Mechanical Engineering Department Faculty Candidate Seminar: John A. Moore

Monday, February 05, 2018
10:30 am to 11:50 am
Floor/Room #: 

Mechanical Engineering Department


John A. Moore

Monday, February 5, 2018

10:30 a.m. – 11:50 a.m.

Higgins Laboratories 102



Dr. John A. Moore graduated from the University of Washington with a bachelor’s degree in aeronautical and astronautical engineering and master’s degree in civil engineering. He was then employed as a structural analyst for Aerojet Rocketdyne working on NASA’s Orion program. Dr. Moore received his Ph.D. in mechanical engineering from Northwestern University in 2015 where he was a Predictive Science and Engineering Design Fellow. He completed his post-doctorate at Lawrence Livermore National Laboratory where he focused on additive manufactured materials and ductile fracture under extreme loads. He has collaborated with partners such as Goodyear Tire, Northwestern University’s Feinberg School of Medicine, and QuesTek Innovations. Dr. Moore’s work strives to better understand and improve engineering materials through computational modeling and to use this understanding to reduce heuristics and trial-and-error in engineering design. His work links topics in computational mechanics, materials science, engineering design, and high performance computing and has been applied to a broad range of problems in alloys, polymers, and biomedical devices.

Improving Materials Performance through Microstructure-Sensitive Modeling

Research Presentation Abstract

                Materials drive technology. Steel enabled the skyscraper; silicon enabled modern electronics; and lithium ion batteries put computers in our pockets. Structural materials, specifically, are in a period of flux where many industries are manufacturing new materials in-house via 3D printing. These new materials’ properties can vary inside a single component due to process-induced gradations in microstructural features, and the question arises of how to understand, predict, and ultimately control the effects of these features. This question is addressed through microstructure-sensitive modeling and will be explored in the context of several emerging research directions. Highlighted topics will include: the effects of surface roughness on fatigue strength in 3D printed/additive manufacturing (AM) alloys, the effects of laser path on impact strength anisotropy in AM Ti-6Al-4V, and development of new, more robust fatigue indicator parameters using modeling microscopy and modeling. Emphasis is given to experimentally informed computational crystal plasticity models, homogenized materials models, and applications to fatigue and high strain-rate failures. Ongoing work in homogenization research-based material models for application in engineering design, as well as a top-down approach to materials databases are also discussed. These examples illustrate the utility of microstructure-sensitive modeling for improving manufacturing, materials development, and engineering design with applications ranging from biomedical devices to consumer goods.

A Scaffolded, Functional Repetition Approach to Engineering Education

Teaching Presentation Abstract

Engineering is an applied science. Accordingly, my teaching approach focuses on application. Practicing engineers master topics by repeated application in increasingly complex functional situations. My teaching emphasizes projects and challenging homework sets, using exams only to test core competency. This presentation will emphasize how I apply functional repetition and graduated scaffolding to materials and mechanics courses on both the undergraduate and graduate level. Examples of how I balance traditional teaching methods with modern teaching techniques, such as “flipped classrooms”, “progressive projects”, and “students-teaching-students” are given in the context of existing Worcester Polytechnic Institute courses. This presentation will also highlight a new graduate level course linking topics of materials science and mechanical engineering.