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Ahmad Al Rashdan

Senior Research and Development Scientist

Research Areas:

Biography:

Ahmad Al Rashdan, Ph.D., is currently a senior research and development scientist in the nuclear science and technology directorate at INL. Dr. Al Rashdan holds a Ph.D. in Nuclear Engineering from Texas A&M University, a M.Sc. in Information Technology and Automation Systems from Esslingen University of Applied Science from Germany, and a B.Sc. in Mechanical Engineering from Jordan University of Science and Technology in Jordan. He has around 15 years of industrial and research experience in automation, instrumentation, and control, including experience at INL, the ABB Group, Texas A&M University, the International Atomic Energy Agency, Daimler Chrysler-Mercedes Group, and Fraunhofer Institute for Production and Automation. His experience includes automated work processes using artificial intelligence methods and advanced analytics, online condition monitoring of nuclear systems, control systems design and development, anomalies detection, and automated modeling and simulation. Dr. Al Rashdan is an active contributor to and organizer of several DOE events and scientific conferences. He authored or co-authored more than 40 technical reports and journal papers and five patent applications and is an active reviewer for several nuclear energy and Institute of Electrical and Electronics Engineers (IEEE) journals, as well as many DOE grants. He is currently a guest editor for the Big Data Analytics for the Nuclear Power Plants Special Issue of the Progress in Nuclear Energy Journal. He is the recipient and co-recipient of more than 15 recognition and funding awards. Dr. Al Rashdan is a senior member of the IEEE and a member of the American Nuclear Society.

Digital Profiles:
Education:

​Ph.D., Nuclear Engineering - Texas A & M University

M.S., Information Technology and Automation Systems - Esslingen University of Applied Science, Germany

B.S., Mechanical ENgineering - Jordan University of Science and Technology, Jordan

Affiliations:

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Publications:

Technical Reports

Al Rashdan, A., Abdel-Khalik, H., Giraud, K., Griffel, M.,  Guillen, D., and Varuttamaseni, A., 2020, An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring, INL/EXT-20-00556.

Al Rashdan, A., M. Griffel, R. Boza, and D. Guillen, 2019, Subtle Process Anomalies Detection Using Machine Learning Methods, INL/EXT-19-55629.

Al Rashdan, A., and S. St. Germain, 2019, Automating Surveillance Activities in a Nuclear Power Plant, INL/EXT-19-55620.

Al Rashdan, A., J. Browning, and C. Ritter, 2019, Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND): Preliminary Model and Ontology,
INL/EXT-19-55610.

Al Rashdan, A., M. Griffel, and L. Powell, 2019, Automating Fire Watch in Industrial Environments through Machine Learning-Enabled Visual Monitoring, INL/EXT-19-55703.

Unruh, T., A. Al Rashdan, K. Davis, K. Fujimoto, M. McMurtrey, K. Mondal, and K. Tsai, 2019, Passive Monitors for Temperature and Neutron Fluence, INL/EXT-19-55501.

Al Rashdan, A., C. Krome, S. St. Germain, J. Corporan, K. Ruppert, and J. Rosenlof, 2019, Method and Application of Data Integration at a Nuclear Power Plant, INL/EXT-19-54294.

Al Rashdan, A., J. Smith, S. St. Germain, C. Ritter, V. Agarwal, R. Boring, T. Ulrich, and J. Hansen, 2018. Development of a Technology Roadmap for Online Monitoring of Nuclear Power Plants, INL/EXT-18-52206.

Al Rashdan, A., and T. Mortenson, 2018, Automation Technologies Impact on the Work Process of Nuclear Power Plants, INL/EXT-18-51457.

Al Rashdan, A., and S. St. Germain, 2018, Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants, INL/EXT-18-51456.

Davis, K., T. Unruh, P. Calderoni, B. Heidrich, S. Van Dyck, A. Gusarov, A. Al Rashdan, and A. Lambson, 2018, Evaluations of BR2 Silicon Carbide Temperature Monitors, INL/EXT‑18‑46086.

Al Rashdan, A., and K. Savchenko, 2018, Preliminary Comparison of Analog and Digital Instrumentation and Control for the Versatile Test Reactor, INL/EXT-18-45510.

Agarwal V., J. Buttles, and A. Al Rashdan A., 2018, Final CRADA Report for Enhanced and Miniaturized Wireless Valve Position Indicator Prototype, INL/EXT-18-44972.

Ali, M., B. Zhang, S. W. Glass, L. Fifield, K. L. Simmons, M. Jones, and Al Rashdan, A., 2017, Novel NDE Sensors, Waveforms, Models, and Algorithms for Cable Health Monitoring: Milestone 1 Report: Interdigitated Sensor Modeling and Simulations, NEUP Report for Project 17-12678.

