John D. Hedengren

Professor, Brigham Young University

Dr. John Hedengren is a Professor at Brigham Young University in the Chemical Engineering Department. He leads the BYU Process Research and Intelligent Systems Modeling (PRISM) group with a focus on physics-informed machine learning for optimization of energy systems, unmanned aircraft, and drilling. Prior to BYU he worked in industry for 7 years on nonlinear estimation and predictive control for polymers. His work includes the APMonitor Optimization Suite with a recent extension to Python GEKKO. He led the development of the Temperature Control Lab that is used by many universities for process control and data science education. His publications span topics of data science, machine learning, smart grid optimization, unmanned aerial systems, and predictive control.

John D. Hedengren Photo Credit: Alyssa Lyman Dahneke, CC BY-SA 4.0 

 John D. Hedengren
 330L Engineering Building
 Department of Chemical Engineering 
 Brigham Young University
 Provo, UT 84602 

 📧 Email: john.hedengren@byu.edu
 📱 Tel: +1 801-477-7341

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 NSF Biographical Sketch

His professional service includes IEEE CSS Chair of Control Education, Trustee of the CACHE Corporation, adjunct professor at the University of Utah, member of the AIChE CAST Committee, and Communications Chair for the American Automatic Control Council (A2C2). In 2005, he received a Ph.D. (Ch.E.) from the University of Texas at Austin for contributions to control and estimation of large-scale dynamic systems. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019, visiting 22 local sections to deliver a presentation on "Drilling Automation and Downhole Monitoring with Physics-based Models". He completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation.

Prof. Hedengren has consulting experience with Meta, Apache, Aramco, ENI Petroleum, HESS, TOTAL, and other companies on machine learning and automation solutions. He worked full-time for 5 years with ExxonMobil supporting advanced control and optimization solutions. His industrial control experience with PLC and DCS systems includes OPTO22, Honeywell TPS/TDC3000, Experion system, OPC, and Modbus. His area of expertise is in process dynamics, control, and optimization with applications in fiber optic monitoring, automation of oil and gas processes, unmanned aerial systems, systems biology, and grid-scale energy systems. In chemicals manufacturing, he has extensive experience in automation and modeling of the production of polymers such as polyethylene, polypropylene, butyl rubber, and polystyrene as well as specialty chemicals (polyalphaolefins). Automation software that he developed has been applied in over 100 industrial applications world-wide in refineries, chemical plants, and offshore oil platforms.

Research Interests

  • APMonitor and GEKKO Optimization Suite: Advanced Process Monitoring (APM) is a software platform to solve large-scale Differential and Algebraic Equation (DAE) models in simulation, process control, and optimization applications. Recipient of the 2014 AIChE David Himmelblau Award, 2018 AIChE Computing Practice Award, and 2024 John R. Ragazzini Award.
  • Drilling Automation
  • Energy System Optimization
  • Model Predictive Control
  • Unmanned Aerial Systems
  • Machine Learning
  • Nonlinear Model Library: One of the major bottlenecks to improve nonlinear Model Predictive Control (Nonlinear MPC) and Real-time Optimization (RTO) is the lack of reliable first-principles or hybrid models. This nonlinear model library is a collaborative platform where chemical process models can be documented and shared.
2024
  1. Chen, Y., Hill, D., Billings, B., Hedengren, J.D., Powell, K.M., Hydrogen underground storage for grid electricity storage: An optimization study on techno-economic analysis, Energy Conversion and Management, Volume 322, 2024, 119115, ISSN 0196-8904, doi: 10.1016/j.enconman.2024.119115 Article
  2. Ho, A., Billings, B., Hedengren, J.D., Powell, K.M., Flexible Nuclear Hybrid Systems for Load Following and Water Desalination, Renewable Energy Focus, Volume 51, October 2024, 1006412024, doi: 10.1016/j.ref.2024.100641 Article
  3. Larsen, A., Lee, R., Wilson, C., Hedengren, J.D., Benson, F., Memmott, M., Multi-Objective Optimization of Molten Salt Microreactor Shielding Perturbations Employing Machine Learning, Nuclear Engineering and Design, Volume 426, September 2024, 113372, 2024. Article
  4. Hill, D., Tito, S.R., Walmsley, M., Hedengren, J.D., Techno-ecnonmic optimization of a hybrid energy system with limited grid connection in pursuit of net zero carbon emissions for New Zealand, e-Prime - Advances in Electrical Engineering, Electronics and Energy, 2024, 100564, ISSN 2772-6711, DOI: 10.1016/j.prime.2024.100564. Article (Open Access)
  5. Wallace, J., Hill, D., Thurston, D., Hedengren, J.D., Memmott, M., Model Predictive Control of a Grid-Scale Thermal Energy Storage System in Relap5-3d, Nuclear Engineering and Design, 2024. Article
  6. Gunnell, L., Nicholson, B., Hedengren, J.D., Equation-based and data-driven modeling: Open-source software current state and future directions, Computers & Chemical Engineering, 2024, 108521, ISSN 0098-1354, DOI: 10.1016/j.compchemeng.2023.108521. Preprint | Article
  7. Chen, Y., Hill, D., Billings, B., Hedengren, J.D., Powell, K.M., Hydrogen Underground Storage for Grid Resilience: A Dynamic Simulation and Optimization Study, American Control Conference, Toronto, Canada, July 2024.
