[HTML][HTML] Intrusive and non-intrusive uncertainty quantification methodologies for pyrolysis modeling
H Jamil, F Brännström - Fire Safety Journal, 2024 - Elsevier
In this work we discuss and compare multiple uncertainty analysis methodologies for
pyrolysis modeling. Using Arrhenius equation as the pyrolysis model and kinetic parameters …
pyrolysis modeling. Using Arrhenius equation as the pyrolysis model and kinetic parameters …
Non-linear stochastic dynamics analysis of mechanical systems using non-intrusive polynomial chaos method: application to pole vaulting
O El Mrimar, O Bendaou, B Samoudi - Meccanica, 2023 - Springer
Numerous stochastic methods for accounting for uncertainties in mechanical systems have
been developed to study the randomness of input parameters. In this study, the non-intrusive …
been developed to study the randomness of input parameters. In this study, the non-intrusive …
Quantification and propagation of model-form uncertainties in RANS turbulence modeling via intrusive polynomial chaos
J Parekh, R Verstappen - International Journal for Uncertainty …, 2023 - dl.begellhouse.com
Undeterred by its inherent limitations, Reynolds-averaged Navier-Stokes (RANS) based
modeling is still considered the most recognized approach for several computational fluid …
modeling is still considered the most recognized approach for several computational fluid …
Development and assessment of an intrusive polynomial chaos expansion‐based continuous adjoint method for shape optimization under uncertainties
AK Papageorgiou… - … Methods in Fluids, 2022 - Wiley Online Library
This article contributes to the development of methods for shape optimization under
uncertainties, associated with the flow conditions, based on intrusive Polynomial Chaos …
uncertainties, associated with the flow conditions, based on intrusive Polynomial Chaos …
Development of Methods for Uncertainty Quantification in CFD Applied to Wind Turbine Wake Prediction
J Parekh - 2023 - research.rug.nl
Development of methods /for uncertainty quantification in CFD simulations of wakes in windfarm
Page 1 University of Groningen Development of Methods for Uncertainty Quantification in CFD …
Page 1 University of Groningen Development of Methods for Uncertainty Quantification in CFD …
[PDF][PDF] Inverse Prediction of Material Properties Using Gram-Schmidt Orthogonalized Polynomial Chaos Expansion
R Kumar - researchgate.net
This study explores the effectiveness of Gram-Schmidt Polynomial Chaos Expansion (PCE)
for forward and inverse modeling in stochastic systems. Three cases are considered …
for forward and inverse modeling in stochastic systems. Three cases are considered …
[PDF][PDF] Integrated Stochastic Modeling and Neural Networks for Inverse Prediction of Elastic Modulus in Beams
R Kumar - researchgate.net
In this work we have obtained elastic modulus from the eigen frequencies of a cantilever
beam. The elastic modulus of the beam has random elastic modulus haing exponential …
beam. The elastic modulus of the beam has random elastic modulus haing exponential …