Big Data, Machine Learning and Artificial Intelligence for CO 2 Management, Fuel Flexibility and Fire Safety

Jay Gore

Vincent P. Reilly Professor of Mechanical Engineering
Purdue University

Seminar Information

Seminar Series
Energy: Joint Mechanical & Aerospace Engineering Dept & Center for Energy Research

Seminar Date - Time
May 4, 2022, 11:00 am
-
12:15

Seminar Location
Hybrid: In Person & Zoom (connection in link below)

Engineering Building Unit 2 (EBU2)
Room 584

Seminar Recording Available: Please contact seminar coordinator, Jake Blair at (j1blair@eng.ucsd.edu)


Abstract

Our need for useful energy, defined as exergy, continues to increase. This necessitates the use of all energy resources - renewable and otherwise. Anthropogenic carbon dioxide (CO 2 ) is a proven source of global warming with rising oceans, melting polar ice, shrinking rivers, scorching draughts, failing crops, and burning forests. Renewable sources of energy are insufficient and unreliable. The good news is that we are innovators and entrepreneurs and have long experience and big data for sustainability. I will present a few examples of deploying machine learning and artificial intelligence to begin addressing these challenges.

Exergy efficiency optimization leads to not only reduced fuel consumption and costs but also to reduced CO 2 emissions. Indeed, many methods of energy conservation lead to enhanced efficiencies and sustainability. I will share as to how big data from operating coal burning power plants need to be used for optimization of exergy efficiency. Exergetic operation of these plants is an immediate opportunity for addressing the economic challenges faced by Pennsylvania,
West Virginia, Kentucky, Indiana, Illinois, North Dakota, South Dakota and others.

Fuel flexibility is one method of not only reducing our reliance on fossil fuels, and their nondemocratic exporters, but also of contributing to the recycling of carbon dioxide by sustainably utilizing biomass. Ammonia and hydrogen mixtures and higher hydrogen content biofuels offer exciting possibilities. Even with carbon containing fuels, utilizing inherently higher temperature and therefore fundamentally higher efficiency cycles is important. Higher efficiencies lead to reduction in CO 2 emissions. However, fuel flexibility and inherent high temperatures must not compromise safety for example in aircraft engine operations. Fuel lean operations of aircraft engines may present challenges such as lean blow out (LBO) and high altitude relight (HAR). Sufficiently big and reliable data for such events are rare and often reliable augmentation of these data is necessary for applying machine learning and artificial intelligence for useful purposes. I will discuss our contributions to the achievements of a large collaborative group in a project called the National Jet Fuel Combustion Program (NJFCP). Specifically, there is the potential to provide sufficiently early warning of an impending LBO for the pilot to respond while utilizing a biofuel.

I will conclude by emphasizing that there are so many opportunities for all of us to identify big data in our specialties and benefit from the (re)emerging fields of machine learning and artificial intelligence.

Speaker Bio

Dr. Jay P. Gore (an AIAA Fellow, 2009; an ASME Fellow; 2006; and a U. S. Presidential Young Investigator Award winner; 1991) is the Vincent P. Reilly Professor in Mechanical Engineering with courtesy appointments in Aeronautical and Astronautical Engineering and Chemical Engineering at Purdue University. Dr. Gore has received recognitions: in the Purdue Innovator Hall of Fame in 2014, by the Chief Minister of the State of Maharashtra in India in 2016. In 2014, McMaster University recognized him with a Cafe X award by and Purdue presented him the Discovery in Mechanical Engineering and the Celebration of Faculty Career awards. He received a panelist award from the Materials Research Society in 2013. Purdue recognized his teamwork with an award for founding the Summer Undergraduate Research Fellowships (SURF) program in 2012. He served as a Jefferson Science Fellow within the Department of State in 2010-11 and remained on call until 2015. Dr. Gore holds the Post-Doctoral Certificate from the Aerospace Engineering Department, University of Michigan, Ann Arbor, the Ph.D. and M. S. in Mechanical Engineering, Penn State University, and the B. E. Mechanical Engineering with Gold Medal from the University of Pune, India. With Purdue approval, he has served as the Principal Transformation Advisor and Vice Chancellor at Maharashtra Institute of Technology, World Peace University (MIT WPU), Pune, India during 2016 and 2017 and is currently serving as the Principal Advisor to MIT WPU. Dr. Gore was the founding Director of the Energy Center in Discovery Park at Purdue. He served as a Research Fellow in Aerospace Engineering at the University of Michigan and as an Assistant Professor of Mechanical Engineering at the University of Maryland (1987-1991) prior to joining Purdue as an Associate Professor. Dr. Gore received early promotions to the rank of Professor of Mechanical Engineering and to the Chair Professorship. Jay is a past Chairman of the Central States Section of the International Combustion Institute and the ASME K11 Committee on Heat Transfer in Fire and Combustion. Dr. Gore has served as an Associate Editor of the AIAA Journal. He has served as an Associate Editor of the ASME Journal of Heat Transfer. He was the U.S. Editor of the 28th International Combustion Symposium. He has received the Best Paper in Heat Transfer Literature Award from ASME. He has also received Faculty Fellowships from the Japanese Ministry of Education and the U. S. Department of Energy. Jay's research is in the area of combustion and radiation heat transfer with applications to CO2 emissions reduction, pollutant reduction, efficiency enhancements, fire safety, and improved fundamental understanding. He has received over $20M in research funding and is currently serving as the PI for grants in gas turbine combustion, sprays and fire safety. He has advised the PhD dissertations of 30 students and MS theses of over 50 students. He has applied infrared radiation sensing knowledge to a wide range of multidisciplinary problems in aerospace, power, and medical diagnostics areas. He has authored or coauthored over 150 archival papers, 4 book chapters, and 250 conference papers.