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For multilayer structures, interfacial failure is one of the most important elements related to device reliability. For cohesive zone modelling, traction-separation relations represent the adhesive interactions across interfaces. However,…

Computational Engineering, Finance, and Science · Computer Science 2023-01-02 Congjie Wei , Jiaxin Zhang , Kenneth M. Liechti , Chenglin Wu

In this article, a failure mode dependent and thermodynamically consistent continuum damage model with polynomial-based damage hardening functions is proposed for continuum damage modeling of laminated composite panels. The damage model…

Computational Physics · Physics 2025-09-24 Shubham Rai , Badri Prasad Patel

Data-driven methods have become increasingly more prominent for musculoskeletal modelling due to their conceptually intuitive simple and fast implementation. However, the performance of a pre-trained data-driven model using the data from…

Signal Processing · Electrical Eng. & Systems 2022-11-23 Jie Zhang , Yihui Zhao , Tianzhe Bao , Zhenhong Li , Kun Qian , Alejandro F. Frangi , Sheng Quan Xie , Zhi-Qiang Zhang

Many geologic materials have a composite structure, in which macroscopic mechanical behavior is determined by the properties, shape, and heterogeneous distribution of individual constituents. In particular, sedimentary rocks commonly…

Geophysics · Physics 2020-08-26 Shabnam J. Semnani , Joshua A. White

Nature has always been our inspiration in the research, design and development of materials and has driven us to gain a deep understanding of the mechanisms that characterize anisotropy and inelastic behavior. All this knowledge has been…

Machine Learning · Computer Science 2024-06-05 Hagen Holthusen , Lukas Lamm , Tim Brepols , Stefanie Reese , Ellen Kuhl

Modeling the full-range deformation behaviors of materials under complex loading and materials conditions is a significant challenge for constitutive relations (CRs) modeling. We propose a general encoder-decoder deep learning framework…

Materials Science · Physics 2023-04-04 Qing-Jie Li , Mahmut Nedim Cinbiz , Yin Zhang , Qi He , Geoffrey Beausoleil , Ju Li

Machine-learning function representations such as neural networks have proven to be excellent constructs for constitutive modeling due to their flexibility to represent highly nonlinear data and their ability to incorporate constitutive…

Soft Condensed Matter · Physics 2024-04-25 Jan N. Fuhg , Asghar Jadoon , Oliver Weeger , D. Thomas Seidl , Reese E. Jones

The development of accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions…

Machine Learning · Computer Science 2023-02-22 Jan N. Fuhg , Craig M. Hamel , Kyle Johnson , Reese Jones , Nikolaos Bouklas

The simulation of growth processes within soft biological tissues is of utmost importance for many applications in the medical sector. Within this contribution we propose a new macroscopic approach fro modelling stress-driven volumetric…

Computational Engineering, Finance, and Science · Computer Science 2022-01-21 L. Lamm , H. Holthusen , T. Brepols , S. Jockenhövel , S. Reese

There has been increasing experimental evidence of non-affine elastic deformation mechanisms in biological soft tissues. These observations call for novel constitutive models which are able to describe the dominant underlying…

Computational Physics · Physics 2021-03-04 Sebastian Skatulla , Carlo Sansour , Georges Limbert

A constitutive model is presented for brittle granular materials based on a recent reformulation of the breakage mechanics theory. Compared with previous breakage mechanics-based models, the proposed model is improved to capture strain…

Soft Condensed Matter · Physics 2019-02-21 M. B. Cil , R. C. Hurley , L. Graham-Brady

A data driven finite element method (DDFEM) that accounts for more than two material state variables has been presented in this work. DDFEM framework is motivated from (1,2) and can account for multiple state variables, viz. stresses,…

Computational Physics · Physics 2020-03-31 M. Amir Siddiq

This paper introduces an innovative physics-informed deep learning framework for metamodeling of nonlinear structural systems with scarce data. The basic concept is to incorporate physics knowledge (e.g., laws of physics, scientific…

Computational Engineering, Finance, and Science · Computer Science 2020-07-15 Ruiyang Zhang , Yang Liu , Hao Sun

We extend a phase-field/gradient damage formulation for cohesive fracture to the dynamic case. The model is characterized by a regularized fracture energy that is linear in the damage field, as well as non-polynomial degradation functions.…

Applied Physics · Physics 2019-03-27 Rudy J. M. Geelen , Yingjie Liu , Tianchen Hu , Michael R. Tupek , John E. Dolbow

As a nonlocal extension of continuum mechanics, peridynamics has been widely and effectively applied in different fields where discontinuities in the field variables arise from an initially continuous body. An important component of the…

Numerical Analysis · Mathematics 2021-09-22 Xiao Xu , Marta D'Elia , John T. Foster

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical…

We develop a tensorial constitutive model for dense, shear-thickening particle suspensions subjected to time-dependent flow. Our model combines a recently proposed evolution equation for the suspension microstructure in rate-independent…

Peridynamics (PD) represents a new approach for modelling fracture mechanics, where a continuum domain is modelled through particles connected via physical bonds. This formulation allows us to model crack initiation, propagation, branching…

Computational Engineering, Finance, and Science · Computer Science 2017-10-19 Gabriel Hattori , Jon Trevelyan , William M. Coombs

For more than 100 years, chemical, physical, and material scientists have proposed competing constitutive models to best characterize the behavior of natural and man-made materials in response to mechanical loading. Now, computer science…

Machine Learning · Computer Science 2022-11-23 Kevin Linka , Ellen Kuhl

We construct a homogeneous, nonlinear elastic constitutive law, that models aspects of the mechanical behavior of inhomogeneous fibrin networks. Fibers in such networks buckle when in compression. We model this as a loss of stiffness in…

Biological Physics · Physics 2015-12-18 Phoebus Rosakis , Jacob Notbohm , Guruswami Ravichandran