Detail publikačního výsledku

Physics-Informed Polynomial Chaos Expansions: Recent Developments and Comparisons

NOVÁK, L.; LU, Q.; SHARMA, H.; ROY SARKAR, D.; GOSWAMI, S.; SHIELDS, M.

Originální název

Physics-Informed Polynomial Chaos Expansions: Recent Developments and Comparisons

Anglický název

Physics-Informed Polynomial Chaos Expansions: Recent Developments and Comparisons

Druh

Stať ve sborníku mimo WoS a Scopus

Originální abstrakt

This work presents recent developments in a constrained polynomial chaos expansion as a physics-informed machine learning technique. Specifically, an optimized numerical solver for straightforward updating of Lagrange multipliers and an improved statistical sampling method are compared to the original algorithm for estimating deterministic coefficients. Both techniques are applied to solve a heat equation with Neumann boundary conditions. A second study presents a preliminary numerical comparison of the constrained polynomial chaos expansion and physics-informed deep operator networks with respect to computational cost and achieved accuracy.

Anglický abstrakt

This work presents recent developments in a constrained polynomial chaos expansion as a physics-informed machine learning technique. Specifically, an optimized numerical solver for straightforward updating of Lagrange multipliers and an improved statistical sampling method are compared to the original algorithm for estimating deterministic coefficients. Both techniques are applied to solve a heat equation with Neumann boundary conditions. A second study presents a preliminary numerical comparison of the constrained polynomial chaos expansion and physics-informed deep operator networks with respect to computational cost and achieved accuracy.

Klíčová slova

Scientific machine learning, Uncertainty quantification, Physics-informed Polynomial chaos expansion, Physics-informed deep operator networks , Statistical sampling

Klíčová slova v angličtině

Scientific machine learning, Uncertainty quantification, Physics-informed Polynomial chaos expansion, Physics-informed deep operator networks , Statistical sampling

Autoři

NOVÁK, L.; LU, Q.; SHARMA, H.; ROY SARKAR, D.; GOSWAMI, S.; SHIELDS, M.

Vydáno

17.05.2025

Nakladatel

CIMNE

Kniha

14th International Conference on Structural Safety and Reliability

Strany od

1

Strany do

9

Strany počet

9

URL

https://www.scipedia.com/public/Novak_et_al_2025a

BibTex

@inproceedings{BUT200567,
  author="Lukáš {Novák} and Qitian {Lu} and Himanshu {Sharma} and  {} and Michael {Shields} and  {}",
  title="Physics-Informed Polynomial Chaos Expansions: Recent Developments and Comparisons",
  booktitle="14th International Conference on Structural Safety and Reliability",
  year="2025",
  pages="9",
  publisher="CIMNE",
  doi="10.23967/icossar.2025.076",
  url="https://www.scipedia.com/public/Novak_et_al_2025a"
}