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A probabilistic approach to phase-field brittle and ductile fracture with random material and geometric properties is proposed within this work. In the macroscopic failure mechanics, materials properties and exactness of spatial quantities…

Numerical Analysis · Mathematics 2022-08-10 Nima Noii , Amirreza Khodadadian , Fadi Aldakheel

In this work, we propose a parameter estimation framework for fracture propagation problems. The fracture problem is described by a phase-field method. Parameter estimation is realized with a Bayesian framework. Here, the focus is on…

Numerical Analysis · Mathematics 2020-06-22 Amirreza Khodadadian , Nima Noii , Maryam Parvizi , Mostafa Abbaszadeh , Thomas Wick , Clemens Heitzinger

In this work, a Bayesian inversion framework for hydraulic phase-field transversely isotropic and orthotropy anisotropic fracture is proposed. Therein, three primary fields are pressure, displacements, and phase-field while…

Computational Engineering, Finance, and Science · Computer Science 2021-09-22 Nima Noii , Amirreza Khodadadian , Thomas Wick

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

A novel phase-field for ductile fracture model is presented. The model is developed within a consistent variational framework in the context of finite-deformation kinematics. A novel coalescence dissipation introduces a new coupling…

Materials Science · Physics 2021-03-24 Tianchen Hu , Brandon Talamini , Andrew J. Stershic , Michael R. Tupek , John E. Dolbow

This paper introduces a Bayesian framework that combines Markov chain Monte Carlo (MCMC) sampling, dimensionality reduction, and neural density estimation to efficiently handle inverse problems that (i) must be solved multiple times, and…

Computational Engineering, Finance, and Science · Computer Science 2026-02-24 Giacomo Bottacini , Matteo Torzoni , Andrea Manzoni

We study Bayesian inversion for a model elliptic PDE with unknown diffusion coefficient. We provide complexity analyses of several Markov Chain-Monte Carlo (MCMC) methods for the efficient numerical evaluation of expectations under the…

Numerical Analysis · Mathematics 2013-05-01 Viet Ha Hoang , Christoph Schwab , Andrew M. Stuart

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

We propose a novel approach to optimize the design of heterogeneous materials, with the goal of enhancing their effective fracture toughness under mode-I loading. The method employs a Gaussian processes-based Bayesian optimization framework…

Optimization and Control · Mathematics 2023-03-29 Sukhminder Singh , Lukas Pflug , Julia Mergheim , Michael Stingl

Fracture in aluminum alloys with precipitates involves at least two mechanisms, namely, ductile fracture of the aluminum-rich matrix and brittle fracture of the precipitates. In this work, a coupled crystal plasticity-phase field model for…

Materials Science · Physics 2022-05-02 Samad Vakili , Pratheek Shanthraj , Franz Roters , Jaber R. Mianroodi , Dierk Raabe

In this article we consider Bayesian estimation of static parameters for a class of partially observed McKean-Vlasov diffusion processes with discrete-time observations over a fixed time interval. This problem features several obstacles to…

Computation · Statistics 2025-04-23 Ajay Jasra , Amin Wu

Efficient assessment of convolved hidden Markov models is discussed. The bottom-layer is defined as an unobservable categorical first-order Markov chain, while the middle-layer is assumed to be a Gaussian spatial variable conditional on the…

Geophysics · Physics 2017-10-19 Torstein Fjeldstad , Henning Omre

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

This work presents a rigorous mathematical formulation for topology optimization of a macrostructure undergoing ductile failure. The prediction of ductile solid materials which exhibit dominant plastic deformation is an intriguingly…

Numerical Analysis · Mathematics 2023-03-22 Nima Noii , Hassan Ali Jahangiry , Haim Waisman

Fatigue fracture in ductile materials, e. g. metals, is caused by cyclic plasticity. Especially regarding the high numbers of load cycles, plastic material models resolving the full loading path are computationally very demanding. Herein, a…

Materials Science · Physics 2019-10-24 Martha Seiler , Thomas Linse , Peter Hantschke , Markus Kästner

Inverse problems involving partial differential equations (PDEs) are widely used in science and engineering. Although such problems are generally ill-posed, different regularisation approaches have been developed to ameliorate this problem.…

Applications · Statistics 2022-03-23 Jan Povala , Ieva Kazlauskaite , Eky Febrianto , Fehmi Cirak , Mark Girolami

In this study, we address damage initiation and micro-crack formation in ductile failure of polycrystalline metals. We show how our recently published thermodynamic framework for ductile phase-field fracture of single crystals can be…

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

The developed computational approach is capable of initiating and propagating cracks inside materials and along material interfaces of general multi-domain structures under quasi-static conditions. Special attention is paid to particular…

Computational Engineering, Finance, and Science · Computer Science 2023-08-23 Roman Vodička

We address the prediction of ductile damage and material anisotropy accumulated during plastic deformation of metals. A new model of phenomenological metal plasticity is proposed which is suitable for applications involving large…

Materials Science · Physics 2015-04-01 A. V. Shutov , C. B. Silbermann , J. Ihlemann

Uncertainty quantification of groundwater (GW) aquifer parameters is critical for efficient management and sustainable extraction of GW resources. These uncertainties are introduced by the data, model, and prior information on the…

Geophysics · Physics 2021-12-08 Amal Alghamdi , Marc Hesse , Jingyi Chen , Umberto Villa , Omar Ghattas
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