Journal Club for May 2021: Strong and tough hydrogels with hierarchical architectures
Mutian Hua, Shuwang Wu, Ximin He
Bioinspired Soft Materials Group
University of California, Los Angeles
Introduction
research
Exact imposition of boundary conditions in physics-informed neural networks
We recently proposed a method that uses distance fields to exactly impose boundary conditions in physics-informed neural networks (PINN). This contribution is available as an arXiv preprint.
Quantitative prediction of rapid solidification by integrated atomistic and phase-field modeling
Dear iMechanica colleagues, I am pleased to share with you our newest paper on qauntitative prediction of rapid solidification. S. Kavousi, B. Novak, D. Moldovan, and M. Asle Zaeem. Quantitative prediction of rapid solidification by integrated atomistic and phase-field modeling. Acta Materialia 211 (2021) 116885 (12 pages).
Abstarct
Postdoctoral Associate Position in the area of machine learning for solid-state batteries
Our team led by Professor Tomasz Wierzbicki at MIT Mechanical Engineering is looking for a highly motivated Postdoctoral Associate in the area of machine learning for solid-state batteries. The candidate is expected to develop machine-learning-based computational tools for the characterization of the interfacial failure in Li-metal all-solid-state batteries. Candidates who have experience in physics-informed machine learning, computational and solid mechanics, multiphysics modeling, and all-solid-state batteries are encouraged to apply by sending a CV to Dr.
Webinar: Efficient High-Fidelity Design and Optimization of Composite Blades/Wings Using VABS
On April 27th we will present a webinar hosted by our partner @Altair where we will share efficient high-fidelity design and optimization of composite blades using VABS. Register now at https://bit.ly/3gnQJAN
Implementation of Abaqus user subroutines and plugin for thermal analysis of powder-bed electron-beam-melting additive manufacturing process
Electron beam melting (EBM) is a metal powder bed fusion additive manufacturing (AM) technology that is widely used for making three-dimensional (3D) objects by adding materials layer by layer. EBM is a very complex thermal process which involves several physical phenomena such as moving heat source, material state change, and material deposition. Conventionally, these phenomena are implemented using in-house codes or embedding some user subroutines in commonly used commercial software packages, like Abaqus, which generally requires considerable expertise.
Energy absorption mechanisms of nanoscopic multilayer structures under ballistic impact loading
Our latest article on the ballistic performance of polymer/metal nanostructures is freely available for 50 days from today: https://authors.elsevier.com/a/1cy9c3In-urcWx
Global Composites Experts Webinar by Dr. R. Byron Pipes
cdmHUB invites you to attend the Global Composites Experts Webinar Series.
Title: Rheology of Carbon Fiber Thermoplastic Polymer Composites
Speaker: Dr. R. Byron Pipes
Time: 4/22, 11AM-12PM EST.
Please go to https://www.purdue.edu/cmsc/events/2020-webinars/ to register for this webinar.
Atomic-Scale Investigation on the Mechanical Behavior of Ultrathin Multilayers Under Shock Loading
Recent advances in microprojectile impact tests have opened a new route to explore the behaviors of nanomaterials under extreme dynamic conditions. For example, impact tests have revealed that the specific penetration energies of ultrathin polymer films are remarkably high compared to the energies of conventional protective materials. The current experimental techniques are, however, unable to elucidate some of the complex atomistic mechanisms associated with the penetration process, which can only be realized through atomistic simulations.