SearcharxivSearch

arXiv · 1605.01402

Challenging Fuel Cycle Modeling Assumptions: Facility and Time Step Discretization Effects

Abstract

Due to the diversity of fuel cycle simulator modeling assumptions, direct comparison and benchmarking can be difficult. In 2012 the Organisation for Economic Co-operation and Development completed a benchmark study that is perhaps the most complete published comparison performed. Despite this, various results from the simulators were often significantly different because of inconsistencies in modeling decisions involving reprocessing strategies, refueling behavior, reactor end-of-life handling, etc. This work identifies and quantifies the effects of selected modeling choices that may sometimes be taken for granted in the fuel cycle simulation domain. Four scenarios are compared using combinations of fleet-based or individually modeled reactors with monthly or quarterly (3-month) time steps. The scenarios approximate a transition from the current U.S. once-through light water reactor fleet to a full sodium fast reactor fuel cycle. The Cyclus fuel cycle simulator's plug-in capability along with its market-like dynamic material routing allow it to be used as a level playing field for comparing the scenarios. When under supply-constraint pressure, the four cases exhibit noticeably different behavior. Fleet-based modeling is more efficient in supply-constrained environments at the expense of losing insight on issues such as realistically suboptimal fuel distribution and challenges in reactor refueling cycle staggering. Finer-grained time steps enable more efficient material use in supply-constrained environments resulting in lower standing inventories of separated Pu. Large simulations with fleet-based reactors run much more quickly than their individual reactor counterparts. Gaining a better understanding of how these and other modeling choices affect fuel cycle dynamics will enable making more deliberate decisions with respect to trade-offs such as computational investment vs. realism.

Explore related subjects

Keep this discovery

BibTeXRIS

Robert W. Carlsen, Paul P. H. Wilson. 2016-05-04. Challenging Fuel Cycle Modeling Assumptions: Facility and Time Step Discretization Effects. https://arxiv.org/abs/1605.01402

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

A Framework for Discharge Time Prediction of Energy Storage Units Based on Coupled Dynamics and Multi-Factor Aging Models

This paper presents a physically interpretable framework for predicting time to empty (TTE) in portable embedded systems. The framework couples usage-driven load-power decomposition, electrical power-voltage-current closure, a semi-empirical aging model, and SOC-temperature dynamics. Smartphone telemetry is mapped to battery current through an interpretable load model and conversion-efficiency correction. Battery capacity loss is modeled by combining Arrhenius temperature dependence, SEI diffusion behavior, and cycle-related power-law degradation. The coupled dynamic model then predicts TTE under different initial SOC values, ambient temperatures, and usage profiles. Chronological hold-out evaluation on a 6.9-h smartphone discharge session yielded a current RMSE of 0.0095 $\pm$ 0.0006 A, a temperature RMSE of 2.93 $\pm$ 0.24$^\circ$C, and a TTE MAPE of 4.81 $\pm$ 0.61%. Evaluation on NASA cell B0005 produced a capacity-loss RMSE of 0.031 Ah. Baseline, ablation, and counterfactual analyses further illustrate the contributions of thermal and aging corrections and the relative influence of load features. The results demonstrate the feasibility and interpretability of the proposed framework, while broader validation across devices and batteries remains necessary.

cs.CE

Node-Shift-Encoding Genetic Algorithm with fuzzy-enhanced reference tour to solve the bi-objective service-oriented TSP

The Travelling Salesman Problem (TSP) remains a key area of research in combinatorial optimization, with applications in logistics, manufacturing, and service delivery. This paper addresses a bi-objective service-oriented TSP in which the clients' ranks in the delivery path matter. Unlike conventional depot-based TSP formulations, the considered problem does not assume a distinguished depot or a fixed tour origin. To address this setting, we adapt the Miller--Tucker--Zemlin (MTZ)-based formulation and derive an original linearization of the resulting model, enabling its solution with off-the-shelf integer linear programming solvers. This adaptation avoids the rigid tour origin imposed by the conventional MTZ formulation, for which fixing the starting node does not affect the tour cost but can affect the objective in a customer-rank-sensitive TSP. To solve this problem, we present a Node-Shift-Encoding (NSE)-based Genetic Algorithm augmented with fuzzy reasoning to update the reference tour throughout the evolutionary process. Experimental evaluation on TSPLIB benchmarks demonstrates that the proposed method achieves improved performance compared with the classical NSE approach.

cs.CE

Geometric organization of olfactory descriptor data in the Poincar\'e disk

Odor quality is commonly represented using high dimensional descriptor profiles, yet their low dimensional organization remains unclear. We investigated whether a two-dimensional hyperbolic embedding can provide an interpretable representation of this structure. We applied hyperbolic metric multidimensional scaling to two complementary datasets: 480 Sagar rating profiles from three participants rating 160 odorants on 15 continuous descriptors, and 4983 GoodScents--Leffingwell molecules annotated with 138 binary descriptors. The embeddings substantially preserved pairwise descriptor distances, supporting subsequent analyses of radial and angular organization. In Sagar, rating profile entropy was strongly and negatively associated with hyperbolic radius, with diffuse profiles closer to the center and concentrated profiles closer to the boundary. This radial organization emerged primarily at the level of the full descriptor profile, rather than any individual descriptor, and remained robust across alternative descriptor representations, participant specific analyses, and averaged ratings. Sweet, musky, fruity, pleasantness showed the strongest directional trends. In GoodScents--Leffingwell, active label entropy, reflecting descriptor multiplicity, increased with radius, whereas orthogonalized descriptor entropy, reflecting spread across orthogonal modes, decreased with radius. Related binary descriptors occupied coherent localized high-density regions. These findings reveal complementary radial and angular organization in the hyperbolic representation of olfactory descriptor data. They support hyperbolic mapping as an interpretable descriptive framework in which radius summarizes global profile properties, while the angular component captures continuous descriptor gradients and categorical organization.

cs.CE