Yan, Zhu place second in NIST AM-Bench challenges
9/27/2022 10:00:28 AM
Assistant professor Jinhui Yan and Ph.D. student Qiming Zhu placed second in two challenges in the 2022 National Institute of Standards and Technology (NIST) Additive Manufacturing Benchmark (2022 AM-Bench) Modeling Challenges. According to NIST, “AM-Bench provides a continuing series of controlled benchmark measurements, in conjunction with a conference series, with the primary goal of enabling modelers to test their simulations against rigorous, highly controlled additive manufacturing benchmark test data.”
The 2022 event included participants from universities, laboratories and companies around the world, with 138 submissions entered for consideration. Yan and Zhu won second place for:
- Modeling results predicting the time-dependent absorption during laser spot welding; and
- Modeling results predicting the melt pool geometry for a scanned laser weld.
Awards were presented during the AM-Bench 2022 awards ceremony held on August 17, 2022 at the AM Bench 2022 conference in Bethesda, Md.
Predicting keyhole instability, pore formation and energy absorption rate.
Yan joined the CEE at Illinois faculty in 2018. He and his students broadly work on computational mechanics and their applications. In particular, they develop novel physics-based and data-driven computational multi-physics methods to overcome the grand challenges in additive manufacturing technologies. See Yan’s profile page for more information, including recent publications.