  8. Gunnell, L., Perez, K.X., Castillo, I., Hoogerwerf, A.S., Peng, Y., Hedengren, J.D., Detection of Valve Stiction in Industrial Control Loops through Continuous Wavelet Transformation with a CNN, American Control Conference, Toronto, Canada, July 2024. Preprint
2023
  1. Park, J., Babaei, M.R., Arce Munoz, S., Venkat, A.N., Hedengren, J.D., Simultaneous Multistep Transformer Architecture for Model Predictive Control, Computers & Chemical Engineering, Volume 178, October 2023, 108396, DOI: 10.1016/j.compchemeng.2023.108396 Preprint | Article
  2. Hill, D., McCrea, D., Ho, A., Memmott, M., Powell, K., Hedengren, J., A Multi-Scale method for combined design and dispatch optimization of nuclear hybrid energy systems including storage, e-Prime - Advances in Electrical Engineering, Electronics and Energy, Volume 5, 2023, 100201, ISSN 2772-6711, DOI: 10.1016/j.prime.2023.100201 Article (Open Access)
  3. Babaei, M.R., Stone, R., Knotts, T.A., Hedengren, J.D., Physics-Informed Neural Networks with Group Contribution Methods, Journal of Chemical Theory and Computation, American Chemical Society, 2023, DOI: 10.1021/acs.jctc.3c00195. Article
  4. Rossiter, J.A., Cassandras, C.G., Hespanha, J., Dormido, S., Torre, L., Ranade, G., Visioli, A., Hedengren, J.D., Murray, R.M., Antsaklis, P., Lamnabhi-Lagarrigue, F., Parisini, T., Control education for societal-scale challenges: A community roadmap, Annual Reviews in Control, 2023, ISSN 1367-5788, DOI: 10.1016/j.arcontrol.2023.03.007 Article (Open Access)
  5. Ho, A., Memmott, M., Hedengren, J.D., Powell, K.M., Exploring the benefits of molten salt reactors: An analysis of flexibility and safety features using dynamic simulation, Digital Chemical Engineering, Volume 7, June 2023, 100091, ISSN 2772-5081, DOI: 10.1016/j.dche.2023.100091 Article
  6. Yao, J., Gao, T., Hedengren, J.D., Powell, K.M., A Two-Level Optimization Framework for Battery Energy Storge Systems to Enhance Economics and Minimize Long-Term Capacity Fading, Journal of Energy Storage, Volume 63, July 2023, 106943, 2023, DOI: 10.1016/j.est.2023.106943 Article
  7. Munoz, S.A., Park, J., Stewart, C.M., Martin, A.M., Hedengren, J.D., Deep Transfer Learning for Approximate Model Predictive Control, Processes 2023, 11, 197. Article (Open Access)
  8. Hedengren, J.D., Brower, D.V., Kidder, K., Hillman, Z., Data-Driven TLP Tendon Loads from Internal Hull Fiber-Optic Sensors, ASME 42nd International Conference on Ocean, Offshore and Arctic Engineering, OMAE2023/103309, Melbourne, Australia, June 2023. Preprint
2022
  1. Gunnell, L., Manwaring, K., Lu, X., Reynolds, J., Vienna, J., Hedengren, J.D., Machine Learning with Gradient-based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints, Processes, 10(11), 2365, Nov 2022, DOI: 10.3390/pr10112365. Article (Open Access) | Documentation
  2. Blackburn, L.D., Tuttle, J.F., Andersson, K., Hedengren, J.D., Powell, K.M., Dynamic Machine Learning-based Optimization Algorithm to Improve Boiler Efficiency, Journal of Process Control, Volume 120, December 2022, Pages 129-149, 2022, DOI: 10.1016/j.jprocont.2022.11.002 Article
  3. Hill, D., Martin, A., Martin-Nelson, N., Granger, C., Memmott, M., Powell, K., Hedengren, J.D., Techno-economic sensitivity analysis for combined design and operation of a small modular reactor hybrid energy system, International Journal of Thermofluids, Volume 16, 100191, November 2022, DOI: 10.1016/j.ijft.2022.100191 Article (Open Access)
  4. Ho, A., Hill, D., Hedengren J.D., Powell, K.M., A nuclear-hydrogen hybrid energy system with large-scale storage: A study in optimal dispatch and economic performance in a real-world market, Journal of Energy Storage, Volume 51, 104510, July 2022, DOI: 10.1016/j.est.2022.104510 Article
2021
  1. Berrett, B.E., Vernon, C.A., Beckstrand, H., Pollei, M., Markert, K., Hedengren, J.D., Franke, K.W., Large-Scale Reality Modeling of a University Campus Using Combined UAV and Terrestrial Photogrammetry for Historical Preservation and Practice Use, Drones, Special Issue on Geoinformatics for the Preservation and Valorization of Cultural Heritage, Nov 17, 2021, 5(4), 136. DOI: 10.3390/drones5040136. Article
  2. Ho, A., Mohammadi, K., Hedengren J.D., Memmott, M., Powell, K.M., Dynamic simulation of a novel nuclear hybrid energy system with large-scale hydrogen storage in an underground salt cavern, International Journal of Hydrogen Energy, 29 July 2021. Article
