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Multimodal variational autoencoder for inverse problems in geophysics: application to a 1-D magnetotelluric problem
(2023-12)
Estimating subsurface properties from geophysical measurements is a common inverse problem. Several Bayesian methods currently aim to find the solution to a geophysical inverse problem and quantify its uncertainty. However, ...
Fast parallel IGA-ADS solver for time-dependent Maxwell's equations
(2023-12)
We propose a simulator for time-dependent Maxwell's equations with linear computational cost. We employ B-spline basis functions as considered in the isogeometric analysis (IGA). We focus on non-stationary Maxwell's equations ...
Diagnosis of the health status of mooring systems for floating offshore wind turbines using autoencoders
(2023-11-01)
Floating offshore wind turbines (FOWTs) show promise in terms of energy production, availability, and sustainability, but remain unprofitable due to high maintenance costs. This work proposes a deep learning algorithm to ...
Machine learning discovery of optimal quadrature rules for isogeometric analysis
(2023-11-01)
We propose the use of machine learning techniques to find optimal quadrature rules for the construction of stiffness and mass matrices in isogeometric analysis (IGA). We initially consider 1D spline spaces of arbitrary ...
Physics-guided deep-learning inversion method for the interpretation of noisy logging-while-drilling resistivity measurements
(2023-10)
Deep learning (DL) inversion is a promising method for real-Time interpretation of logging-while-drilling (LWD) resistivity measurements for well-navigation applications. In this context, measurement noise may significantly ...
Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations
(2023-10)
This work proposes a novel supervised learning approach to identify damage in operating bridge structures. We propose a method to introduce the effect of environmental and operational conditions into the synthetic damage ...
Neural network architecture optimization using automated machine learning for borehole resistivity measurements
(2023-09)
Deep neural networks (DNNs) offer a real-time solution for the inversion of borehole resistivity measurements to approximate forward and inverse operators. Using extremely large DNNs to approximate the operators is possible, ...
An exponential integration generalized multiscale finite element method for parabolic problems
(2023-04-15)
We consider linear and semilinear parabolic problems posed in high-contrast multiscale media in two dimensions.
The presence of high-contrast multiscale media adversely affects the accuracy, stability, and overall efficiency ...
A Deep Double Ritz Method (D2RM) for solving Partial Differential Equations using Neural Networks
(2023-02-15)
Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields a saddle-point (min–max) problem over the ...
On building physics-based AI models for the design and SHM of mooring systems
(2023-01-01)
Expert systems in industrial processes are modelled using physics-based approaches, data-driven models or hybrid approaches in which however the underlying physical models generally constitute a separate block with respect ...