Al Rashdan, A., S. St Germain, R. Boring, T. Ulrich, and B. Rice, 2017, Automated Work Packages: Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Industry, INL/EXT-17-43264.

Al Rashdan, A., T. Unruh, and J. Daw, 2017, Automated Post-irradiation Examination of SiC Monitors for Peak Irradiation Temperature Measurement: Holder Design and Preliminary Results, INL/EXT-17-41729.

Al Rashdan, A., J. Oxstrand, and V. Agarwal, 2016, Automated Work Package: Conceptual Design and Data Architecture, INL/EXT-16-38809.

Oxstrand, J., A. Al Rashdan, A. Bly, B. Rice, K. Fitzgerald, and K. Wilson, 2016, Digital Architecture Planning Model, INL/EXT-16-38220.

Unruh, T., J. Daw, and A. Al Rashdan, 2015, Silicon Carbide Temperature Monitor Processing Improvement, INL/EXT-15-36738.

Oxstrand, J., A. Al Rashdan, K. Le Blanc, A. Bly, and V. Agarwal, 2015, Automated Work Package Prototype: Initial Design, Development, and Evaluation, INL/EXT-15-35825.

Parma, E., S. Wright, M. Vernon, D. Fleming, G. Rochau, A. Suo-Anttila, A. Al Rashdan, and P. Tsvetkov, 2011, Supercritical CO2 Direct Cycle Gas Fast Reactor (SC-GFR) Concept, Sandia National Laboratories, SAND2011-2525.

Journal Papers

Guillen, D., Anderson, N., Krome, C.,  Boza, R.,  Griffel, M.,  Zouabe, J.,  Al Rashdan, A., A RELAP5-3D/LSTM Model for the Analysis of Drywell Cooling Fan Failure, Progress in Nuclear Energy, accepted October 2020. https://doi.org/10.1016/j.pnucene.2020.103540.

Garcia, H., S. Aumeier, A. Al Rashdan, and B. Rolston, 2020, “Secure embedded intelligence in nuclear systems: Framework and methods," Annals of Nuclear Energy, accepted for publication. DOI:10.1016/j.anucene.2019.107261.

Garcia, H., S. Aumeier, and A. Al Rashdan, 2019, “Integrated state awareness through secure embedded intelligence in nuclear systems: Opportunities and implications," Nuclear Science and Engineering, accepted for publication. DOI:10.1080/00295639.2019.1698237.

Davis, K., A. Gusarov, T. Unruh, P. Calderoni, B. Heidrich, K. Verner, A. Al Rashdan, S. Van Dyck, and I. Uytdenhouwen, 2019, “Evaluation of low dose silicon carbide temperature monitors," IEEE Transactions on Nuclear Science, accepted for publication. DOI:10.1109/TNS.2019.2957972.

Al Rashdan, A. and D. Roberson, 2019, “A frequency domain control perspective on xenon resistance for load following of thermal nuclear reactors," IEEE Transactions on Nuclear Science., Vol. 66, No. 9, pp. 2034–2041.

Fleming, A., A. Al Rashdan, C. Jensen, and P. Calderoni, 2019, An impedance-based diameter gauge for in-pile fuel deformation measurements," Instrumentation Science & Technology, Vol. 47, No. 6,
pp. 611–626.

Boring, R., T. Ulrich, R. Lew, C. Kovesdi, and A. Al Rashdan, 2019, “A comparison study of operator preference and performance for analog versus digital turbine control systems in control room modernization," Nuclear Technology, Vol. 205, No. 4, pp. 507–523.

Farber, J., D. Cole, A. Al Rashdan, and V. Yadav, 2019. Using Kernel Density Estimation to Detect Loss-of-Coolant Accidents in a Pressurized Water Reactor. Nuclear Technology, special issue on Big Data for Nuclear Power Plants, Vol. 205, No. 8, pp. 1043–1052.

Al Rashdan, A., and V. Agarwal, 2019, “A data model for nuclear power plant work packages," Nuclear Technology, special issue on Big Data for Nuclear Power Plants, Vol. 205, No. 8,
pp. 1053–1061.

Al Rashdan, A., and S. St. Germain, 2019, “Methods of data collection in nuclear power plants," Nuclear Technology, special issue on Big Data for Nuclear Power Plants, Vol. 205, No. 8,
pp. 1062–1074.

Al Rashdan, A., J. Oxstrand, and V. Agarwal, 2018, “Automated work packages: Capabilities of the future," Nuclear Technology, Vol. 202, No. 2–3, pp. 201–209.

