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USACM Virtual Seminar Series this Summer

Submitted by John E. Dolbow on

The USACM has established a virtual seminar series that will run for six weeks over the course of this summer.  Exact dates and times will vary each week, but a full listing of the speakers is available here:

https://www.usacm.org/seminar-series

The series features young computational mechanicians from across the US.  The talks are an opportunity for these young scientists to showcase their research activities during a period in which so many conferences and meetings are being cancelled or postponed.  

Generalised boundary conditions for hydrogen transport at crack tips

Submitted by Emilio Martíne… on

Dear iMechanicians,

I hope the present work is of interest to you. We present a new formulation for resolving the electrochemical-diffusion interface in hydrogen embrittlement modelling 

E. Martínez-Pañeda, A. Díaz, L. Wright, A. Turnbull

Generalised boundary conditions for hydrogen transport at crack tips

Corrosion Science 173, 108698 (2020)

https://www.sciencedirect.com/science/article/pii/S0010938X20305345

EML Webinar by Prof. Robert Wood on June 3, 2020: The Mechanical Side of Artificial Intelligence

Submitted by Teng Li on

EML Webinar on June 3, 2020 will be given by Prof. Rob Wood at Harvard University via Zoom meeting. Discussion leader: Rob Howe, Harvard.

Title: The mechanical side of artificial intelligence

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

Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane

Submitted by Luca-Deseri on

Carotenuto A., Lunghi L., Piccolo V., Babaei M., Dayal K., Pugno N. M., Zingales M., Deseri L.*, Fraldi M. Mechanobiology predicts raft formations triggered by ligand-receptor activity across the cell membrane, Journal of the Mechanics and Physics of Solids 141 (2020) 103974 https://doi.org/10.1016/j.jmps.2020.103974
*Corresponding Author

SciANN: Scientific computations and physics-informed deep learning using artificial neural networks

Submitted by haghighat on

Interested in deep learning, scientific computations, solution, and inversion methods for PDE? 

Check out the preprint at: 

https://www.researchgate.net/publication/341478559_SciANN_A_Keras_wrapp…

 

 

Some problems are shared in our GitHub repository on how to use sciann for inversion and forward solution of: