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12-21 Instabilities in Solids and Structures symposium at IMECE 2023

Submitted by Stavros Gaitanaros on

Dear colleagues,

We, the AMD IiSS Technical Committee organizers, are pleased to continue our long-standing tradition of arranging a symposium on "Instabilities in Solids and Structures" at the annual ASME-International Mechanical Engineering Congress and Exposition (IMECE).  The Congress this year will be held in New Orleans, LA during the period of October 29-November 2, 2023

The "Presentation Only" abstract submission deadline this year is June 23, 2023.

Postdoc Position | Mechanics of Slender Structures | EPFL | Switzerland

Submitted by Pedro Reis on

We're excited to share the news that we have a Postdoc opening in our fleXLab (Flexible Structures Laboratory) at EPFL in Switzerland. This position is focused on the mechanics of slender structures. We appreciate the unique perspectives that individual research interests bring, so we'll work to align the specifics of the research project with the successful candidate's interests.

Technical Write-up: Identifying unknown material properties using reverse engineering by combining materials databases and artificial intelligence

Submitted by Chandima Uyanage on

An article published in the latest edition of Futurities - Simulation-Based Engineering & Sciences Magazine, discusses in detail about using Virtual Material Testing and AI to predict the material properties of complex microstructures that are difficult to measure in practice.

Journal Club for June 2023: A perspective on the role of machine learning in constitutive modeling and computational mechanics

Submitted by nbouklas on


Introduction


The purpose of this blog post is to briefly outline a perspective on the emerging opportunities and challenges that arise as the field of Machine Learning (ML) is quickly driving the development of tools that are becoming mainstream in the study of solid mechanics and computational mechanics, with a focus on constitutive modeling. By no means is this a complete review of ML-enabled constitutive modeling.



Background on Scientific Machine Learning (SciML)

A joint #PhD with IIT Ropar and IIT Mandi on Mechanical characterization of discontinuities in material's microstructure

Submitted by hermatician on

#Apply for a joint #PhD with IIT Ropar and IIT Mandi on "Mechanical characterization of discontinuities in material's microstructure "
The brief description is given below.

Opening for Post-Doctoral Associate in Machine Learning for Computational Mechanics

Submitted by rbsills on

The microMechanics of Deformation Research Group (mMOD) in the Department of Materials Science and Engineering at Rutgers University is seeking a Post-Doctoral Associate to perform research as part of an NSF CAREER award project aimed at understanding the fundamentals of fracture in metals. Research tasks will include the development of a machine learning framework for training surrogate models which couples with the finite element method and analyzing large atomistic simulation datasets.

Post-Doc position at MSU - Multi-axis vibrations

Submitted by joodaky on

We are currently seeking a highly motivated candidate for a Post-Doc position in the School of Packaging at MSU. The focus of this position will be on studying the multi-axis vibrations experienced by packages during transportation. This research will involve utilizing various tools and techniques such as a multi-axis shaker, acceleration sled, FEM simulations, nonlinear models, and more. To be considered for this position, the ideal candidate should possess the following qualifications:

Universal Displacements in Inextensible Fiber-Reinforced Linear Elastic Solids

Submitted by arash_yavari on

For a given class of materials, universal displacements are those displacements that can be maintained for any member of the class by applying only boundary tractions. In this paper we study universal displacements in compressible anisotropic linear elastic solids reinforced by a family of inextensible fibers. For each symmetry class and for a uniform distribution of straight fibers respecting the corresponding symmetry we characterize the respective universal displacements. A goal of this paper is to investigate how an internal constraint affects the set of universal displacements.