2020
  1. Moura Oliveira, P.B., Hedengren, J.D., Pires, E.J.S., Swarm-Based design of Proportional Integral and Derivative Controllers using a Compromise Cost Function: An Arduino Temperature Laboratory Case Study, Special Issue: Algorithms for PID Controller, Algorithms, 13(12), 315, DOI: 10.3390/a13120315, 2020. Article
  2. Hammond, J.E., Vernon, C.A., Okeson, T.J., Barrett, B.J., Arce, S., Newell, V., Janson, J., Franke, K.W., Hedengren, J.D. Survey of 8 UAV Set-Covering Algorithms for Terrain Photogrammetry, Remote Sensing, 2020, 12, 2285. Article
  3. Arce, S., Vernon, C.A., Hammond, J., Newell, V., Janson, J., Franke, K.W., Hedengren, J.D. Automated 3D Reconstruction Using Optimized View-Planning Algorithms for Iterative Development of Structure-from-Motion Models, Remote Sensing, 2020, 12, 2169. Article
  4. Park, J., Price, C., Pixton, D., Aghito, M., Nybø, R., Bjørkevoll, K., Hedengren, J.D., Model predictive control and estimation of managed pressure drilling using a real-time high fidelity flow model, ISA Transactions, 105, pp. 256-268, Oct 2020, doi: 10.1016/j.isatra.2020.05.035. Preprint | Article
  5. Park, J., Martin, R.A., Kelly, J.D., Hedengren, J.D., Benchmark Temperature Microcontroller for Process Dynamics and Control, Computers & Chemical Engineering, Special Issue in Honor of Thomas F. Edgar, 135, 6 April 2020, doi: 10.1016/j.compchemeng.2020.106736. Preprint | Article
2019
  1. Simmons, C., Arment, J., Powell, K.M., Hedengren, J.D., Proactive Energy Optimization in Residential Buildings with Weather and Market Forecasts, Processes, MDPI, 7 (12), 929, doi: 10.3390/pr7120929, 2019. Abstract | Article (Open Access)
  2. Freeman, M., Vernon, C., Berrett, B., Hastings, N., Derricott, J., Pace, J., Horne, B., Hammond, J., Janson, J., Chiabrando, F., Hedengren, J.D., Franke, K., Sequential Earthquake Damage Assessment Incorporating Optimized sUAV Remote Sensing at Pescara del Tronto, Special Issue: Remote Sensing Applications for Earthquake and Tsunami Damage Assessment, Geosciences, 2019. Article (Open Access)
  3. Okeson, T.J., Barrett, B.J., Arce, S., Vernon, C.A., Franke, K.W, Hedengren, J.D., Achieving Tiered Model Quality in 3D Structure from Motion Models Using a Multi-Scale View-Planning Algorithm for Automated Targeted Inspection, Sensors, MDPI, 19 (12), 2703, doi: 10.3390/s19122703, 2019. Article (Open Access)
  4. Hansen, B., Tolbert, B., Vernon, C., Hedengren, J.D., Model Predictive Automatic Control of Sucker Rod Pump System with Simulation Case Study, Computers & Chemical Engineering, 121, pp. 263-284, 2019. Preprint | Article | Source Code
  5. Blackburn, L., Young, A., Rogers, P., Hedengren, J.D., Powell, K.M., Dynamic Optimization of a District Energy System with Storage Using a Novel Mixed-Integer Quadratic Programming Algorithm, Optimization and Engineering, 2019. Article
2018
  1. Martin, R.A., Gates, N., Ning, A., Hedengren, J.D., Dynamic Optimization of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints, Journal of Guidance, Control, and Dynamics, 2018, doi: 10.2514/1.G003737. Preprint | Article | Source Code
  2. Beal, L.D.R., Hill, D., Martin, R.A., and Hedengren, J.D., GEKKO Optimization Suite, Processes, Volume 6, Number 8, 2018, doi: 10.3390/pr6080106. Article
  3. Safdarnejad, S.M., Hedengren, J.D., Powell, K.M., Performance Comparison of Low Temperature and Chemical Absorption Carbon Capture Processes in Response to Dynamic Electricity Demand and Price Profiles, Applied Energy, Volume 228, pp. 577-592, 2018, doi:10.1016/j.apenergy.2018.06.098. Article
  4. Beal, L.D., Petersen, D., Grimsman, D., Warnick, S., Hedengren, J.D., Integrated Scheduling and Control in Discrete-time with Dynamic Parameters and Constraints, Computers & Chemical Engineering, 115, pp. 361-376, 2018. Article
  5. Hedengren, J.D., Beal, L., Special Issue: Combined Scheduling and Control, Processes, 6(3), 24, doi: 10.3390/pr6030024, 2018. Editorial and Special Issue
  6. Brower, D.V., Bentley, N.L., Hedengren, J.D., Kipp, R.M., Le, S.Q., Seaman, C., Tang, H.H., Wilson, J.C., Full-Scale Testing of a Friction-Based, Post-Installable, Fiber-Optic Strain Sensor for Subsea Monitoring Systems, Topic: 4-6 Innovative Technologies for Deepwater Low-Cost Production, Symposium 4 Pipelines, Risers, and Subsea Systems, ASME 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2018/77117, Madrid, Spain, June 2018.
