05/26/2022
By Sokny Long
The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Weidi Wang on “Reduced Order Modeling and Design of 3D Printable Mechanical Metamaterials.”
Doctoral Student: Weidi Wang
Proposal Defense Date: Wednesday June 8, 2022
Time: 12:30 - 1:30 p.m. EST
Location: Southwick 240 and virtual via Microsoft Teams
All interested students and faculty members are invited to attend the defense in person or via remote online access. Those interested in attending should contact the student (Weidi_Wang@student.uml.edu) and committee advisor (Alireza_Amirkhizi@uml.edu) at least 24 hours prior to the defense to request access to the meeting.
Committee:
Advisor, Alireza Amirkhizi, Associate Professor, Mechanical Engineering, UMass Lowell
Christopher Hansen, Associate Professor, Mechanical Engineering, UMass Lowell
Scott Stapleton, Associate Professor, Mechanical Engineering, UMass Lowell
Thomas Plaisted, Materials Engineer, CCDC Army Research Laboratory,
Ankit Srivastava, Associate Professor, Department of Mechanical, Materials, and Aerospace Engineering,
Illinois Institute of Technology
Abstract:
Mechanical metamaterials (MMs) are artificial media primarily composed of periodic micro-structures, designed for manipulating the propagation and distribution of stress and deformation. This proposal focuses on the dynamic behavior of MMs and utilizes reduced order models (ROMs) to investigate the exotic properties of MMs, reduce the computational effort, and further facilitate design optimizations. The ROM is a discrete yet analytical representation of the continuum system, developed based on beam theories and optimization methods. With accurate reproduction of eigen-analysis results, the ROM effectively preserves the salient physics of the continuum unit cell in a parameterized fashion. Physical phenomena such as band gaps, level repulsion, and exceptional points are investigated through the discrete setups. Modeling the MMs often involves extensive computational efforts due to their geometric complexity. The reduced order representation, with small-sized matrices, enables fast computation of large finite arrays under dynamical loading, leading to a significant saving of computational effort. The low-cost nature of ROM is particularly suitable for iterative design optimization and allows for exploration in a vast design space. In light of machine learning techniques, a systematic design approach using the ROM method will be developed to achieve desired functionalities. The deepened physical understanding and accelerated computational tools are utilized for developing practical metamaterial applications. The wave attenuation functionality highlights the band gap nature of metamaterials and is validated in shaker experiments. Other uncharted applications such as impact protection and source localization will be developed and demonstrated numerically. The proposed study presents an efficient modeling/design tool set and will help exploit novel technological opportunities based on mechanical metamaterials.
All interested students and faculty members are invited to attend the defense via remote online access.