou_ivanov_boyarinov_fomichenko_2017, title={OECD/NEA benchmark for time-dependent neutron transport calculations without spatial homogenization}, volume={317}, ISSN={["1872-759X"]}, url={https://doi.org/10.1016/j.nucengdes.2017.02.008}, DOI={10.1016/j.nucengdes.2017.02.008}, abstractNote={A Nuclear Energy Agency (NEA), Organization for Economic Co-operation and Development (OECD) benchmark for the time-dependent neutron transport calculations without spatial homogenization has been established in order to facilitate the development and assessment of numerical methods for solving the space-time neutron kinetics equations. The benchmark has been named the OECD/NEA C5G7-TD benchmark, and later extended with three consecutive phases each corresponding to one modelling stage of the multi-physics transient analysis of the nuclear reactor core. This paper provides a detailed introduction of the benchmark specification of Phase I, known as the “kinetics phase”, including the geometry description, supporting neutron transport data, transient scenarios in both two-dimensional (2-D) and three-dimensional (3-D) configurations, as well as the expected output parameters from the participants. Also presented are the preliminary results for the initial state 2-D core and selected transient exercises that have been obtained using the Monte Carlo method and the Surface Harmonic Method (SHM), respectively.}, journal={NUCLEAR ENGINEERING AND DESIGN}, publisher={Elsevier BV}, author={Hou, Jason and Ivanov, Kostadin N. and Boyarinov, Victor F. and Fomichenko, Peter A.}, year={2017}, month={Jun}, pages={177–189} }
 @article{hou_qvist_kellogg_greenspan_2016, title={3D in-core fuel management optimization for breed-and-burn reactors}, volume={88}, ISSN={["0149-1970"]}, url={https://doi.org/10.1016/j.pnucene.2015.12.002}, DOI={10.1016/j.pnucene.2015.12.002}, abstractNote={Breed-and-burn (B&B) reactors are a special class of fast reactors that are designed to utilize low grade fuel such as depleted uranium without fuel reprocessing. One of the most challenging practical design feasibility issues faced by B&B reactors is the high level of radiation damage their fuel cladding has to withstand in order to sustain the B&B mode of operation – more than twice the maximum radiation damage cladding materials were exposed to so far in fast reactors. This study explores the possibility of reducing the minimum required peak radiation damage by employment of 3-dimensional (3D) fuel shuffling that enables a significant reduction in the peak-to-average axial burnup, that is, more uniform fuel utilization. A new conceptual design of a B&B core made of axially segmented fuel assemblies was adopted to facilitate the 3D shuffling. Also developed is a Simulated Annealing (SA) algorithm to automate the search for the optimal 3D shuffling pattern (SP). The primary objective of the SA optimization is to minimize the peak radiation damage while its secondary objective is to minimize the burnup reactivity swing, radial power peaking factor and maximum change of fuel assembly power over the cycle. Also studied is the sensitivity of the 3D shuffled core performance to the number of axially stacked sub-assemblies, core height and power level. It was found that compared with the optimal 2-dimensional (2D) shuffled core, the optimal 3D shuffled B&B core made of four 70 cm long axially stacked sub-assemblies and 12 radial shuffling batches offers a 1/3 reduction of the peak radiation damage level – from 534 down to 351 displacements per atom (dpa), along with a 45% increase in the average fuel discharge burnup, and hence, the depleted uranium utilization, while satisfying all major neutronics and thermal-hydraulics design constraints. For the same peak dpa level, the 3D shuffling offers more than double the uranium utilization and the cycle length relative to 2D shuffling. The minimum peak radiation damage is increased to 360 or to 403 dpa if the core is made of, respectively, three – 70 cm or two – 140 cm long axially stacked subassemblies. Reducing the length of the subassemblies of B&B cores made of three-segment assemblies from 70 cm to 60 or 50 cm results in an increase in the peak radiation damage from 360 dpa to, respectively, 368 and 397 dpa.}, journal={PROGRESS IN NUCLEAR ENERGY}, publisher={Elsevier BV}, author={Hou, Jason and Qvist, Staffan and Kellogg, Roger and Greenspan, Ehud}, year={2016}, month={Apr}, pages={58–74} }
 @article{qvist_hou_greenspan_2015, title={Design and performance of 2D and 3D-shuffled breed-and-burn cores}, volume={85}, ISSN={["0306-4549"]}, DOI={10.1016/j.anucene.2015.04.007}, abstractNote={The primary objective of this work is to find design approaches that will enable 3D fuel shuffling in stationary breed-and-burn (B&B) cores and to quantify the attainable reduction in peak DPA and change in additional performance characteristics going from conventional 2D to 3D fuel shuffling strategies. An additional objective is to establish the tradeoff between the minimum required DPA (displacements per atom) and average required burnup (fuel utilization) for B&B cores spanning a core power range from 1250 to 3500 MWth. It is found possible to design a B&B core fuelled with depleted uranium to have a peak radiation damage at or below 350 DPA when using 3D-shuffling. Relative to conventional 2D-shuffling, 3D-shuffling offers between 30% and 40% reduction in the peak DPA along with up to 30% increase in the average discharge burnup and, hence, in the depleted uranium utilization as well as significant increase in the core average and specific power density. Per DPA, the 3D shuffling option offers up to 60% higher uranium utilization. Even though 350 DPA is above the 200 DPA peak radiation damage HT9 steels were exposed to so far, it is below the 400 DPA advanced structural materials are expected to tolerate.}, journal={ANNALS OF NUCLEAR ENERGY}, publisher={Elsevier BV}, author={Qvist, Staffan and Hou, Jason and Greenspan, Ehud}, year={2015}, month={Nov}, pages={93–114} }