  7. Hedengren, J.D., Brower, D.V., Wilson J.C., High, G., Witherow, K., New Flow Assurance System With High Speed Subsea Fiber Optic Monitoring Of Pressure And Temperature, Symposium 4 Pipelines, Risers, and Subsea Systems, ASME 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2018/78079, Madrid, Spain, June 2018. Preprint
2017
  1. Beal, L.D., Petersen D., Pila G., Davis, B., Warnick, S., and Hedengren, J.D., Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes, Processes, 5(4), 84, doi:10.3390/pr5040084, 2017. Article (Open Access)
  2. Petersen, D., Beal, L.D., Prestwich D., Warnick, S., and Hedengren, J. D., Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes, Processes, 2017, Processes, 5(4), 83, doi:10.3390/pr5040083, 2017. Article (Open Access)
  3. Taysom, S., Hedengren, J.D., Sorensen, C., A Comparison of Model Predictive Control and PID Temperature Control in Friction Stir Welding, Journal of Manufacturing Processes, 29, pp. 232-241, 2017, doi: 10.1016/j.jmapro.2017.07.015. Article
  4. Udy, J., Hansen, B., Maddux, S., Peterson, D., Heilner, S., Stevens, K., Lignell, D., Hedengren, J.D., Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms, Processes, 5(3), 34, 2017, doi:10.3390/pr5030034. Article (Open Access)
  5. Martin, R.A., Blackburn, L., Pulsipher, J., Franke, K., Hedengren, J.D., Potential Benefits of Combining Anomaly Detection with View Planning for UAV Infrastructure Modeling, Remote Sensing, 9(5), 434, 2017, doi:10.3390/rs9050434. Article (Open Access)
  6. Beal, L., Park, J., Petersen, D., Warnick, S., Hedengren, J.D., Combined Model Predictive Control and Scheduling with Dominant Time Constant Compensation, Computers & Chemical Engineering, 104, pp. 271-282, 2017, doi: 10.1016/j.compchemeng.2017.04.024 Article
  7. Hedengren, J. D., Eaton, A. N., Overview of Estimation Methods for Industrial Dynamic Systems, Optimization and Engineering, Springer, Vol 18 (1), 2017, pp. 155-178, DOI: 10.1007/s11081-015-9295-9. Preprint, Article
  8. Mojica, J.L., Petersen, D.J., Hansen, B., Powell, K.M., Hedengren, J.D., Optimal Combined Long-Term Facility Design and Short-Term Operational Strategy for CHP Capacity Investments, Energy, Vol 118, 1, pp. 97–115, January 2017, DOI: 10.1016/j.energy.2016.12.009. Article
  9. Eaton, A.N., Beal, L., Thorpe, S., Hubbell, C., Hedengren, J.D., Nybø, R., Aghito, M., Real Time Model Identification Using Multi-Fidelity Models in Managed Pressure Drilling, Computers and Chemical Engineering, Vol 97, 2 February 2017, pp. 76–84, doi:10.1016/j.compchemeng.2016.11.008. Article
  10. Franke, K.W., Rollins, K.M., Ledezma, C., Hedengren, J.D., Wolfe, D. Ruggles, S., Bender, C., Reimschiissel, B., Reconnaissance of Two Liquefaction Sites using Small Unmanned Aerial Vehicles and Structure from Motion Computer Vision Following the April 1, 2014 Chile Earthquake, Journal of Geotechnical and Geoenvironmental Engineering, Volume 143, Issue 5, May 2017, doi:10.1061/(ASCE)GT.1943-5606.0001647. Article
2016
  1. Powell, K.M., Kim, J.S., Kapoor, K., Mojica, J.L., Hedengren, J.D., and Edgar, T.F., Thermal Energy Storage to Minimize Cost and Improve Efficiency of a Polygeneration District Energy System in a Real-time Electricity Market, Energy, 113, 52–63, 2016, doi:10.1016/j.energy.2016.07.009. Article
  2. Ruggles, S., Clark, J., Franke, K.W., Wolfe, D., Reimschiissel, B., Martin, R.A., Okeson, T.J., Hedengren, J.D., Comparison of SfM Computer Vision Point Clouds of a Landslide Derived from Multiple Small UAV Platforms and Sensors to a TLS based Model, Journal of Unmanned Vehicle Systems, 2016, doi:10.1139/juvs-2015-0043. Preprint
  3. Taysom, S., Hedengren, J.D., Sorensen, C., Dynamic Modeling of Friction Stir Welding for Model Predictive Control, Journal of Manufacturing Processes, 23, 165-174, 2016, doi:10.1016/j.jmapro.2016.06.004. Article
  4. Safdarnejad, S.M., Hedengren, J.D., Baxter, L.L, Dynamic Optimization of a Hybrid System of Energy-Storing Cryogenic Carbon Capture and a Baseline Power Generation Unit, Applied Energy, 172 (15), 66–79, June 2016, doi:10.1016/j.apenergy.2016.03.074. Article
  5. Powell, K. M., Eaton, A. N., Hedengren, J. D., Edgar, T. F., A Continuous Formulation for Logical Decisions in Differential Algebraic Systems using Mathematical Programs of Complementarity Constraints, Processes, 2016, 4(1), 7; doi:10.3390/pr4010007. Article
  6. Safdarnejad, S. M., Gallacher, J. R., Hedengren, J. D., Dynamic Parameter Estimation and Optimization for Batch Distillation, Computers & Chemical Engineering, Vol. 86, pp. 18–32, 2016, DOI: 10.1016/j.compchemeng.2015.12.001.Preprint, Article
  7. Martin, R.A., Rojas, I., Franke, K.W., Hedengren, J.D., Evolutionary View Planning for Optimized UAV Terrain Modeling in a Simulated Environment, Remote Sensing, 8(1), 26, 2016, DOI:10.3390/rs8010026. Article (Open Access)
