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Title: MOOSE Optimization Module: Physics-constrained optimization

Journal Article · · SoftwareX
 [1]; ORCiD logo [1]; ORCiD logo [1];  [2];  [3]
  1. Idaho National Laboratory (INL), Idaho Falls, ID (United States)
  2. Idaho National Laboratory (INL), Idaho Falls, ID (United States); Duke University, Durham, NC (United States)
  3. North Carolina State University, Raleigh, NC (United States)

The MOOSE Optimization Module integrates optimization capabilities within the MOOSE framework, enabling efficient and accurate physics-constrained optimization. This module leverages automatic differentiation to compute Jacobians and employs an automatic adjoint formulation for gradient computation, significantly simplifying the implementation of optimization algorithms. The primary goal of this software is to provide a platform where analysts and researchers can rapidly prototype and explore new optimization algorithms tailored to their complex multiphysics problems without requiring them to be computational experts. By handling the aspects of adjoint problem formulation and gradient computation, the module allows users to focus on the optimization problem itself, thereby accelerating the development of more efficient designs and solutions.

Research Organization:
Idaho National Laboratory (INL), Idaho Falls, ID (United States)
Sponsoring Organization:
USDOE Office of Nuclear Energy (NE); USDOE Laboratory Directed Research and Development (LDRD) Program
Grant/Contract Number:
AC07-05ID14517
OSTI ID:
2345795
Alternate ID(s):
OSTI ID: 2352472
Report Number(s):
INL/JOU-24-76848-Revision-0; TRN: US2411303
Journal Information:
SoftwareX, Vol. 26, Issue -; ISSN 2352-7110
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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