Nicholas J. Ward, Ph.D.
Email: njw723@gmail.com
Summary
· Ph.D., Mechanical Engineering, Texas Tech University, Lubbock, TX. (Aug 2023), Cumulative GPA: 4.0
· Over 14 years of research experience in various renewable energy fields, including wind energy, solar energy, geothermal energy, and bioenergy.
· Specialized in modeling turbulence, fluid dynamics, atmospheric flows, uncertainty quantification, uncertainty propagation, generator/component performance, reliability, and wind resource assessment.
· Applied strong mathematical skills and knowledge of statistical methods to real-world problems in energy applications.
· Utilized artificial intelligence (AI) techniques, including high-performance computing, GPU computing, machine learning, deep learning, generative AI, supervised learning, and unsupervised learning.
· Authored three peer-reviewed journal articles, seven DOE technical reports, three conference papers, and four technical posters.
· Focused on unsupervised deep learning of turbulent flows and uncertainty quantification in wind turbine operation.
· National Overall Champion, US Department of Energy/AWEA National Collegiate Wind Competition 2014.
· Founding Team member and Turbine Design Engineer, PSU Remote Wind Team.
Work Experience
Machine Learning and Deep Learning Modeling and Analysis Specialist - AI Automation for Energy Applications (Wind Energy) Aug 27/2018 – Present
Gained experience as a Wind Power Generation Performance Modeling and Reliability Specialist at Electric Power Research Institute, as well as a Ph.D. Researcher at Texas Tech University in Lubbock, TX
· Spearheaded collaborative efforts with scientific teams to create automation scripts, enhancing efficiency in simulations and analyses within the energy sector.
· Applied expertise in programming to model, simulate, and forecast wind turbine failures using advanced uncertainty quantification techniques and AI algorithms for prognostics and health management, utilizing Python.
· Facilitated seamless communication between scientific and operational teams, contributing to the transfer of technical knowledge to wind turbine operators. This is exemplified by a comprehensive technical report outlining improved reliability modeling for wind turbines.
· Conducted extensive research in machine learning, deep learning, uncertainty quantification, turbulence, wind wake modeling, and rotor imbalance. Analyzed their impact on turbine product lifetime and durability.
· Played a key role in educating mechanical engineering students by conducting office hours, review sessions, and grading assignments as part of the teaching team.
Energy Efficiency Consultant - Technology Innovation & Management
Energetics Incorporated, Columbia, MD Jul 18/2016 – Aug 24/2018
· Conducted research, and drafted reports and factsheets for an independent consulting firm specializing in sustainable energy practices in United States manufacturing industries. My research has culminated in six publicly available published reports.
· Maintained high-quality company standards and professional relationships with both federal, state, and commercial clients on a daily basis.
Research & Development Engineer for Energy Systems
Dept. of Energy & Mineral Engineering, Penn State University Aug 25/2014 – Dec 19/2015
· Conducted research on modeling turbulence intensity incorporation into the power curve for a small wind turbine. Research presented at the 2015 NAWEA Conference in Virginia Tech.
· Assisted in teaching energy engineering courses by holding office hours, conducting review sessions and grading assignments.
Energy System Modeling & Design Engineer
Dept. of Energy & Mineral Engineering, Penn State University Aug 20/2012 – May 09/2014
· Designed and tested a prototype small-scale wind turbine coupled with a battery at the foundation for remote installation, as well as developed a business plan for the implementation and commercialization procedures. Research and development efforts were awarded First Place overall at the inaugural Collegiate Wind Competition in May 2014 at Las Vegas, NV.
· Developed a compartmentalized anaerobic digestor for a local farmer and business owner in State College, PA. Research was eventually published as a patent for the company, which was approved in Apr. 2015.
· Conducted research on modeling the flow, heat transfer and mass transfer of an entrained flow reactor with combined inlet feed of bituminous coal and biomass. Research was eventually defended by a Ph.D., student in May 2017.
· Assisted in teaching energy engineering courses by holding office hours, conducting review sessions and grading assignments.
Geothermal Specialist
Carney PHC, Inc., Colmar, PA Jun 04/2012 – Aug 10/2012
· Installed two different geothermal systems used for residential applications.
· Delivered a high-quality product to the clients by ensuring safe and effective installation practices, as well as maintaining excellent communication with the clients and the project team members.
Design Engineering Intern
M.C. Dean, Inc., Sterling, VA May 16/2011 – Aug 12/2011
· Designed the drawings and processed change orders for three military-base hospitals, one defense operations building, and one international embassy using AutoCAD and Revit software.
Design Engineering Intern
M.C. Dean, Inc., Sterling, VA Jun 28/2010 – Aug 06/2010
· Provided high-quality technical assistance for government clients and maintained workplace standards via extensive communication and maintaining protocol for product delivery.
Education
Ph.D., Mechanical Engineering
Texas Tech University, Lubbock, TX Aug 05/2023
Dissertation Title: Unsupervised Deep Learning for Turbulent Heat Transfer and Channel Flows via Generative Adversarial Networks
M.S., Energy Engineering
The Pennsylvania State University, University Park, PA Dec 19/2015
B.S., Energy Engineering
The Pennsylvania State University, University Park, PA May 09/2014
Certificates
Certificate in Critical Infrastructure Physical and Cyber-Security
Texas Tech University, Lubbock, TX Jul 27/2023
Wind Energy Graduate Credential with DNV-GL
Texas Tech University, Lubbock, TX Jun 20/2019
Graduate Certificate in Wind Energy
The Pennsylvania State University, University Park, PA May 25/2015
Publications
Ward, N. J. “Unsupervised deep learning of turbulent heat transfer using generative adversarial networks.” (Manuscript submitted to Fluids)
Ward, N. J., Ekwaro-Osire, S., and Dias, J.-P. “Uncertainty considerations of aerodynamic imbalances for offshore wind turbines.” (Manuscript in preparation)
Ward, N. J. (2023). “Physics-Informed Super-Resolution of Turbulent Channel Flows via Three-Dimensional Generative Adversarial Networks.” Fluids, 8(7):195.