2015
  1. Sun, L., Castagno, J., Hedengren, J. D., and Beard, R. W., Parameter Estimation for Towed Cable Systems Using Moving Horizon Estimation, IEEE Transactions on Aerospace and Electronic Systems, Vol. 51, No. 2, April 2015. Preprint, Article
  2. Asgharzadeh Shishavan, R., Hubbell, C., Perez, H.D., Hedengren, J.D., Pixton, D.S., and Pink, A.P., Multivariate Control for Managed Pressure Drilling Systems Using High Speed Telemetry, SPE Journal, SPE-170962, Published Online 7 Oct 2015, DOI: 10.2118/170962-PA. Article
  3. Lewis, N.R., Hedengren, J.D., Haseltine, E.L., Hybrid Dynamic Optimization Methods for Systems Biology with Efficient Sensitivities, Special Issue on Algorithms and Applications in Dynamic Optimization, Processes, 2015, 3(3), 701-729; doi:10.3390/pr3030701. Article
  4. Safdarnejad, S.M., Hedengren, J.D., Lewis, N.R., Haseltine, E., Initialization Strategies for Optimization of Dynamic Systems, Computers and Chemical Engineering, 2015, Vol. 78, pp. 39-50, DOI: 10.1016/j.compchemeng.2015.04.016. Article
  5. Safdarnejad, S.M., Hedengren, J.D., Baxter, L.L, Plant-level Dynamic Optimization of Cryogenic Carbon Capture with Conventional and Renewable Power Sources, Applied Energy Journal, Vol. 149, pp. 354-366, 2015, DOI: 10.1016/j.apenergy.2015.03.100 Article
  6. Asgharzadeh Shishavan, R., Hubbell, C., Perez, H.D., Hedengren, J.D., and Pixton, D.S., Combined Rate of Penetration and Pressure Regulation for Drilling Optimization Using High Speed Telemetry, SPE Drilling & Completion Journal, SPE-170275-PA, 30 (1), pp. 17-26, 5 March 2015. Article
  7. Eaton, A., Safdarnejad, S.M., Hedengren, J.D., Moffat, K., Hubbell, C., Brower, D.V., Brower, A.D., Post-Installed Fiber Optic Pressure Sensors on Subsea Production Risers for Severe Slugging Control, ASME 34th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2015-42196, St. John's, Newfoundland, Canada, June 2015. Preprint
  8. Safdarnejad, S.M., Kennington, L., Baxter, L., Hedengren, J.D., Investigating the Impact of Cryogenic Carbon Capture on Power Plant Performance, American Control Conference, pp. 5016-5021, Chicago, IL, July 2015, DOI: 10.1109/ACC.2015.7172120. Preprint
  9. Palmer, L.M., Franke, K.W., Martin, R.A., Sines, B.E., Rollins, K.M., and Hedengren, J.D., The Application and Accuracy of Structure from Motion Computer Vision Models with Full-Scale Geotechnical Field Tests. Proceedings, 2015 International Foundation Congress and Equipment Expo, Paper 301, ASCE, IFCEE 2015, pp. 2432-2441, doi: 10.1061/9780784479087.225, Reston, VA, 2015. Preprint
  10. Hallac, B., Keyvanloo, K., Hedengren, J.D., Hecker, W.C., Argyle, M.D., An Optimized Simulation Model for Iron-Based Fischer-Tropsch Catalyst Design: Transfer Limitations as Functions of Operating and Design Conditions, Chemical Engineering Journal, Volume 263, 1 March 2015, Pages 268–279, ISSN 1385-8947, doi: 10.1016/j.cej.2014.10.108. Article
2014
  1. Asgharzadeh Shishavan, R., Brower, D.V., Hedengren, J.D., Brower, A.D., New Advances in Post-Installed Subsea Monitoring Systems for Structural and Flow Assurance Evaluation, ASME 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE2014-24300, San Francisco, CA, June 2014. Presentation and Preprint
  2. Brower, D.V., Brower, A.D., Hedengren, J.D., Asgharzadeh Shishavan, R., A Post-Installed Subsea Monitoring System for Structural and Flow Assurance Evaluation, Offshore Technology Conference, OTC 25368, Houston, TX, May 2014. Preprint
  3. Powell, K.M., Hedengren, J.D., and Edgar, T.F., "Dynamic Optimization of a Hybrid Solar Thermal and Fossil Fuel System", Solar Energy, DOI: 10.1016/j.solener.2014.07.004, Vol. 108, pp. 210–218, 2014. Article
  4. Hedengren, J.D., Asgharzadeh Shishavan, R., Powell, K.M., Edgar, T.F., Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014, DOI: 10.1016/j.compchemeng.2014.04.013. Preprint Article
  5. Sun, L., Hedengren, J. D., and Beard, R. W., Optimal Trajectory Generation using Model Predictive Control for Aerially Towed Cable Systems, Journal of Guidance, Control, and Dynamics, Vol. 37, Issue 2, pp. 525-539, 2014. Preprint, Article
2013
  1. Brower, D., Hedengren, J.D., Asgharzadeh Shishavan, R., and Brower, A., Advanced Deepwater Monitoring System, ASME 32st International Conference on Ocean, Offshore and Arctic Engineering, OMAE2013-10920, Nantes, France, June 2013, ISBN: 978-0-7918-5531-7. Preprint, Presentation
  2. Jacobsen, L. T. and Hedengren, J. D., Model Predictive Control with a Rigorous Model of a Solid Oxide Fuel Cell, American Control Conference (ACC), Washington, DC, pp. 3747–3752, 2013. Preprint, Presentation
  3. Kelly, J. D. and Hedengren, J. D., A Steady-State Detection (SSD) Algorithm to Detect Non-Stationary Drifts in Processes, Journal of Process Control, 23, 3, pp. 326–331, March 2013. Preprint, Article
