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We present a novel, generalised formulation to treat coupled structural integrity problems by combining phase field and multi-physics modelling. The approach exploits the versatility of the heat transfer equation and is therefore well…

Computational Engineering, Finance, and Science · Computer Science 2025-06-27 Y. Navidtehrani , C. Betegón , E. Martínez-Pañeda

Data-informed predictive maintenance planning largely relies on stochastic deterioration models. Monitoring information can be utilized to update sequentially the knowledge on time-invariant deterioration model parameters either within an…

Computation · Statistics 2023-08-02 Antonios Kamariotis , Luca Sardi , Iason Papaioannou , Eleni Chatzi , Daniel Straub

The quantitative phase image formation process is posed as a problem of parameter estimation from intensity measurements. This approach is inclusive of traditional pixel-oriented imaging, where the sought parameters are the pixel values.…

Classical Physics · Physics 2024-07-04 George Barbastathis

Modeling gas flow through fractures of subsurface rock is a particularly challenging problem because of the heterogeneous nature of the material. High-fidelity simulations using discrete fracture network (DFN) models are one methodology for…

We consider a one-dimensional fracture problem modelled using either the phase-field or lip-field approach. In both cases, we optimise the incremental potential with respect to the displacement and damage fields and the nodal coordinates of…

Computational Engineering, Finance, and Science · Computer Science 2025-09-08 Nicolas Moës , Benoît Lé , Nicolas Chevaugeon , Jean-François Remacle

The phase-field approach to fracture has been proven to be a mathematically sound and easy to implement method for computing crack propagation with arbitrary crack paths. Hereby crack growth is driven by energy minimization resulting in a…

Numerical Analysis · Mathematics 2019-06-26 Carola Bilgen , Kerstin Weinberg

We present a Bayesian method for feature selection in the presence of grouping information with sparsity on the between- and within group level. Instead of using a stochastic algorithm for parameter inference, we employ expectation…

Machine Learning · Statistics 2018-09-26 Edgar Steiger , Martin Vingron

Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the output of numerical methods. The use of these methods is usually motivated by the fact that they can represent our uncertainty due to…

Computation · Statistics 2018-08-01 Xiaoyue Xi , François-Xavier Briol , Mark Girolami

We develop a novel constitutive modeling approach for the analysis of fracture propagation in quasi-brittle materials using the Material Point Method. The kinematics of constitutive models is enriched with an additional mode of localized…

Computational Physics · Physics 2014-06-06 Giang Dinh Nguyen

Discharge of hazardous substances into the marine environment poses a substantial risk to both public health and the ecosystem. In such incidents, it is imperative to accurately estimate the release strength of the source and reconstruct…

Signal Processing · Electrical Eng. & Systems 2024-10-29 Yang Liu , Christopher M. Harvey , Frederick E. Hamlyn , Cunjia Liu

We present a continuum phase-field model of crack propagation. It includes a phase-field that is proportional to the mass density and a displacement field that is governed by linear elastic theory. Generic macroscopic crack growth laws…

Materials Science · Physics 2009-11-07 L. O. Eastgate , J. P. Sethna , M. Rauscher , T. Cretegny , C. -S. Chen , C. R. Myers

In this work, we present a mathematical model to describe the adsorption-diffusion process on fractal porous materials. This model is based on the fractal continuum approach and considers the scale-invariant properties of the surface and…

The $\xi$-based spatially adaptive three-field variable phase-field model for quasi-static anti-plane crack propagation is introduced. A dynamically optimized regularization length is integrated to improve computational efficiency and…

Numerical Analysis · Mathematics 2025-06-17 Maria P. Fernando , S. M. Mallikarjunaiah

This study addresses ductile fracture of single grains in metals by modeling of the formation and propagation of transgranular cracks. A proposed model integrates gradient extended hardening, phase-field modeling for fracture, and crystal…

Numerical Analysis · Mathematics 2024-11-01 Kim Louisa Auth , Jim Brouzoulis , Magnus Ekh

Multiscale computational modelling is challenging due to the high computational cost of direct numerical simulation by finite elements. To address this issue, concurrent multiscale methods use the solution of cheaper macroscale surrogates…

Computational Engineering, Finance, and Science · Computer Science 2022-01-20 Vasilis Krokos , Viet Bui Xuan , Stéphane P. A. Bordas , Philippe Young , Pierre Kerfriden

When using the finite element method (FEM) in inverse problems, its discretization error can produce parameter estimates that are inaccurate and overconfident. The Bayesian finite element method (BFEM) provides a probabilistic model for the…

Numerical Analysis · Mathematics 2026-01-26 Anne Poot , Iuri Rocha , Pierre Kerfriden , Frans van der Meer

This paper presents a macroscopic theory, alongside its numerical implementation, aimed at describing, explaining, and predicting the nucleation and propagation of fracture in viscoelastic materials subjected to quasistatic loading…

Soft Condensed Matter · Physics 2025-06-23 Farhad Kamarei , Evan Breedlove , Oscar Lopez-Pamies

In this paper, we study porous media flows in heterogeneous stochastic media. We propose an efficient forward simulation technique that is tailored for variational Bayesian inversion. As a starting point, the proposed forward simulation…

Applications · Statistics 2018-02-12 Keren Yang , Nilabja Guha , Yalchin Efendiev , Bani K. Mallick

Fractured metal fragments with rough and irregular surfaces are often found at crime scenes. Current forensic practice visually inspects the complex jagged trajectory of fractured surfaces to recognize a ``match'' using comparative…

In many inverse problems, model parameters cannot be precisely determined from observational data. Bayesian inference provides a mechanism for capturing the resulting parameter uncertainty, but typically at a high computational cost. This…

Computation · Statistics 2019-03-28 Matthew Parno , Tarek Moselhy , Youssef Marzouk