Abstract
The U.S. Department of Energy Light Water Reactor Sustainability Program Risk-Informed Systems Analysis Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimizing core design. Optimizing the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible core configuration options, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization platform, which supports artificial-intelligence-based reactor core designing, is now fully capable of handling realistic problems. The Plant ReLoad Optimization platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual ENvironment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multiobjective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.
| Original language | English |
|---|---|
| State | Published - 2024 |
| Event | LWRS Spring Meeting - Virtual Duration: Apr 30 2024 → May 1 2024 |
Conference
| Conference | LWRS Spring Meeting |
|---|---|
| Period | 04/30/24 → 05/1/24 |
Keywords
- 11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS
- 22 - GENERAL STUDIES OF NUCLEAR REACTORS
- plant reload optimization
- fuel cost
- genetic algorithm
- NSGA-II
INL Publication Number
- INL/MIS-24-77706
- 172282
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