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Numerical and experimental analysis of the bi-stable state for frictional continuous system

Submitted by Antonio Papangelo on
research
Contact mechanics; Adhesion; Friction; Tribology; Wear; Surface Cracking

Friction induced vibrations are a very well known problem in engineering applications. Sometimes they are referred to be unpredictable, intermittent, capricious (!!!) and particularly experimentalists know this very well. Here, by means of numerical simulations and experimental measurements, we highlight how capriciousness may arise from the multistable behavior of frictional systems, i.e. their characteristic to show multiple stable solutions for the same set of governing parameters. Hence initial conditions and perturbations become crucial.

How contact area decreases under shear load in soft bodies?

Submitted by Antonio Papangelo on
research
adhesion; contact mechanics; bioinspired adhesion; nanolayers; microlayers

A very good paper has just been published in JMPS by  J.C. Mergel, J. Scheibert, R.A. Sauer "Contact with coupled adhesion and friction: Computational framework, applications, and new insights". it shows the results of numerical simulations with soft bodies sheared by a tangential force. There is a vivacious discussion in Literature if the contact area reduces due to adhesion or due to large deformation.

Invitation to attend Mr. Ran Tao PhD defense at COHMAS lab, KAUST.

Submitted by Ahmed wagih on
research
Structural Adhesive Bonding

 

Title:

Enhancing the bonding of CFRP adhesive bonding through laser-based surface preperation sterategies.

Abstract:

Carbon Fiber-Reinforced Polymers (CFRPs) have been widely applied in the aerospace and automotive industries to achieve unprecedented weight reductions. However, major challenges need to be solved in order to exploit their full potential, especially in the design of full composite primary structure, making then a vital part of the mobility and energy revolution.

A finite element formuation for a direct approach to elastoplasticity in special Cosserat rods

Submitted by Ajeet Kumar on
research
Elastoplastic deformation
Cosserat rod
Finite Element Method

A finite element formulation is presented for a direct approach to model elastoplastic deformation in slender bodies using the special Cosserat rod theory. The direct theory has additional plastic strain and hardening variables, which are functions of just the rod's arc-length, to account for plastic deformation of the rod. Furthermore, the theory assumes the existence of an effective yield function in terms of stress resultants, i.e., force and moment in the cross-section and cross-section averaged hardening parameters.

EML Webinar on October 28, 2020 on Multi-scale and Trans-scale Analysis in Particle-laden Turbulence

Submitted by Teng Li on
research
EML Webinar
EML

EML Webinar on 28 October 2020 will be given by Prof. Xiaojing Zheng, Lanzhou University. Discussion leader: Prof. Yujie Wei, Institute of Mechanics, Chinese Academy of Sciences.

Title: Multi-scale and Trans-scale Analysis in Particle-laden Turbulence

Time: 7 am California, 10 am Boston, 3 pm London, 10 pm Beijing on 28 October 2020

Global Composites Experts Webinar by Kevin Potter

Submitted by Wenbin Yu on
research
cdmHUB
Global Composites Experts Webinar

Title: Automating the lay-up of geometrically complex composite structures made from preimpregnated reinforcements: a route to a roadmap

Speaker: Dr. Kevin Potter

Time: 10/29, 11AM-12PM EST.

Please go to https://www.purdue.edu/cmsc/events/2020-webinars/ to register for this talk.

 

EML Webinar on October 14, 2020: Fluid dynamics of speech: Mechanisms underlying pathogen transmission

Submitted by Teng Li on
research
EML Webinar
EML

 

EML Webinar on 14 October 2020 will be given by Prof. Howard Stone, Princeton University; Manouk Abkarian and Simon Mendez, CNRS, France.

Title: Fluid dynamics of speech: Mechanisms underlying pathogen transmission

A predictive deep-learning approach for homogenization of auxetic kirigami metamaterials with randomly oriented cuts

Submitted by Jinxiong Zhou on
research
deep learning; kirigami

This paper describes a data-driven approach to predict mechanical properties of auxetic kirigami metamaterials with randomly oriented cuts. The finite element method (FEM)was used to generate datasets, the convolutional neural network (CNN) was introduced to train these data, and an implicit mapping between the input orientations of cuts and the output Young’s modulus and Poisson’s ratio of the kirigami sheets was established. With this input–output relationship in hand, a quick estimation of auxetic behavior of kirigami metamaterials is straightforward.

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