Computational mechanics / thermoplastic composites / inverse problems
Joseph Kirchhoff
I develop experimental and computational methods for reliable, energy-efficient manufacturing of advanced thermoplastic composites.
My research connects process physics, full-field measurements, and scalable inverse methods to turn laboratory observations into predictive manufacturing tools.
I am a Ph.D. student in the Walker Department of Mechanical Engineering at UT Austin, co-advised by Prof. Omar Ghattas and Prof. Mehran Tehrani, and affiliated with the Oden Institute for Computational Engineering and Sciences. My research is supported by a NASA NSTGRO Fellowship.
Research focus
Mechanics-informed tools for composite manufacturing.
Understanding fusion bonding, crystallization, and sub-melt consolidation so high-rate manufacturing can move from promising to certifiable.
02 / computation Inverse problems and digital twinsRecovering full-field material properties from indirect measurements with PDE-constrained optimization and function-space regularization.
03 / research outputs Measurement to decision supportCombining experiments, mechanics models, and uncertainty-aware inference to support process monitoring, qualification, and design decisions.
Method
Experiments, models, and inference in the same loop.
I work on problems where material behavior, manufacturing constraints, and numerical methods have to be treated together. The goal is practical: build models that are physically interpretable, computationally scalable, and useful in real processing environments.
In the news
Research stories from UT Austin.
Selected outputs