Al Rashdan, A., and P. Tsvetkov, 2015, “Parametric evaluation of an SMR design domain," Annals of Nuclear Energy, Vol. 85, pp. 958–978.

Patents:

Al Rashdan, A. “Automated gauge reading to reduce operation and maintenance activities in nuclear power plants," BA-1097: 62/934,970, filed November 13, 2019.

Al Rashdan, A. “Image-driven self-navigation of drones in indoor environments," BA‑1141: 62/934,976, filed November 13, 2019.

Oxstrand, J., K. Le Blanc, and A. Al Rashdan, “Method to convert written instructions to structured data for use in context sensitive procedures," Patent Application 16/222,370, filed December 2018.

Agarwal, V., J. Buttles, and A. Al Rashdan, “Sensor system and implementation of the same," Battelle Energy Alliance, Patent Application 15/851,442, filed December 2017.

A. Al Rashdan, “Method and apparatus for online condition monitoring of spent nuclear fuel dry cask storage systems," Battelle Energy Alliance, Patent Application 15/703,655, filed September 2017.​

Awards:

Selected Awards and Recognition:

Lead inventor of R&D 100 finalists for the technology: Route Operable Unmanned Navigation of Drones.

INL awardee of DOE award for “Automated Logging of Analog Control Rooms", Technology Commercialization Fund -20-21458, 2020 (led by INL).

INL awardee of DOE award (led by INL) for “High Accuracy Self-Navigation of Indoor Environment Drones", Technology Commercialization Fund -20-21397, 2020 (led by INL).

Recipient of INL Recognition Award in recognition of contributions supporting INL's strategic mission objectives, which resulted in a performance evaluation score of A+ for nuclear energy in 2019.

Recipient of INL Exceptional Innovation Contribution Award for creating valuable INL intellectual property entitled, “Automated Gauge Reading to Reduce Operations and Maintenance Activities at a Nuclear Power Plant," 2019.

Recipient of INL Exceptional Innovation Contribution Award for creating valuable INL intellectual property entitled, “Data Integration Aggregated Model for Nuclear Deployment," 2019.

Recipient of INL Exceptional Innovation Contribution Award for creating valuable INL intellectual property entitled, “Image-driven Self-Navigation of Drones in Indoor Environments," 2019.

Recipient of INL Exceptional Contribution Program Award in recognition of persistent efforts to bring new and challenging work into the department with numerous LDRD, NEET, and other proposals, and initiation of collaboration with other INL organizations, 2019.

Recipient of Idaho Innovation Center Innovator of the Year Award, 2019.

INL awardee of DOE award for “Online Monitoring for Nuclear Power Plants" – U.S. Industry Opportunities for Advanced Nuclear Technology Development, 2019 (led by Utilities Service Alliance).

INL awardee of DOE award for “Passive Radio Frequency Tags and Sensors for Process Monitoring in Advanced Reactors" – U.S. Industry Opportunities for Advanced Nuclear Technology Development, 2019 (led by Dirac Solutions).

Co-awardee of DOE award (led by Westinghouse) for “Self-Regulating, Solid Core Block 'SCB' for an Inherently Safe Heat Pipe Reactor" – Department of Energy Advanced Research Projects Agency-Energy, 2018 (led by Westinghouse).

Co-awardee of DOE award for “Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform" – U.S. Industry Opportunities for Advanced Nuclear Technology Development, 2018 (led by Rolls Royce).

Co-awardee of DOE award for “Pilot Demonstration of a Wireless Valve Position Indication Sensor System in Nuclear Power Plants" –Technology Commercialization Fund Phase II, 2018 (led by INL).

Co-awardee of DOE award for “Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants" – Department of Energy Nuclear Energy Enabling Technologies, 2018 (led by INL).

INL awardee of DOE award for “Online Condition Monitoring of Spent Nuclear Fuel Dry Cask Storage Systems" – Department of Energy Lab Corps program, 2016 (led by INL).

INL awardee of DOE award for “Novel NDE Sensors, Waveforms, Models, and Algorithms for Cable Health Monitoring" – Department of Energy Nuclear Energy University Program, 2016 (led by University of South Carolina).

Co-awardee of DOE award for “Enhanced and Miniaturized Wireless Valve Position Indicator Prototype and Pilot Demonstration of Wireless Valve Position Indication Sensor System on Manual Valves in Nuclear Power Plants" –Technology Commercialization Fund Phase I, 2016 (led by INL).​


Research Interests:

​Nuclear Instrumentation and Control

Artificial Intelligence
Online Monitoring
Automation

Version: 9.0
Created at 3/21/2018 8:44 AM by Phyllis L. King
Last modified at 3/15/2021 4:48 PM by Tiffany M. Adams