MechE-CSE Thesis Defense Announcement

MechE-CSE Thesis Defense Announcement

August 28, 2019, 2:00 PM

3-370

Mojtaba Forghani, MechE-CSE PhD Candidate

An inverse problem framework for reconstruction of phonon properties using solutions of the Boltzmann transport equation

By:      Mojtaba Forghani
Date:    August 28, 2019
Time:    2:00 pm
Location: 3-370

Abstract:

A methodology for reconstructing phonon properties in a solid material, such as the frequency-dependent relaxation time distribution, from thermal spectroscopy experimental results is proposed and extensively validated. The reconstruction is formulated as a non-convex optimization problem whose goal is to minimize the difference between the experimental results and the ones calculated by a Boltzmann transport equation (BTE)-based model of the experimental process, with the desired material property treated as the unknown in the optimization process. Crucially, the proposed approach makes no assumption of an underlying Fourier behavior, thus avoiding all approximations associated with that assumption.

The proposed method combines a derivative-free optimization method with a graduated (multi-stage) optimization framework. Our results show that, compared to other reconstruction methods, the proposed method is less sensitive to scarcity of data in a specific transport regime (such as sub-micron length scales). The method is also very versatile in incorporating known information into the optimization process, such as the known value of the material thermal conductivity or solid-solid interface conductance if a material interface is present; addition of this information improves the quality of the optimization.  In the presence of a material interface of unknown conductance, we show that simultaneous reconstruction of both the solid-solid interface frequency-dependent transmissivity function and the relaxation time function is possible.

The reliability and uniqueness of the optimized solution as well as its statistical properties due to the presence of noise are studied using a number of statistical techniques. Our analysis provides strong evidence that the formulated optimization problem has a unique solution; furthermore, the proposed optimization-based framework is capable of finding that solution with good accuracy.

PhD Thesis Committee:

Professor Nicolas G. Hadjiconstantinou (Chair and Thesis Supervisor),
Professor of Mechanical Engineering

Professor Gang Chen
Professor of Mechanical Engineering

Professor Youssef M. Marzouk
Associate Professor of Aeronautics and Astronautics

Title:  An inverse problem framework for reconstruction of phonon properties using solutions of the Boltzmann transport equation