Welcome to the Computational Mechanics of Materials Laboratory at Marquette University. Our overarching goal is to understand, predict and improve materials performance through advancements in materials modeling.
Materials drive technology; however, improving modern structural materials is a formattable challenge involving sophisticated techniques, beyond the Edisonian (trail-and-error) approach. Our work strives to use computational modeling to understand the connection between materials microstructure and their properties, build tools to predict materials performance in environments that are difficult to access experimentally, and ultimately transfer this knowledge to materials and product designers.
PhD student Jacob Rusch recently presented his work Modeling Transformation Ratcheting of Nitinol Using Computational Crystal Plasticity at the 16th US National Congress on Computational Mechanics
What is the best porosity model? Our new paper in International Journal of Fracture explores this question.
New Research Experiences for Undergraduates grant funded by the National Science Foundation to explore the role parallel computing can play in determining the driving force for fatigue crack nucleation in a superelastic nickel titanium shape memory alloy
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Crystal plasticity model of an FCC metal microstructure
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Spall failure of an experimentally-measured copper microstructure
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Dislocation evolution in Ti-6Al-4V α and β phases
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Fatigue fracture prediction for a Nickel-Titanium Alloy
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Impact simulation using a multiscale material degradation model
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Multiscale fatigue life prediction in biomedical stent surrogate
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Multiscale model of a filled polymer microstructure