FY22 FECM Spring R&D Project Review Meeting - Crosscutting Research (University Training & Research)

• May 10, 2022

University Training and Research – Program Overview
Sydni Credle, Technology Manager, National Energy Technology Laboratory

Techno-Economic and Deployment Analysis of Fossil Fuel-Based Power Generation with Integrated Energy Storage
Javad Khalesi, University of North Carolina Charlotte

Expedited Real Time Processing for the NETL Hyper Cyber-Physical System
Comas Haynes and Gared Colton, Georgia Tech Research Corporation

Ultra-Low Disorder Graphene Quantum Dot-Based Spin Qubits for Cyber Secure Fossil Energy Infrastructure
Aruna Narayanan Nair and Venkata Surya N. Chava, University of Texas at El Paso

Harnessing Quantum Information Science For Enhancing Sensors In Harsh Fossil Energy Environment
Bryan Wong, and Xian Wang, University of California – Riverside

AI Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers
Hao Zhang, Colorado School of Mines

A Lizard-Inspired Tube Inspector (LTI) Robot
Ehsan Dehghan Niri, New Mexico State University and Hamidreza Marvi, Arizona State University

Development of a Pipe Crawler Inspection Tool for Fossil Energy Power Plants
Julie Villamil and Sharif Sarker, Florida International University

Autonomous Aerial Power Plant Inspection in GPS-Denied Environments
Angel Flores Abad, University of Texas at El Paso

A Novel Access Control Blockchain Paradigm for Cybersecure Sensor Infrastructure in Fossil Power Generation Systems
Rahul Panat, Carnegie Mellon University

Secure Data Logging and Processing with Blockchain and Machine Learning
Leonel E. Lagos and Himanshu Upadhyay, Florida International University’s Applied Research Center and Wenbing Zhao, Cleveland State University

Blockchain Empowered Provenance Framework for Sensor Identity Management and Data Flow Security in Fossil-Based Power Plants
Abel Gomez, University of Texas El Paso and Sayyed Farid Ahamed, Old Dominion University

Incorporating Blockchain/P2p Technology into an SDN-Enabled Cybersecurity System to Safeguard Fossil Fuel Power Generation Systems
Jun Liu, University of North Dakota

 

• May 12, 2022

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments
Kenneth McAfee, University of Maryland

Wireless High Temperature Sensor Network for Smart Boiler Systems
Xuejun Lu, University of Massachusetts Lowell

High-Accuracy and High-Stability Fiber-Optic Temperature Sensors for Coal Fired Advanced Energy Systems
Hasanur Chowdhury, Michigan State University

Passive Wireless Sensors for Realtime Temperature and Corrosion Monitoring of Coal Boiler Components Under Flexible Operation
Brian Jordan, West Virginia University

Ceramic-Based Ultra-High Temperature Thermocouples in Harsh Environments
Grace Farrell, Morgan State University and Zhe Chen, University of Wyoming

Developing Drag Models for Non-Spherical Particles through Machine Learning
Rui Ni, Johns Hopkins University

A General Drag Model for Assemblies of Non-Spherical Particles Created with Artificial Neural Networks
Andres Leon Islas and Joshua Conner, University of Texas at San Antonio

Development and Evaluation of a General Drag Model for Gas-Solid Flows Via Physics Informed Deep Machine Learning
Maria Pres-Reyes and Cheng-Xian Lin, Florida International University

A Machine Learning Based Interaction Force Model for Irregular-Shaped Particles in Incompressible Flows
Soohwan Hwang, Ohio State University

Functional Predictor Variables for the Leaching Potential of Arsenic and Selenium from Coal Fly Ash
Zehao Jin and Helen Hsu-Kim, Duke University

Elucidating Arsenic and Selenium Speciation in Coal Fly Ashes
Yuanzhi Tang, Georgia Institute of Technology

Trace Element Sampling and Partitioning Modeling to Estimate Wastewater Composition and Treatment Efficacy at Coal Generators
Alison Fritz, Stanford University

Probing Particle Impingement in Boilers and Steam Turbines Using High-Performance Computing with Parallel and Graphical Processing Units
Steve Yang, University of California – Riverside

Enhancement of Operational Flexibility of Power Plants Using IN740 (Machine Learning)
Ahmed Cherif Megri, North Carolina A&T State University

An Integrated Approach to Predicting Ash Deposition and Heat Transfer in Coal Fired Boilers
Gautham Krishnamoorthy, University of North Dakota