Damage Mechanics Challenge
In February 2019, a workshop was held at Purdue University to gather computational scientists and experimentalists to define and launch a numerical challenge to predict damage evolution and signatures of failure in rock. At the workshop, participants
(1) presented their computational approach for numerical simulation of damage;
(2) participated in the design of a challenge problem that will be compared to laboratory experimental data on samples designed through additive manufacturing methods (e.g. 3D printing) to fail in controlled ways and with increasing complexity;
(3) defined repeatable and unbiased metrics to quantitatively assess and measure the quality of the theoretical and data-driven models, given the significant influence of inherent uncertainty and variability on the onset and modes of failures.
The challenge is now open. The details of the challenge, how to obtain calibration data and how to submit results to the competition can be found at
12/01/2021– Benchmark dataset and challenge information posted on website listed above.
1/15/2022 – Online Forum (11 AM EST - New York City Time) with challenge hosts to address questions (to register for the forum please send an email to Laura Pyrak-Nolte email@example.com). If you can't attend the forum, please email questions to Laura Pyrak-Nolte. A recording of the forum and a list of questions is posted on Question & Answer page.
4/15/2022 – Abstract submission for workshop (On Comparison to Calibration Data Set)
5/15/2022 – Submission of results by participants
6/25/2022 – Workshop where calibration data and participants solutions are compared (Hybrid Workshop)
Abstracts of 250-500 words, in English, can be submitted to your challenge account. Abstracts should include a brief description of the numerical method, results and other comments on your results. Workshop Fee: $75 and students are free.
New: 12/12 - 12/16/2022 - Plan to hold a session at the 2022 Annual Fall Meeting of the Geophysical Union to reveal the results of the code comparison to challenge data set and to have participants present their findings.
Laura J. Pyrak-Nolte, Purdue University
Antonio Bobet, Purdue University
Hongkyu Yoon, Sandia National Laboratories
Liyang Jiang, Purdue University
Joseph P. Morris, Lawrence Livermore National Laboratory
Acknowledgment: Office of the Provost and the Office of the Executive Vice President for Research and Partnerships, Purdue University; National Science Foundation CMMI 1932312.