Post-doctoral position at the University of Zaragoza, Spain
POST-DOCTORAL POSITION WITHIN THE PROJECT
"Physics-informed Artificial Intelligence for Cognitive Twins of Complex Systems"
Ph.D. positions in Computational Solid Mechanics at Worcester Polytechnic Institute
Fully funded Ph.D. positions in the area of computational mechanics are available in Dr. Yuan’s research group at the Aerospace Engineering Department at Worcester Polytechnic Institute.e
Mechanical couplings of 2D lattices uncovered by decoupled micropolar elasticity tensor and symmetry operation
We introduce a generalized methodology to uncover all mechanical couplings in 2D lattice geometries by obtaining the decoupled micropolar elasticity tensor. We also correlate the mechanical couplings with the point groups of 2D lattices by applying the symmetry operation to the decoupled micropolar elasticity tensor. The decoupled micropolar constitutive equation reveals eight mechanical coupling effects in planar solids, four of which are discovered for the first time in the mechanics' community.
Tenure-Track Faculty Position in Engineered Living Materials
The College of Engineering at Boston University has embarked on a bold new strategic plan that will pursue excellence and impact along convergent themes: (1) Intelligent, Autonomous and Secure Systems, (2) Synthetic Biology, Tissue Engineering and Mechanobiology, (3) Energy, Sustainability and Climate, (4) Materials by Design, (5) Photonics and Optical Systems, and (6) Neuroengineering, Neuroinformatics, and Neuroscience.
New webinar: Introduction of Composite Material Analysis Technology by Integrating Actual Testing and CAE
Join Synopsys Simpleware software, CYBERNET Multiscale.Sim, and Shimadzu Corporation for a webinar on Thursday, October 13th, 2022 on composite material analysis integrated actual testing and CAE.
Learn more and register here: https://register.gotowebinar.com/rt/204553566873541131?source=iMechanica
Problem-independent machine learning (PIML)-based topology optimization—A universal approach
Solving topology optimization problem is very computationally demanding especially when high resolution results are sought for. In the present work, a problem-independent machine learning (PIML) technique is proposed to reduce the computational time associated with finite element analysis (FEA) which constitutes the main bottleneck of the solution process.
Defect-based Physics-Informed Machine Learning Framework for Fatigue Prediction
I would like to draw your attention to our recently proposed predictive method based on a semi-empirical model (LEFM) and Neural Network, exploiting the Physics-informed Machine Learning concept. We show how the accuracy of state-of-the-art fatigue predictive models, based on defects present in materials, can be significantly boosted by accounting for additional morphological features via Physics-Informed Machine Learning.
Post-doctoral position
A post-doctoral position in the general area of material science and mechanics related to wire arc additive manufacturing (WAAM) is available in the Mechanical Engineering Department at Northeastern University, Boston, MA. The aim of the work is to investigate the thermomechanical causes of residual stresses and to assess the general build quality by experimental and modeling approaches. FLIR and other non-contact measurement techniques will be used for in-situ process monitoring. XRD will be used to assess residual stresses.
Delayed tensile instabilities of hydrogels
Jie Ma, Daochen Yin, Zhi Sheng, Jian Cheng, Zheng Jia*, Teng Li, Shaoxing Qu, Delayed Tensile Instabilities of Hydrogels, Journal of the Mechanics and Physics of Solids, 168, 105052 (2022)