@article{andersen_kropaczek_2023, title={MOOGLE: A Multi-Objective Optimization tool for three-dimensional nuclear fuel assembly design}, volume={155}, ISSN={["1878-4224"]}, DOI={10.1016/j.pnucene.2022.104518}, abstractNote={MOOGLE is a new genetic algorithm based methodology for the 3D design of nuclear fuel assemblies. MOOGLE uses common fuel rod types as the decision variable to develop a suite of 3D fuel assemblies to provide optimized solutions to the design problem. Pressurized water reactor (PWR) fuel assemblies were optimized using Integral Fuel Burnable Absorber (IFBA) and gadolinium (Gd2O3) as burnable poisons to compare how burnable poison choice affects optimization results. Boiling water reactor (BWR) fuel bundles were also optimized using three unique fuel rod palettes to study how the size of the design space affects optimization results. Burnable poison analysis showed that utilizing IFBA and Gd2O3 as burnable poisons produced the best and widest range of optimized solutions. BWR fuel bundle optimization results indicate that the inclusion of additional fuel rod types produced a wider solution space but did not improve optimization results for regions explored using fewer unique fuel rods. These tests demonstrate MOOGLE’s ability to analyze the trade-offs between the inclusion of different fuel elements and their effects on assembly performance.}, journal={PROGRESS IN NUCLEAR ENERGY}, author={Andersen, Brian and Kropaczek, David J.}, year={2023}, month={Jan} }
 @article{toptan_salko_avramova_clarno_kropaczek_2019, title={A new fuel modeling capability, CTFFuel, with a case study on the fuel thermal conductivity degradation}, volume={341}, ISSN={["1872-759X"]}, DOI={10.1016/j.nucengdes.2018.11.010}, abstractNote={A new fuel modeling capability, CTFFuel, is developed from the subchannel code, CTF. This code is a standalone interface to the CTF fuel rod models, allowing for fuel rod simulations to be run independently from the fluid. This paper provides an overview of the code with a case study on the thermal conductivity degradation of LWR fuels to demonstrate its capabilities. The modeling of fuel thermal conductivity degradation in the code is improved through the addition of new modeling options to account for the irradiation effects via globally defined parameters. After the initial implementation, a variety of order-of-accuracy tests and code comparisons are performed to test software quality. A controlled analysis is allowed by CTFFuel to verify the numerical scheme of CTF’s conduction solution and to benchmark its fuel temperature predictions against FRAPCON-4.0’s. Overall, the software quality and verification procedure ensures that the new model is coded correctly, that it properly interacts with the rest of the code.}, journal={NUCLEAR ENGINEERING AND DESIGN}, author={Toptan, Aysenur and Salko, Robert K. and Avramova, Maria N. and Clarno, Kevin and Kropaczek, David J.}, year={2019}, month={Jan}, pages={248–258} }
 @article{kropaczek_walden_2019, title={Constraint Annealing Method for Solution of Multiconstrained Nuclear Fuel Cycle Optimization Problems}, volume={193}, ISSN={["1943-748X"]}, DOI={10.1080/00295639.2018.1554173}, abstractNote={Abstract A method is developed, assessed, and demonstrated for addressing objective functions and constraints within the context of combinatorial optimization problems. The penalty-free method developed, referred to as constraint annealing, eliminates the use of traditional constraint penalty factors by treating the objective functions and constraints as separate and concurrently solved minimization problems within a global optimization search framework. The basis of the constraint annealing algorithm is a highly scalable method based on the method of parallel simulated annealing with mixing of states. Unique to constraint annealing is a novel approach that employs both global solution acceptance and local objective function and constraint statistics in the calculation of adaptive cooling temperatures that are specific to each objective function and constraint. The constraint annealing method is assessed against a traditional penalty-factor approach for a realistic core loading pattern design problem and shown to be robust with respect to elimination of arbitrary weighting factors on constraint values. In addition, the constraint annealing method is demonstrated to be robust with respect to parallel scaling as well as improved optimization performance on high-performance-computing systems.}, number={5}, journal={NUCLEAR SCIENCE AND ENGINEERING}, author={Kropaczek, David J. and Walden, Ryan}, year={2019}, pages={506–522} }
 @article{toptan_kropaczek_avramova_2019, title={Gap conductance modeling I: Theoretical considerations for single- and multi-component gases in curvilinear coordinates}, volume={353}, ISSN={["1872-759X"]}, DOI={10.1016/j.nucengdes.2019.110283}, abstractNote={Abstract Accurate estimation of heat transfer across the gap is important in nuclear fuel performance because heat transfer across the fuel-to-cladding gap heavily impacts fuel temperatures and the thermo-mechanical performance of nuclear fuel rods. Better understood physics will allow a better prediction of the gap behavior. This paper focuses on providing an overview of the gap conductance model including theoretical considerations and underlying assumptions. The gap conductance is calculated considering three summed heat paths: fill gas conductance, direct thermal radiation, and solid contact conductance. Each heat transfer mechanism is described in detail. First, the models are generalized to curvilinear coordinates for diatomic/polyatomic molecules. Traditional models use one-dimensional Cartesian equations for a monatomic gas. Second, expressions for temperature jump distance and thermal accommodation coefficients are made consistent with the kinetic theory for both single- and multi-component gases. Lastly, fill gas thermal conductivity is updated to include its dependence on rod internal pressure.}, journal={NUCLEAR ENGINEERING AND DESIGN}, author={Toptan, Aysenur and Kropaczek, David J. and Avramova, Maria N.}, year={2019}, month={Nov} }
