William Musinski
University of Wisconsin-Milwaukee, WI·Materials Science·Early-career
Metal parts in cars, power plants and medical devices can fail after being loaded over and over again, a process called fatigue. Fatigue failure starts with tiny cracks that form and grow inside the metal at the scale of its individual crystals, or grains.
- Fields
Materials Science
Engineering
- Topics
fatigue
crack initiation
microstructure
- Grants
- 1 known grant, through Jul 2031
What they work on
- Measure strains inside grains, dislocation substructures and grain boundary interactions before and during fatigue cracking, using synchrotron high-energy X-ray diffraction, which sees inside metals as they deform, together with high-resolution microscopy.
- Develop crystal plasticity finite element models, simulations of how individual metal crystals deform, that include substructure formation, grain boundary interactions and changing direction-dependent hardening, and validate them against the X-ray data.
- Create reduced-order modeling strategies that keep the models sensitive to microstructure while greatly lowering their computational cost for fatigue prediction.
- Train machine learning frameworks to predict fatigue-relevant fields and crack-initiation measures from grain arrangement and loading. Use uncertainty quantification to test how reliable the predictions are and how well they transfer across several fcc alloys.
More about the research
Engineers still cannot reliably predict where these cracks will start, how fast they will grow, or why. Better predictions could lead to safer, longer-lasting and more efficient metals for transportation, manufacturing, energy and health.
Why it matters
Predicting where and when fatigue cracks start could help engineers design metals that last longer and fail less often. This matters for parts used in transportation, manufacturing, energy and health. A fast, microstructure-aware prediction framework could cut costly testing and guide the design of more reliable alloys.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Jaime Marian
University of California-Los Angeles, CA·Materials Science
Determine how 'necklace' microstructures nucleate at grain boundaries during dynamic recrystallization in body-centered-cubic refractory multi-principal element alloys, using mesoscale modeling.
Yong Gan
California State Polytechnic University-Pomona, CA·Engineering
Develop an energy dissipation criterion, a measure of energy lost as damage grows, to evaluate thermomechanical fatigue in semiconductor/metal interfaces under cyclic thermal and mechanical loading.
Sougata Roy
Iowa State University, IA·Materials Science·Early-career
Reveal how solidification cracks start and grow in aluminum printed by laser directed energy deposition (L-DED), and how large cracks relate to pores in deposited parts.
The school
University of Wisconsin-Milwaukee: 2 labs on PI Pages, $66M a year on research, 162 research doctorates a year.
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