  4. Powell, K. M., Hedengren, J. D., and Edgar, T. F., Dynamic Optimization of a Solar Thermal Energy Storage System over a 24 Hour Period using Weather Forecasts, American Control Conference (ACC), Washington, DC, pp. 2952-2957, 2013. Preprint
2012
  1. Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Constrained Control and Optimization of Tubular Solid Oxide Fuel Cells for Extending Cell Lifetime, American Control Conference (ACC), Montréal, Canada, pp. 1356-1361, July 2012. Preprint | Presentation
  2. Brower, D., Hedengren, J.D., Loegering, C., Brower, A., Witherow, K., and Winter, K., Fiber Optic Monitoring of Subsea Equipment, ASME 31st International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2012, Rio de Janiero, Brazil, Volume 1: Offshore Technology, Number: 84143, pp. 769-776, June 2012. Preprint | Presentation
2010
  1. Spivey, B. J., Hedengren, J. D. and Edgar, T. F., Constrained Nonlinear Estimation for Industrial Process Fouling, Industrial & Engineering Chemistry Research, 49 (17), pp 7824–7831, DOI: 10.1021/ie9018116, 2010. Abstract
2008
  1. Hedengren, J. D. and Edgar, T. F., Approximate Nonlinear Model Predictive Control with In Situ Adaptive Tabulation, Computers and Chemical Engineering, Volume 32, pp. 706-714, 2008. Abstract
2007
  1. Hedengren, J.D. Allsford, K.V., and Ramlal, J., Moving Horizon Estimation and Control for an Industrial Gas Phase Polymerization Reactor, Proceedings of the American Control Conference (ACC), New York, NY, pp. 1353-1358, July 2007. Preprint
2006
  1. Hedengren, J. D. and Edgar, T. F., Moving Horizon Estimation - The Explicit Solution, Proceedings of the CPC-VII, Lake Louise, Alberta, Canada, 2006. Preprint
2005
  1. Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Real-Time Control, Industrial & Engineering Chemistry Research, Ind. Eng. Chem. Res., Volume 44, Issue 8, pp. 2716 -2724, 2005. Abstract
  2. Hedengren, J. D. and Edgar, T. F., Order Reduction of Large Scale DAE Models, Computers and Chemical Engineering, Volume 29, Issue 10, pp. 2069-2077, 2005. Abstract
  3. Hedengren, J.D. and Edgar, T.F., Order Reduction of Large Scale DAE Models, IFAC 16th World Congress, Prague, Czechoslovakia, July, 2005. Preprint
2004
  1. Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Real-time Control, Proceedings of the American Control Conference (ACC), Boston, MA, pp. 2222-2227, July 2004. Preprint | Presentation

Conference Proceedings

2024
  1. Hedengren, J.D., Park, J., Perez, K., Generative AI for Process Systems Engineering: Potential Applications and Pitfalls, Emerging Technologies in Data Analytics, 2024 AIChE Spring Meeting, New Orleans, LA. Presentation
2023
  1. Hedengren, J.D., Fry, A., Perez, K., Hacioglu, A., Wang, J., Loftin, J., Machine Learning for Engineering course in MATLAB and Python, Education Division, 2023 AIChE Annual Meeting, Orlando, FL.
  2. Hedengren, J.D., Unlock Data to Optimize Industrial Processes, Energy Geoscience Institute (EGI), Invited Talk, University of Utah, Sept 2023.
  3. Hedengren, J.D., Data-Driven Engineering Education with Hands-On Learning, Plenary Talk, Past and Future of Process/Product Analytics & Machine Learning, including Education and Workforce Development, FOPAM 2023, Foundations of Process/Product Analytics and Machine learning, University of California, Davis. Presentation
  4. Hedengren, J.D., Learn Data-Driven Engineering with Interactive Modules, Industry 4.0 Topical Session, Analytics & AI, 2023 AIChE Spring Meeting, Houston, TX. Presentation
  5. Babaei, M.R., Park, J., Venkat, A., Hedengren, J.D., Framework for Hybrid Machine Learning with Open-Source Python Seeq Sysid Package, 2023 AIChE Spring Meeting, Houston, TX. Presentation
  6. Babaei, M.R., Mtetwa, F., Stone, R., Knotts, T.A., Hedengren, J.D., Physics-Informed Deep Learning for Prediction of Thermophysical Properties: Normal Boiling Point, 2023 AIChE Spring Meeting, Houston, TX. Presentation
  7. VanKeersblick, L., Clark, M., Hunter, I., Hedengren, J.D., Joint Angle Calculations Using Motion Capture and Deep Learning Pose Estimation for Safety Applications, Poster Session: Industry 4.0/Analytics & AI, 2023 AIChE Spring Meeting, Houston, TX. Presentation
  8. Hedengren, J.D., Physics-Informed Deep Learning for Optimization and Control, Automated Systems & Soft Computing Lab (ASSCL), College of Computer and Information Sciences (CCIS), Prince Sultan University, Feb 2023.
  9. Hedengren, J.D., Nicholson, B., Open-Source Modeling Platforms, Keynote Talk at FOCAPO / CPC 2023, San Antonio, TX, 8-12 January 2023. Preprint | Presentation
2022
  1. Knotts, T., Hedengren, J.D., Babaei, M.R., Physics-Informed Deep Learning for Prediction of Thermophysical Properties: The Parachor Method for Surface Tension, AIChE Annual Meeting, Phoenix, AZ, Nov 13-18, 2022.