 @article{hou_choi_ivanov_2015, title={Development of an iterative diffusion-transport method based on MICROX-2 cross section libraries}, volume={77}, ISSN={["0306-4549"]}, DOI={10.1016/j.anucene.2014.11.014}, abstractNote={This paper introduces an innovative online cross section generation method, developed based on Iterative Diffusion-Transport (IDT) calculation to minimize the inconsistency and inaccuracy in determining physics parameters by feeding actual reactor core conditions into the cross section generation process. A two-dimensional (2-D) pin-by-pin lattice program, NEMA, was developed to generate assembly lattice parameters using the refined MICROX-2 cross section libraries and Nodal Expansion Method (NEM). The proposed method was verified against a 2-D miniature core (mini-core) benchmark problem. First, the few-group cross sections generated by NEMA were compared with those calculated by a Monte Carlo method code Serpent. Next, the analysis of a 2-D Light Water Reactor (LWR) mini-core benchmark problem was carried out by the nodal transport code DIF3D using few-group cross sections generated by NEMA, and the results were compared with those obtained from the Serpent full core calculation. Finally, the same benchmark problem was solved by the NEMA-DIF3D approach using the IDT coupling method. The computational benchmark calculations have shown that the homogenization technique implemented in NEMA is reliable when producing the few-group cross sections for the reactor core calculation. The IDT method also improves the eigenvalue and power distribution predictions.}, journal={ANNALS OF NUCLEAR ENERGY}, publisher={Elsevier BV}, author={Hou, J. and Choi, H. and Ivanov, K. N.}, year={2015}, month={Mar}, pages={335–342} }
 @article{hou_choi_ivanov_2014, title={ASSESSMENT OF MICROX-2 CODE WITH NEW ENDF/B-VII RELEASE 0 MASTER LIBRARIES}, volume={186}, ISSN={["1943-7471"]}, DOI={10.13182/nt12-137}, abstractNote={Abstract A lattice code, MICROX-2, was assessed for its neutronics calculation performance with new cross-section libraries. First, the new cross-section libraries were generated based on ENDF/B-VII release 0. A total of 386 nuclides were processed, including 10 thermal scattering nuclides. The updated NJOY system and MICROR code were used to process nuclear data and convert them into the MICROX-2 library format. The energy group structure of the new library was optimized for both the thermal and fast neutron spectrum systems based on the Contributon and Pointwise Cross Section Driven (CPXSD) method, resulting in a total of 1173 energy groups. Second, a series of pin-cell–level benchmark calculations was performed against experimental measurements and numerical calculations performed by the deterministic and Monte Carlo codes for multiplication factors and reaction rate ratios. Both the homogeneous and heterogeneous pin-cell calculations were conducted for 15 cases. The results of MICROX-2 calculations show good agreement with the reference values. The arithmetic average errors of k∞ for the homogeneous and heterogeneous lattices are 0.30% and 0.44%, respectively. For the finite lattices (five cases for water reactor fuels), the average error of keff is 0.32%. These errors are due to the combined effect of the solution method and the cross-section library. Especially for the fast reactor cases, the prediction of the physics parameter by MICROX-2 deteriorates when the fuel volume increases, which is mostly due to the simplified resonance self-shielding model.}, number={3}, journal={NUCLEAR TECHNOLOGY}, publisher={American Nuclear Society}, author={Hou, Jia and Choi, Hangbok and Ivanov, Kostadin}, year={2014}, month={Jun}, pages={305–316} }
 @article{hou_choi_ivanov_2014, title={Self-shielding models of MICROX-2 code: Review and updates}, volume={64}, ISSN={["0306-4549"]}, DOI={10.1016/j.anucene.2013.10.005}, abstractNote={The MICROX-2 is a transport theory code that solves for the neutron slowing-down and thermalization equations of a two-region lattice cell. The MICROX-2 code has been updated to expand its application to advanced reactor concepts and fuel cycle simulations, including generation of new fine-group cross section libraries based on ENDF/B-VII. In continuation of previous work, the MICROX-2 methods are reviewed and updated in this study, focusing on its resonance self-shielding and spatial self-shielding models for neutron spectrum calculations. The improvement of self-shielding method was assessed by a series of benchmark calculations against the Monte Carlo code, using homogeneous and heterogeneous pin cell models. The results have shown that the implementation of the updated self-shielding models is correct and the accuracy of physics calculation is improved. Compared to the existing models, the updates reduced the prediction error of the infinite multiplication factor by ∼0.1% and ∼0.2% for the homogeneous and heterogeneous pin cell models, respectively, considered in this study.}, journal={ANNALS OF NUCLEAR ENERGY}, publisher={Elsevier BV}, author={Hou, J. and Choi, H. and Ivanov, K. N.}, year={2014}, month={Feb}, pages={256–263} }
 @inproceedings{osborne_hou_graves_miller_2007, title={Development of a Modern Pressurized Water Reactor Simulator: Instrumentation, Design and Data Acquisition}, DOI={10.1109/nssmic.2007.4436393}, abstractNote={A method is proposed for redesigning an existing pressurized water reactor simulator with modern control and data acquisition electronics along with a custom designed GUI. This system will be used in providing instruction to undergraduate and graduate Nuclear Engineers on the operation of a Pressurized Water Reactor and for simulation of nuclear criticality events. This system will allow users from across the world to access the simulator in order to run modeling and optimization experiments for assisting in the future development of reactor technology and the development of this simulator project.}, booktitle={2007 IEEE Nuclear Science Symposium Conference Record}, publisher={Institute of Electrical & Electronics Engineers (IEEE)}, author={Osborne, Dustin R. and Hou, Jia and Graves, Gary and Miller, Laurence F.}, year={2007}, month={Oct} }