Blog posts

Three-day on-site intensive course on "Invitation to nondestructive evaluation and structural health monitoring" by Zahra Sharif Khodaei, 22--24 May 2023, Czech Republic, Prague

Submitted by jenda_z on Sat, 04/22/2023 - 16:47

Composites materials; Modeling; Testing; Structural Health Monitoring

I would like to bring to your attention an intensive three-day course on "Invitation to nondestructive evaluation and structural health monitoring" that will be given by Dr. Zahra Sharif Khodaei (Imperial College London) from Monday, 22 May, to Wednesday, 24 May 2023, at the Faculty of Civil Engineering, Czech Technical University in Prague.

Mechanisms of nucleation and defect growth in undercooled melt containing oxide clusters

Submitted by mohsenzaeem on Fri, 04/21/2023 - 15:43

research

Solidification; Oxides; Molecular dynamics

Dear iMechanica colleagues; I am happy to share with you our recent paper that is just published in Acta Materialia, it is open access:

S. Kavousi and M. Asle Zaeem. Mechanisms of nucleation and defect growth in undercooled melt containing oxide clusters. Acta Materialia 252 (2023) 118942 (12 pages).

SES 2023 mini-symposium: Multiscale Modeling of Phase Transformation in Materials

Submitted by Kmomeni on Fri, 04/21/2023 - 09:32

conference

We would like to invite you to present your work at our mini-symposium titled "Multiscale Modeling of Phase Transformation in Materials" at the 2023 annual Society of Engineering Sciences (SES) meeting.

A funded Ph.D. position at University of Alabama on Multiscale Modeling of Materials

Submitted by Kmomeni on Fri, 04/21/2023 - 09:20

job

#Job #PhD #Computational mechanics

One fully supported Ph.D. position is open immediately in Advanced Hierarchical Materials by Design Lab at the University of Alabama on multiscale modeling of materials and processes. The goal of this research project is to use machine learning algorithms to design materials and their synthesis process.

KTH Summer School: Computational Biomechanics. From in-vitro experiment to damage and failure analysis

Submitted by tcg on Thu, 04/20/2023 - 13:18

the program is out now!!

Cutting a material

Submitted by davoud1983 on Wed, 04/19/2023 - 12:33

research

what are the main material properties a substrate should have if you want to be able to cut through it nicely and have a clean cut? I know a little bit about cutting tools but not much about the substrate?

PhD course - "Probability-Informed Wind Engineering against Synoptic and Non-Synoptic Wind Hazards", Prof. Luca Caracoglia (UniGe Visiting Prof)

Submitted by Giuseppe Piccardo on Tue, 04/18/2023 - 12:14

It is with great pleasure that I announce that from mid-May
Prof. Luca Caracoglia (Northeastern University, Boston MA, USA)
will be UniGe Visiting Professor.

During the visiting period, starting from 17 May, Prof. Caracoglia will hold a PhD course entitled
"Probability-Informed Wind Engineering against Synoptic and Non-Synoptic Wind Hazards".
All information is contained in the attached file.

Those interested in participating are invited to write to me.
Thank you very much for the attention,
kindest regards
Giuseppe Piccardo

Post-Doctoral Position in Biomechanics, Boston University

Submitted by yanhang on Tue, 04/18/2023 - 03:51

research

A postdoctoral research position is available in Dr. Katherine Yanhang Zhang’s Multi-Scale Tissue Biomechanics Lab in the Mechanical Engineering Department at Boston University.

Data-Driven State of Health Estimation for Lithium-Ion Batteries Based on Universal Feature Selection

Submitted by zhan-sheng guo on Tue, 04/18/2023 - 01:11

A simple yet effective health indicator (HI)-based data-driven model forecasting the state of health (SOH) of lithium-ion batteries (LIBs) and thus enabling their efficient management is developed. Five HIs with high physical significance and predictive power extracted from voltage, current, and temperature profiles are used as model inputs. The generalizability and robustness of the proposed ridge regression–based linear regularization model are assessed using three NASA datasets containing information on the behavior of batteries over a wide range of temperatures and discharge rates.