  2. Yao, J., Gao, T., Hedengren, J.D., Powell, K., Two-Level Optimization Framework with Consideration of Economic Benefits and Long-Term Capacity Fading for Battery Energy Storage Systems, AIChE Annual Meeting, Phoenix, AZ, Nov 13-18, 2022.
  3. Ho, A., Mohammadi, K., Memmott, M., Hedengren, J.D., Powell, K., Dynamic Modeling and Simulation of a Novel Nuclear-Hydrogen Hybrid Energy System with Large-Scale Storage in an Underground Salt Cavern, AIChE Annual Meeting, Phoenix, AZ, Nov 13-18, 2022.
  4. Ho, A., Hill, D., Hedengren, J.D., Powell, K., An Optimal Dispatch and Economic Performance Study of a Nuclear-Hydrogen Hybrid Energy System with Large-Scale Storage in Underground Salt Cavern, AIChE Annual Meeting, Phoenix, AZ, Nov 13-18, 2022.
  5. Ho, A., Mohammadi, K., Memmott, M., Hedengren, J.D., Powell, K., Dynamic Modeling and Simulation of a Novel Nuclear-Hydrogen Hybrid Energy System with Large-Scale Storage in an Underground Salt Cavern, AIChE Annual Meeting, Phoenix, AZ, Nov 13-18, 2022.
  6. Serbezov, A., Zakova, K., Visioli, A., Rossiter, J.A., Douglas, B., Hedengren, J.D., Open access resources to support the first course in feedback, dynamics and control, Advanced in Control Education (ACE2022), Hamburg, Germany, 24-27 July 2022. Preprint
  7. Rossiter, J.A., Visioli, A., Serbezov, A., Hedengren, J.D., Douglas, B., Zakova, K., Open access resources to support learning of control engineering, 2022 European Control Conference (ECC), London, UK, July, 11-14, 2022. Article
  8. Granger, C., Martin, A., Hill, D., Wallace, J., Memmott, M., Hedengren, J.D., Optimal Dispatch with MPC Using Lab Scale Arduino Hardware, Process Modeling and Simulation IV, 2022 AIChE Spring Meeting, San Antonio, TX, April 2022.
2021
  1. Gates, N.S., Hill, D.C., Billings, B.W., Powell, K.M., Hedengren, J.D., Benchmarks for Grid Energy Management with Python Gekko, 60th Conference on Decision and Control (CDC), Austin, TX, USA, December 13-15, 2021. Preprint | Benchmarks
2020
  1. Wallace, J., Hill, D., Memmott, M., Hedengren, J., Modeling and Optimizing Molten Salt Thermal Storage for Nuclear Power, Transactions of the 2020 Winter ANS (American Nuclear Society) Meeting, November, 2020, Vol. 123, No. 1, pp. 144-145. Preprint | Article
  2. Hedengren, J.D., Teaching Dynamics and Control with Arduino-based TCLab, Invited Presentation at MathWorks Special Session, 59th Conference on Decision and Control, Jeju Island, Republic of Korea, December 14-18, 2020. Presentation
  3. Moura Oliveira, P., Hedengren, J., Boaventura, J., Bridging Theory to Practice: Feedforward and Cascade Control with TCLab Arduino Kit, 14th International Conference on Automatic Control and Soft Computing (CONTROLO), Bragança, Portugal, July 2020. Proceedings
  4. Moura Oliveira, P., Hedengren, J., Rossiter, J.A., Introducing Digital Controllers to Undergraduate Students Using the TCLab Arduino Kit, 21st IFAC World Congress, Berlin, Germany, Volume 53, Issue 2, July 12-17, 2020, pp. 17524-17529. Article
  5. Park, J., Lyman, J., Darby, M., Lima, L., Nelson, C., and Hedengren, J.D., Hybrid Machine Learning and Fundamental Modeling for Real-Time Optimization of a Fluidized Bed Roaster, 2020 Spring Meeting & 16th Global Congress on Process Safety, AIChE, Houston, TX, 29 March-2 April, 2020. Abstract
2019
  1. Hedengren, J.D., Martin, R.A., Kantor, J.C., Reuel, N., Temperature Control Lab for Dynamics and Control, AIChE Annual Meeting, Orlando, FL, Nov 2019. Abstract
  2. Oliveira, P.M., Hedengren, J.D., An APMonitor Temperature Lab PID Control Experiment for Undergraduate Students, 24th IEEE Conference on Emerging Technologies and Factory Automation (ETFA), Sep 10th - 13th, 2019, pp. 790-797, Zaragoza, Spain. Preprint | Paper
  3. Pastusek, P., Payette, G., Shor, R., Cayeux, E., Aarsnes, U.J., Hedengren, J.D., Menand, S., Macpherson, J., Gandikota, R., Behounek, M., Harmer, R., Detournay, E., Illerhaus, R., Liu, Y., Creating Open Source Models, Test Cases, and Data for Oilfield Drilling Challenges, SPE/IADC Drilling Conference, The Hague, Netherlands, March 2019, SPE-194082-MS. Article
  4. Rossiter, J.A., Jones, B.L., Pope, S., Hedengren, J.D., Evaluation and Demonstration of Take Home Laboratory Kit, Invited Session: Demonstration and poster session, 12th IFAC Symposium on Advances in Control Education, July 7-9, 2019, 52 (9), pp. 56-61, Philadelphia, PA, USA. Preprint
  5. Gates, N.S., Moore, K.R., Ning, A., Hedengren, J.D., Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long Endurance Unmanned Aircraft, AIAA Science and Technology Forum (SciTech), 2019. Preprint
  6. Tubbs, B., Hedengren, J.D., Data-Driven Operations Management and Production Optimization, Operations: Case Studies and Best Practices, Canadian Institute Of Mining Metallurgy And Petroleum Conference Convention, CIM Convention, Montreal, Canada, 2019.
