Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions. [PDF]
PLoS Computational Biology, 2019 We present a novel surrogate modeling method that can be used to accelerate the solution of uncertainty quantification (UQ) problems arising in nonlinear and non-smooth models of biological systems.
Joel A Paulson +2 more
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Stochastic Chaos and Markov Blankets [PDF]
Entropy, 2021 In this treatment of random dynamical systems, we consider the existence—and identification—of conditional independencies at nonequilibrium steady-state.
Karl Friston +4 more
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Uncertainty propagation in pore water chemical composition calculation using surrogate models [PDF]
Scientific Reports, 2022 Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations.
Pierre Sochala +3 more
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Broad ranges of investment configurations for renewable power systems, robust to cost uncertainty and near-optimality [PDF]
iScience, 2023 Summary: Achieving ambitious CO2 emission reduction targets requires energy system planning to accommodate societal preferences, such as transmission reinforcements or onshore wind parks, and acknowledge uncertainties in technology cost projections among
Fabian Neumann, Tom Brown
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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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HIERARCHICAL ADAPTIVE POLYNOMIAL CHAOS EXPANSIONS [PDF]
Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015), 2015 Polynomial chaos expansions (PCE) are widely used in the framework of uncertainty quantification. However, when dealing with high dimensional complex problems, challenging issues need to be faced. For instance, high-order polynomials may be required, which leads to a large polynomial basis whereas usually only a few of the basis functions are in fact ...
Mai, Chu V., Sudret, Bruno
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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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