News & EventsDepartment Events
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Mar10
EVENT DETAILS
Machine Learning Enabled Parametric Multiscale Modeling of Metals & Composites: From Fatigue Crack Nucleation to Damage Sensing
Professor Somnath Ghosh
Civil & Systems Engineering, Mechanical Engineering, and Materials Science & Engineering
Johns Hopkins University
The rapid surge of machine learning (ML) tools in developing efficient surrogate models for solving challenging problems has drawn significant attention from the Mechanics of Materials community. However, ML techniques rely on extensive training datasets and often lack physical interpretability. Also, exclusively data-driven models can result in ill-posed problems or non-physical solutions. Alternatively, the notion of ML-enhanced parametric upscaling has been introduced for multi-scale analysis of fatigue failure in metallics materials, damage and failure of unidirectional and woven composites, and damage sensing in multifunctional composites. The Parametrically Upscaled Constitutive Model (PUCM) for metallic materials like Ti alloys and the Parametrically Upscaled Continuum Damage Mechanics Model (PUCDM) for composites are thermodynamically-consistent constitutive models that bridge multiple spatial scales through the explicit representation of representative aggregated microstructural parameters (RAMPs), representing statistical distributions of morphological and crystallographic descriptors of the microstructure. ML tools, viz. genetic programming-based symbolic regression (GPSR) and artificial neural networks (ANN) are implemented for generating PUCM/PUCDM coefficients as functions of lower-scale RAMPs, using data sets of homogenized micromechanical response variables. For damage sensing in piezocomposite structures, the Parametrically Upscaled Coupled Constitutive Damage Model (PUCCDM) is developed coupling mechanical, damage, and electrical fields. An advanced machine learning model (ConvLSTM) based on the combination of a convolutional neural network and a recurrent neural network is developed to predict microstructural damage mechanisms from macroscopic electric signal and RAMPs. The computational tool chain outputs the highly efficient PUCM/PUCDM/PUCCDM, which are invaluable tools for multiscale analysis with implications in location-specific design.
TIME Monday, March 10, 2025 at 3:00 PM - 4:00 PM
LOCATION L211, Technological Institute map it
CONTACT Jeremy Wells jeremywells@northwestern.edu EMAIL
CALENDAR McCormick - Mechanical Engineering (ME)
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Mar15
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Winter Classes End
TIME Saturday, March 15, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar17
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Winter exams begin
TIME Monday, March 17, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar22
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Spring Break Begins
TIME Saturday, March 22, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Mar31
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Spring Break Ends
TIME Monday, March 31, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Apr1
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Spring Classes Begin - Northwestern Monday: Classes scheduled to meet on Mondays meet on this day.
TIME Tuesday, April 1, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar
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Jun15
EVENT DETAILSmore info
2024-2025 Commencement Ceremony
TIME Sunday, June 15, 2025
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar