Results 21 to 30 of about 13,481 (226)
Sparse Polynomial Chaos expansions using variational relevance vector machines [PDF]
Journal of Computational Physics, 2020 The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations. These challenges can be addressed by enforcing sparsity in the series representation through retaining only the most important basis terms.
Panagiotis Tsilifis +3 more
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Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction. [PDF]
PLoS Computational BiologyComputational inverse problems for biomedical simulators suffer from limited data and relatively high parameter dimensionality. This often requires sensitivity analysis, where parameters of the model are ranked based on their influence on the specific ...
Mitchel J Colebank
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Uncertainty Quantification in SAR Induced by Ultra-High-Field MRI RF Coil via High-Dimensional Model Representation [PDF]
BioengineeringAs magnetic field strength in Magnetic Resonance Imaging (MRI) technology increases, maintaining the specific absorption rate (SAR) within safe limits across human head tissues becomes challenging due to the formation of standing waves at a shortened ...
Xi Wang +2 more
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International Journal for Numerical Methods in Fluids, Volume 98, Issue 5, Page 557-577, May 2026.This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element‐Volume method.
Nathalie Nouaime +3 more
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Surrogate models for the blade element momentum aerodynamic model using non-intrusive polynomial chaos expansions [PDF]
Wind Energy Science, 2022 In typical industrial practice based on IEC standards, wind turbine simulations are computed in the time domain for each mean wind speed bin using a few unsteady wind seeds.
R. Haghi, C. Crawford
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Physics-informed polynomial chaos expansions
Journal of Computational Physics, 2023 Surrogate modeling of costly mathematical models representing physical systems is challenging since it is typically not possible to create a large experimental design. Thus, it is beneficial to constrain the approximation to adhere to the known physics of the model.
Lukáš Novák +2 more
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Efficient Bayesian calibration of aerodynamic wind turbine models using surrogate modeling [PDF]
Wind Energy Science, 2022 This paper presents an efficient strategy for the Bayesian calibration of parameters of aerodynamic wind turbine models. The strategy relies on constructing a surrogate model (based on adaptive polynomial chaos expansions), which is used to perform both ...
B. Sanderse +4 more
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Polynomial chaos Kalman filter for target tracking applications
IET Radar, Sonar & Navigation, 2023 In this paper, an approximate Gaussian state estimator is developed based on generalised polynomial chaos expansion for target tracking applications. Motivated by the fact that calculating conditional moments in an approximate Gaussian filter involves ...
Kundan Kumar +3 more
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Shock and Vibration, 2021 For the vibro-acoustic system with interval and random uncertainties, polynomial chaos expansions have received broad and persistent attention. Nevertheless, the cost of the computation process increases sharply with the increasing number of uncertain ...
Shengwen Yin, Xiaohan Zhu, Xiang Liu
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Aerospace, 2023 Uncertainties in the atmosphere and flight conditions can drastically impact the performance of an aircraft and result in certification delays. However, uncertainty propagation in high-fidelity simulations, which have become integral to the design ...
Nikhil Iyengar +2 more
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