@article{karve_turinsky_2001, title={FORMOSA-B: A boiling water reactor in-core fuel management optimization package III}, volume={135}, ISSN={["0029-5450"]}, DOI={10.13182/NT01-A3219}, abstractNote={Abstract As part of the continuing development of the boiling water reactor in-core fuel management optimization code FORMOSA-B, the cold shutdown margin (SDM) constraint evaluator has been improved. The SDM evaluator in FORMOSA-B had been a first-order accurate Rayleigh quotient variational technique. It was deemed unreliable for difficult perturbed loading patterns (LPs) and thus was replaced by a high-fidelity, robust, computationally efficient evaluator. The new model is based on the solution of the one-group diffusion equation using approximate albedo boundary conditions for a three-dimensional, variable axial node, 10 × 10 assembly subregion around the stuck rod location. The fidelity and robustness of the model are first demonstrated by performing calculations on difficult perturbed LPs and for different plant cores. It is shown that the SDM reactivity is estimated within 40 pcm for the highest worth rod and that the speedup factors are 50 to 100 for small cores (and even more for larger cores) in comparison to the full-core three-dimensional simulations. Next, the successful implementation of the model in imposing the SDM constraint for FORMOSA-B’s adaptive simulated annealing (SA)-based optimization strategy is presented. The results demonstrate SA’s ability to remove large SDM violations (>700 pcm) along with thermal margin and critical flow constraint violations. Finally, the importance of having the SDM constraint on during optimization is shown by comparing results with a simulation in which the constraint is off.}, number={3}, journal={NUCLEAR TECHNOLOGY}, author={Karve, AA and Turinsky, PJ}, year={2001}, month={Sep}, pages={241–251} }
 @article{karve_turinsky_2000, title={FORMOSA-B: A boiling water reactor in-core fuel management optimization package II}, volume={131}, ISSN={["0029-5450"]}, DOI={10.13182/NT00-A3104}, abstractNote={As part of the continuing development of the boiling water reactor in-core fuel management optimization code FORMOSA-B, the fidelity of the core simulator has been improved and a control rod pattern (CRP) sampling capability has been added. The robustness of the core simulator is first demonstrated by benchmarking against core load-follow depletion predictions of both SIMULATE-3 and MICROBURN-B2 codes. The CRP sampling capability, based on heuristic rules, is next successfully tested on a fixed fuel loading pattern (LP) to yield a feasible CRP that removes the thermal margin and critical flow constraint violations. Its performance in facilitating a spectral shift flow operation is also demonstrated, and then its significant influence on the cost of thermal margin is presented. Finally, the heuristic CRP sampling capability is coupled with the stochastic LP optimization capability in FORMOSA-B—based on simulated annealing (SA)—to solve the combined CRP-LP optimization problem. Effectiveness of the sampling in improving the efficiency of the SA adaptive algorithm is shown by comparing the results to those obtained with the sampling turned off (i.e., only LP optimization is carried out for the fixed reference CRP). The results presented clearly indicate the successful implementation of the CRP sampling algorithm and demonstrate FORMOSA-B’s enhanced optimization features, which facilitate the code’s usage for broader optimization studies.}, number={1}, journal={NUCLEAR TECHNOLOGY}, author={Karve, AA and Turinsky, PJ}, year={2000}, month={Jul}, pages={48–68} }
 @article{moore_turinsky_karve_1999, title={Formosa-B: A boiling water reactor in-core fuel management optimization package}, volume={126}, ISSN={["0029-5450"]}, DOI={10.13182/NT99-A2964}, abstractNote={The computational capability to determine optimal core loading patterns (LPs) for boiling water reactors (BWRs) given a reference control rod program has been developed. The design and fidelity of the reference BWR core simulator are presented. The placement of feed and reload fuel is solved by an adaptive optimization by simulated annealing (OSA) objective algorithm. Objective functions available for BWR fuel management are maximization of end-of-cycle core reactivity, minimization of peak linear power density, maximization of critical power ratio, maximization of region average discharge burnup, and minimization of total reload cost. Constraints include thermal and fuel exposure related limits and cycle energy production, when appropriate. The results presented demonstrate the utility of OSA to improve LPs in this highly nonlinear and constrained search space.}, number={2}, journal={NUCLEAR TECHNOLOGY}, author={Moore, BR and Turinsky, PJ and Karve, AA}, year={1999}, month={May}, pages={153–169} }