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multiscale modeling

WCCM 2024: Minisymposium Numerical modelling of composite materials and structures

Submitted by GEStavroulakis on

Call for papers

 
 
Dear colleague, 
 

We warmly invite you to submit an Abstract to the mini symposium: Numerical modelling of Composite Materials and Structures (1004) 

Multiscale deep learning for woven composites

Submitted by Mirkhalaf on

Woven composites exhibit a complex hierarchical structure with multiple heterogeneous sub-scales, stemming from microscale fiber arrangements and mesoscale interlacing patterns, necessitating sophisticated modeling approaches to accurately capture their intricate multiscale nature.

Opening for a Ph.D. student at the University of Wyoming for Fall 2023: multiscale modeling of heterogeneous materials under inelastic deformation and damage

Submitted by xiangzhang on

The Computations for Advanced Materials and Manufacturing Laboratory (CAMML) in the College of Engineering and Physical Science at the University of Wyoming has an opening for a Ph.D. student for Fall 2023, in the area of multiscale modeling of heterogeneous materials under inelastic deformation and damage. 

Several PhD positions available at Vanderbilt University

Submitted by Caglar Oskay on

 

We are seeking several doctoral students to join the Multiscale Computational Mechanics Laboratory (MCML) at Vanderbilt University beginning either Spring 2023 or Fall 2023. The two broad research areas are briefly described below. Candidates must also have a strong general interest (prior experience is a plus) in computational mathematics, mechanics, modeling and simulation and computer programming.

 

The specific research areas as follows:

 

PhD Position in Multiscale Brain Injury Modelling at KTH-Stockholm

Submitted by Xiaogai Li on

One PhD Student position in Multiscale brain injury modeling for 4-5 years; expected from March 1, 2021 or according to agreement at KTH Royal Institute of Technology in Stockholm, Sweden.

Eligibility: have basic studies at the MSc level in medical engineering, bio mechanics, engineering physics, mechanical engineering, or the like; Requirements for English equivalent to English B/6.

New article on inelastic homogenization through machine learning

Submitted by Julian J. Rimoli on

I would like to share another article from my group just published in CMAME. I think this is an interesting approach towards the automatic generation of constitutive laws for arbitrary microstructures:

https://authors.elsevier.com/a/1bxlSAQEIt1ls

The article focuses on how to systematically create constitutive laws using only:

1) Available microstructural models

2) Machine learning techniques