IE/EE Seminar with Erick C. Jones

Our next seminar will be held jointly with the Electrical Engineering Department. Our next presenter will be Erick C. Jones, a PhD candidate at The University of Texas at Austin.

All students, faculty, and staff are welcomed to attend.

Title: Multi-Systems Optimization: Equitably Aligning Generation and Demand

Presenter: Erick C. Jones

Date: March 8, 2021

Time: 1:15pm – 2:15pm

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Abstract: Modern life depends on cheap and reliable energy. The energy system powers just about every other major sector including buildings, transportation, food systems, and water systems. However, the energy production process produces large amounts of pollution and greenhouse gases, most of the energy it does produce is wasted, and the negative externalities cascade to other systems. Furthermore, the environmental concerns, inefficiencies, and adjacent system effects have the largest impacts on the most vulnerable. Those of us who are housed in areas with higher air pollution, have less efficient homes and cars, and as a result spend more of their income on energy while getting less out of it. New technologies and the purposeful integration of energy with other sectors via systems of systems engineering techniques can address some of these issues. The goal of this work is to advance research related to multi-systems optimization by examining possible interdependencies between the energy sector and other systems that encourages clean energy adoption by aligning the flexible loads of those systems with the intermittent supply of renewables and investigating if that minimizes an individual or a community’s barrier of entry into the clean energy space.

Bio: Erick Jones is a Ph.D. Candidate in Operations Research and Industrial Engineering at the University of Texas at Austin. He received a B.S. in Chemical Engineering with a minor in Petroleum Engineering from Texas A&M University. As an undergraduate, Erick researched growth mechanisms of single-walled carbon nanotubes. From there, he spent several years working in the design, manufacturing, oil and gas, and HVAC industries. These experiences motivated Erick to pursue research that can enhance quality of life by improving access to sustainable resources, particularly where a lack of physical infrastructure or economic resources presents a major obstacle. In his research, Erick develops integrated assessment tools to analyze how energy systems, water resources, supply chains, urban space, and transportation networks operate in concert to influence economic and environmental well-being. Since Fall 2019, Erick has been an NRT Fellow in the NSF Research Traineeship program on food-energy-water systems at UT and in the Summer of 2020 received the Mickey Leland Energy Fellowship from the Department of Energy’s Office of Fossil Energy to support his research with Los Alamos National Laboratory on the SimCCS tool for CCS infrastructure optimization. Erick also participates in education and outreach activities through the Planet Texas 2050 initiative, INFORMS, GEC, and Science in Residence, which encourages K-12 students to think about climate change and other STEM issues. 

Dr. Xin Liu to present seminar

Title: Integrating Multiscale Modeling and Machine Learning – Design, Analysis and Manufacturing of Advanced Materials and Structures

Presenter: Dr. Xin Liu

Date: February 22, 2021

Time: 1:15 pm-2:15 pm

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Abstract: The superior performances of advanced materials and structures are mainly achieved through engineering the microstructure at different scales. This seminar will introduce a novel physics-based data-driven multiscale modeling approach to connecting the microstructures to the material properties and structural performances. The first part of this seminar will introduce the basic idea of the multiscale modeling method called mechanics of structure genome (MSG) and its application to textile composite structures. The accuracy and efficiency of the MSG models will be demonstrated by comparing with conventional finite element models. Moreover, the neural network models were trained to further accelerate the multiscale modeling. The second part of the seminar will introduce the on-going research of developing multiscale and multiphysics models to predict the process-structure-property-performance relation. The multiscale modeling was carried out to predict the effective thermal conductivity. In addition, a two-step homogenization approach was developed to enable in-situ monitoring and performance prediction considering the manufacturing-induced geometry imperfections. The developed approach can be used for the in-process decision making for additively manufactured materials with complex geometry shapes (e.g., metamaterials).

Bio: Dr. Xin Liu is an Assistant Professor in the Industrial, Manufacturing, & Systems Engineering Department at UTA. He is also a member in the Institute for Predictive Performance Methodologies at UTA Research Institute. Dr. Liu obtained his PhD in 2020 and Master of Engineering in 2016 from Purdue University in Aeronautical and Astronautical Engineering. His expertise is in data-driven multiscale modeling of composite materials and structures. He has authored/co-authored 20+ journal papers and refereed conference papers. He also developed 3 computer codes for multiscale modeling of composites.  He received the American Society for Composites (ASC) Ph.D. Research Scholarship Award in 2018.