 @article{toptan_kropaczek_avramova_2019, title={Gap conductance modeling II: Optimized model for UO2-Zircaloy interfaces}, volume={355}, ISSN={["1872-759X"]}, DOI={10.1016/j.nucengdes.2019.110289}, abstractNote={The model conventionally used to calculate heat transfer across the fuel-cladding gap in light water nuclear reactors is a modified version of the Ross-Stoute model. The model was modified to include gap distance in the formulation, which introduced additional uncertainties because the model parameters were not adjusted after the modification. In this study, this conventional model is optimized for uranium dioxide-Zircaloy interfaces using experimental data at high pressure for single- and multi-component gases. First, a calibration is performed for single-component gases. Second, the calibration is extended to multi-component gases, which allows for a demonstration of sources of uncertainty in the model. Third, a general form of the gap conductance model is optimized by combining both data sets. Difficulties arise due to: (i) inaccurate estimation of contact characteristics (e.g., number of solid contacts, deformation mechanism of surface irregularities, contact shapes) that are different for each experimental setup; (ii) the non-physical ratio of temperature jump distance to the gap distance for postulated model function form; (iii) an insufficient description of the appropriate heat transfer regime; and (iv) the pressure dependence of thermal conductivity for inert gases aside from helium. Lastly, a general model is optimized by setting the temperature jump distance at the wall to zero, which reduces possible uncertainties. This final analysis results in a more accurate prediction of the available experimental data. The Associated parameter uncertainty of the model is estimated by performing uncertainty propagation. Overall, the optimized model results in a larger gap conductance with significantly reduced error.}, journal={NUCLEAR ENGINEERING AND DESIGN}, author={Toptan, Aysenur and Kropaczek, David J. and Avramova, Maria N.}, year={2019}, month={Dec} }
 @article{kropaczek_walden_2019, title={Large-Scale Application of the Constraint Annealing Method for Pressurized Water Reactor Core Design Optimization}, volume={193}, ISSN={["1943-748X"]}, DOI={10.1080/00295639.2018.1550970}, abstractNote={Abstract The constraint annealing method is presented and demonstrated for the solution of large-scale, multiconstrained problems in light water reactor fuel cycle optimization. Constraint annealing is a penalty-free method that eliminates the need for traditional constraint weighting factors by treating each objective function and constraint as separate and concurrently solved minimization problems within a global optimization search framework. The current application seeks to demonstrate the effectiveness of constraint annealing for a complex core loading pattern design problem containing multiple objective functions and constraints without the need for additional ad hoc control parameters. Two problems of varying degrees of complexity are analyzed. The first problem is defined by a single objective function based on maximizing cycle energy with two constraints based on power peaking and peak rod exposure. The second problem expands upon the first by adding an additional objective function for vessel fluence and four additional constraints based on controlled power peaking, steaming rate, moderator temperature coefficient, and alternate source term. Results demonstrate that constraint annealing inherently addresses issues of scaling associated with different objective function and constraint formulations as well as the impact on cycle energy.}, number={5}, journal={NUCLEAR SCIENCE AND ENGINEERING}, author={Kropaczek, David J. and Walden, Ryan}, year={2019}, pages={523–536} }
 @article{toptan_kropaczek_avramova_2019, title={On the validity of the dilute gas assumption for gap conductance calculations in nuclear fuel performance codes}, volume={350}, ISSN={["1872-759X"]}, DOI={10.1016/j.nucengdes.2019.04.042}, abstractNote={Fill gas thermal conductivity’s dependence on pressure is neglected in today’s nuclear fuel performance codes. Current codes assume that gas behaves as a dilute gas, but the pressure effect is more pronounced at temperatures lower than ten times the critical temperature of each pure gas. The validity of this assumption for nuclear fuel performance is examined herein. Theories related to dilute and dense gas properties are presented, along with their validation against literature data at up to 30 MPa for selected inert gases. Underlying assumptions are clearly described for each model, and their possible impacts on gap conductance calculations are discussed. The dilute gas assumption is valid for helium because it behaves as a dilute gas. However, the assumption is not valid in most gap conductance calculations when the gap is mostly occupied with either lower conductivity gaseous fission products or an initial fill gas other than helium.}, journal={NUCLEAR ENGINEERING AND DESIGN}, author={Toptan, Aysenur and Kropaczek, David J. and Avramova, Maria N.}, year={2019}, month={Aug}, pages={1–8} }