pypolymix

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Authors: Cosmin Safta, Habib N. Najm, Pieterjan Robbe
Cited by: 0

Abstract

SAND2026-16700O Pypolymix builds stochastic surrogate models using a lightweight Python library. Researchers working with large-scale scientific models can use it to enhance optimization and uncertainty quantification studies. Pypolymix enables the efficient construction of surrogate models and improves analysis and performance of complex simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fields of Study & Subjects

Advanced Multi-Objective Optimization Algorithms Probabilistic and Robust Engineering Design Model Reduction and Neural Networks

Publication details

Journal / source
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
Publication date
1 January 2026
Language
EN