Results 61 to 70 of about 1,013 (219)

Uncertainty Quantification in Mooring Cable Dynamics Using Polynomial Chaos Expansions

Journal of Marine Science and Engineering, 2020
Mooring systems exhibit high failure rates. This is especially problematic for offshore renewable energy systems, like wave and floating wind, where the mooring system can be an active component and the redundancy in the design must be kept low.
Guilherme Moura Paredes, Claes Eskilsson, Allan P. Engsig-Karup   +2 more
doaj   +1 more source

Efficient Gradient‐Enhanced Bayesian Optimizer with Comparisons to Conjugate‐Gradient and Quasi‐Newton Optimizers for Unconstrained Local Optimization

International Journal for Numerical Methods in Engineering, Volume 127, Issue 4, 28 February 2026.
ABSTRACT The probabilistic surrogates used by Bayesian optimizers make them popular methods when function evaluations are noisy or expensive to evaluate. While Bayesian optimizers are traditionally used for global optimization, their benefits are also valuable for local optimization.
André L. Marchildon, David W. Zingg
wiley   +1 more source

Stochastic Optimization of Economic Dispatch With Wind and Photovoltaic Energy Using the Nested Sparse Grid-Based Stochastic Collocation Method

IEEE Access, 2019
Due to the increasing uncertainty brought about by renewable energy, conventional deterministic dispatch approaches have not been very applicative. This paper investigates a nested sparse grid-based stochastic collocation method (NS-SCM) as a possible ...
Zhilin Lu, Mingbo Liu, Wentian Lu, Zhuoming Deng   +3 more
doaj   +1 more source

Probabilistic Identification of Parameters in Dynamic Fracture Propagation

International Journal for Numerical Methods in Engineering, Volume 127, Issue 4, 28 February 2026.
ABSTRACT In this paper, we propose a novel multiphase approach for identifying input parameters in dynamic fracture propagation. Often, such parameters are partially known and uncertain with incomplete input data, resulting in challenges in predicting a reliable dynamic failure response.
Andjelka Stanić, Mijo Nikolić, Hermann G. Matthies, Noémi Friedman   +3 more
wiley   +1 more source

Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation

Open Mathematics, 2018
This paper presents a methodology to quantify computationally the uncertainty in a class of differential equations often met in Mathematical Physics, namely random non-autonomous second-order linear differential equations, via adaptive generalized ...
Calatayud Julia, Cortés Juan Carlos, Jornet Marc   +2 more
doaj   +1 more source

Physics‐Informed Emulation of Systemic Circulation for Fast Parameter Estimation and Uncertainty Quantification

International Journal for Numerical Methods in Biomedical Engineering, Volume 42, Issue 2, February 2026.
This work presents an innovative approach to modelling 1D fluid dynamics in complex networks using physics‐informed neural networks as surrogate models. By integrating physics‐based constraints with data‐driven learning, we develop an efficient and generalisable framework for uncertainty quantification and parameter estimation in real‐world ...
William Ryan, Alyssa Taylor‐LaPole, Mette Olufsen, Dirk Husmeier, Vladislav Vyshemirskiy   +4 more
wiley   +1 more source

Sharp commutator estimates of all order for Coulomb and Riesz modulated energies

Communications on Pure and Applied Mathematics, Volume 79, Issue 2, Page 207-292, February 2026.
Abstract We prove functional inequalities in any dimension controlling the iterated derivatives along a transport of the Coulomb or super‐Coulomb Riesz modulated energy in terms of the modulated energy itself. This modulated energy was introduced by the second author and collaborators in the study of mean‐field limits and statistical mechanics of ...
Matthew Rosenzweig, Sylvia Serfaty
wiley   +1 more source

Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction

Frontiers in Neuroscience, 2019
Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the ...
Johannes Vorwerk, Johannes Vorwerk, Johannes Vorwerk, Ümit Aydin, Ümit Aydin, Carsten H. Wolters, Carsten H. Wolters, Christopher R. Butson, Christopher R. Butson, Christopher R. Butson   +9 more
doaj   +1 more source

Convergence properties of dynamic mode decomposition for analytic interval maps

Communications on Pure and Applied Mathematics, Volume 79, Issue 2, Page 179-206, February 2026.
Abstract Extended dynamic mode decomposition (EDMD) is a data‐driven algorithm for approximating spectral data of the Koopman operator associated to a dynamical system, combining a Galerkin method with N$N$ functions and a quadrature method with M$M$ quadrature nodes.
Elliz Akindji, Julia Slipantschuk, Oscar F. Bandtlow, Wolfram Just   +3 more
wiley   +1 more source

Robust Trajectory Optimization of a Ski Jumper for Uncertainty Influence and Safety Quantification

Proceedings, 2018
This paper deals with the development of a robust optimal control framework for a previously developed multi-body ski jumper simulation model by the authors.
Patrick Piprek, Florian Holzapfel
doaj   +1 more source