4. Ward, N. J., Ekwaro-Osire, S., and Dias, J.-P. (2020). “Uncertainty Quantification of Mass and Aerodynamic Rotor Imbalance for Offshore Wind Turbines.” Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. Volume 12: Wind Energy. Virtual, online. Sept 21–25, 2020.
Pereira, T., Ekwaro-Osire, S., Dias, J.-P., Ward, N. J., and Cunha Jr., A. (2019). “Uncertainty quantification of wind turbine wakes under random wind conditions.” ASME 2019 International Mechanical Engineering Congress and Exposition (IMECE2019), November 2019, Salt Lake City, Utah, USA.
Brueske, S., Giles, L., Makila, T., Rogers, J., Dollinger, C., Ivanic, Z., Ward, N., and Tornatore, F. (2019, February). Research Roadmap for Advancing Technologies in California’s Industrial, Agriculture and Water Sectors. https://www.energy.ca.gov/publications/2019/research-roadmap-advancing-technologies-californias-industrial-agriculture-and
Energetics Incorporated. “Integrating Analysis Study on Energy Use and Potential Energy Saving Opportunities in the Manufacturing of Lightweight Materials.” Prepared for National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy (DOE). (Submitted October 2017, but not publicly available)
Rao, P., Aghajanzadeh, A., Sheaffer, P., Morrow III, W. R., Dollinger, C., Ward, N., Price, K., Sarker, P., Brueske, S., and Cresko, J. (2017, October). Bandwidth Study on Energy Use and Potential Energy Savings Opportunities in U.S. Cement Manufacturing. Bandwidth Study U.S. Seawater Desalination Systems. https://www.energy.gov/eere/iedo/articles/bandwidth-study-us-seawater-desalination-systems
Schwartz, H., Ward, N., Levie, B., Chadwell, B., Brueske, S., Carpenter, A., and Cresko, J. (2017, September). Bandwidth Study on Energy Use and Potential Energy Savings Opportunities in U.S. Cement Manufacturing. Bandwidth Study U.S. Cement Manufacturing. https://www.energy.gov/eere/iedo/articles/bandwidth-study-us-cement-manufacturing
Dollinger, C., Ward, N., Levie, B., Talapatra, A., Brueske, S., Carpenter, A., and Cresko, J. (2017, September). Bandwidth Study on Energy Use and Potential Energy Savings Opportunities in U.S. Food and Beverage Manufacturing. Bandwidth Study U.S. Food and Beverage Manufacturing. https://www.energy.gov/eere/iedo/articles/bandwidth-study-us-food-and-beverage-manufacturing
Z, Inc., and Energetics Incorporated (2017, March). Study of the Potential Energy Consumption Impacts of Connected and Automated Vehicles. Study of the Potential Energy Consumption Impacts of Connected and Automated Vehicles. https://www.eia.gov/analysis/studies/transportation/automated/
Rao, P., Aghajanzadeh, A., Sheaffer, P., Morrow III, W. R., Brueske, S., Dollinger, C., Price, K., Sarker, P., Ward, N., Cresko, J. (2016, October). Volume 1: Survey of Available Information in Support of the Energy-Water Bandwidth Study of Desalination Systems. Volume 1: Survey of Available Information in Support of the Energy-Water Bandwidth Study of Desalination Systems. https://eta.lbl.gov/publications/volume-1-survey-available-information
Ward, N. J., and Stewart, S. (2015). “A Turbulence Intensity Similarity Distribution for Evaluating the Performance of a Small Wind Turbine in Turbulent Wind Regimes.” Wind Engineering, 39(6):661-673.
Techniques, Awards & Hobbies
Foreign Languages: English– native; Spanish – fluent; Italian – elementary
· Engineering Programs: FAST, TurbSim, OpenFOAM, FLORIS, AutoCAD, Revit, Inventor, SolidWorks, Visual Studio, Windographer, GAMS
· Programming Languages: Python (Tensorflow, Keras, PyTorch, sklearn, pandas, NumPy, SciPy, SymPy, Matplotlib, Pandas, scikit-learn, scikit-image, reliability, SALib), C++, Fortran, R, Java, MATLAB, Mathematica
· General Programs: Microsoft Office (Word, Excel, PowerPoint, Access), Adobe, Foxit, Latex/Overleaf, Dropbox
· Phi Kappa Phi Honor Society Member, March 2019-August 2023
· John and Willie Leone Department of Energy & Mineral Engineering, Outstanding Graduate Teaching Assistant Award 2015
· NREL National Wind Energy Competition 2014: founding team leader, National Champion 2014
· Society of Energy Engineers, Earth and Mineral Sciences Student Council
· Penn State Geocaching Club: Member, President (2012-2014)
· Union League of Philadelphia: Citizenship Award and Scholarship Recipient, Ginsburg Family Foundation Scholarship
· 3D Architectural Model Competition, National Champion 2008; PA State Champion 2008; PA Regional Champion 2009, 2010
· Eagle Scout with Gold and Bronze Palms, Class of 2008
· Aikido: First-Kyu Black Belt