Results 91 to 100 of about 31,846 (223)

Quantifying Urban Morphology‐Induced Uncertainty in Urban Meteorology and Heat Stress Simulations in Southern California

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 4, 28 February 2026.
Abstract Accurate representation of land use and urban morphological parameters (UMPs), particularly building height, road width, and roof width, is critical for urban climate/weather modeling. The Weather Research and Forecasting (WRF) coupled with the Single‐Layer Urban Canopy Model (SLUCM) has been widely used; however, few studies have quantified ...
Hao Hu, Xinyi Zhang, Cenlin He, Ellis Fertig, Reza Zarrin, Soroush E. Neyestani, Jiachen Zhang   +6 more
wiley   +1 more source

Bifurcation Analysis with Aerodynamic-Structure Uncertainties by the Nonintrusive PCE Method

International Journal of Aerospace Engineering, 2017
An aeroelastic model for airfoil with a third-order stiffness in both pitch and plunge degree of freedom (DOF) and the modified Leishman–Beddoes (LB) model were built and validated.
Linpeng Wang, Yuting Dai, Chao Yang
doaj   +1 more source

A polynomial chaos expansion in dependent random variables

Journal of Mathematical Analysis and Applications, 2018
26 pages, three figures, four tables; accepted by Journal of Mathematical Analysis and Applications.
openaire   +3 more sources

Buckling Sensitivity of Tow-Steered Plates Subjected to Multiscale Defects by High-Order Finite Elements and Polynomial Chaos Expansion. [PDF]

Materials (Basel), 2021
Sanchez-Majano AR, Pagani A, Petrolo M, Zhang C.   +3 more
europepmc   +1 more source

Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion

Advances in Mechanical Engineering
To address the challenge of balancing accuracy and computational efficiency in evaluating the measurement error and uncertainty of surface profile errors on complex free-form surfaces, this paper proposes an evaluation method combining adaptive sparse ...
Ke Zhang, Xinya Zheng, Ruiyu Zhang
doaj   +1 more source

Sparse polynomial chaos expansion for universal stochastic kriging

Journal of Computational and Applied Mathematics
Surrogate modelling techniques have opened up new possibilities to overcome the limitations of computationally intensive numerical models in various areas of engineering and science. However, while fundamental in many engineering applications and decision-making, the incorporation of uncertainty quantification into meta-models remains a challenging ...
J.C. García-Merino, C. Calvo-Jurado, E. García-Macías   +2 more
openaire   +4 more sources

Uncertainty Quantification at the Molecular–Continuum Model Interface †

Fluids, 2017
Non-equilibrium molecular dynamics simulations are widely employed to study transport fluid properties. Observables measured at the atomistic level can serve as inputs for continuum calculations, allowing for improved analysis of phenomena involving ...
Małgorzata J. Zimoń, Robert Sawko, David R. Emerson, Christopher Thompson   +3 more
doaj   +1 more source

Polynomial Chaos Expansion Based Rauch–Tung–Striebel Smoothers

2024 27th International Conference on Information Fusion (FUSION)
Peer ...
Kumar Kundan, Särkkä Simo
openaire   +2 more sources

Multi-parameter identification of concrete dam using polynomial chaos expansion and slime mould algorithm

Computers & Structures, 2023
Li Yifei, MaoSen Cao, H.Tran-Ngoc, S. Khatir, M. Abdel Wahab   +4 more
semanticscholar   +1 more source

Combining Polynomial Chaos Expansions and Kriging

, 2014
Computer simulation has emerged as a key tool for designing and assessing engineeringsystems in the last two decades. Uncertainty quantification has becomepopular more recently as a way to model all the uncertainties affecting the systemand their impact onto its performance.In this respect meta-models (a.k.a.
Schöbi, R., Kersaudy, P., Sudret, B., Wiart, J.   +3 more
openaire   +1 more source