  7. Park, J., Hansen, B., Gates, N., Darby, M., Hedengren, J.D., Use of Nonlinear and Machine Learning Techniques for Improved APC Modeling, AIChE Spring Meeting, New Orleans, LA, April 2019. Abstract
  8. Park, J., Patterson, C., Kelly, J., Hedengren, J.D., Closed-Loop PID Re-Tuning in a Digital Twin By Re-Playing Past Setpoint and Load Disturbance Data, AIChE Spring Meeting, New Orleans, LA, April 2019. Abstract
2018
  1. Martin, R.A., Heiner, B., Hedengren, J.D., Targeted 3D Modeling from UAV Imagery, Proc. SPIE 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII, 106450D (27 April 2018); doi: 10.1117/12.2304436 Article
  2. Blackburn, L., Hedengren, J.D., Powell, K.M., Real-time Optimization of Chillers with Thermal Energy Storage and Variable Electricity Rates, Smart City & Sustainable Communities, INFORMS 2018 Annual Meeting, Phoenix, AZ, USA, Nov. 4-7, 2018.
2017
  1. Safdarnejad, S.M., Strahl, W., Hedengren, J.D., Baxter, L.L., Comparison in Dynamic Response of Energy-Storing Cryogenic and Chemical Absorption Carbon Capture Systems to Electricity Demand, AIChE Annual Meeting, Minneapolis, MN, Nov 2017. Presentation Abstract
  2. Incorporating Dynamic Simulation into Chemical Engineering Curricula, Hedengren, J.D., Badgwell, T.A., Grover, M., Braatz, R., ASEE Summer School for New Chemical Engineering Faculty, Raleigh, North Carolina, July 2017. Abstract
  3. Aghito, M., Bjørkevoll, K.S., Nybø, R., Eaton, A., Hedengren, J.D., Automatic Model Calibration for Drilling Automation, SPE Bergen One Day Seminar, Bergen, Norway, 5 April 2017. Article
  4. Okeson, T., Barrett, B., Blackburn, L., Hedengren, J.D., Franke, K., Optimized Infrastructure Monitoring: 3D Modeling in Complex Environments, Center for Unmanned Aircraft Systems (C-UAS), Atlanta, GA, 8 Feb 2017. Presentation
  5. Beal, L., Clark, J., Anderson, M., Warnick, S., Hedengren, J.D., Combined Scheduling and Control with Diurnal Constraints and Costs using a Discrete Time Formulation, FOCAPO / CPC 2017, Tucson, AZ, Jan 2017.
  6. Udy, J., Blackburn, L., Hedengren, J.D., Darby, M., Reduced Order Modeling for Reservoir Injection Optimization and Forecasting, FOCAPO / CPC 2017, Tucson, AZ, Jan 2017. Preprint
  7. Park, J., Webber, T.R., Asgharzadeh Shishavan, R., Hedengren, J., Improved Bottomhole Pressure Control with Wired Drillpipe and Physics-Based Models, SPE-184610-MS, SPE/IADC Drilling Conference and Exhibition, The Hague, The Netherlands, 14-16 March 2017. Paper | Presentation
  8. Franke, K., Nguyen, T., Shao, L., Bender, C., Wolfe, D., Hedengren, J.D., Reimschiissel, B., The Use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) to Measure Volume Change at a Deep Dynamic Compaction Site, Geotechnical Frontiers, March 12-15, 2017, Orlando, Florida.
2016
  1. Eaton, A.N., Park, J., Thorpe, S., Webber, T., Safdarnejad, S.M., Hedengren, J.D., High-Speed Data and High-Fidelity Models: Opportunities and Challenges in Well Manufacturing, AIChE Spring Meeting, Houston, TX, April 2016. Presentation Abstract
  2. Safdarnejad, S.M., Richards, J., Griffiths, J., Hedengren, J.D., Baxter, L.L., Increased Stability of a Power Grid by Energy Storage of Cryogenic Carbon Capture, AIChE Spring Meeting, Houston, TX, April 2016. Presentation Abstract
  3. Nikbakhsh, S., Hedengren, J.D., Darby, M., Udy, J., Constrained Model Identification Using Open-Equation Nonlinear Optimization, AIChE Spring Meeting, Houston, TX, April 2016. Presentation Abstract
  4. Martin, R.M., Hall, A., Brinton, C., Franke, K., and Hedengren, J.D., Privacy Aware Mission Planning and Video Masking for UAV Systems, UMS-01, Unmanned Systems: Mission Management and Planning Technologies, Jan 4, 2016, AIAA Infotech at Aerospace, AIAA Science and Technology Forum and Exposition 2016, San Diego, California, USA, 4-8 Jan 2016, DOI: 10.2514/6.2016-0250. Article
2015
  1. Safdarnejad, S.M., Hedengren, J.D., Baxter, L.L., Dynamic Optimization of the Hybrid System of a Baseline Power Generation Unit and Cryogenic Carbon Capture, Western Section of the Combustion Institute, Fall 2015 Meeting, Provo, UT, October 5-6, 2015.
  2. Eaton, A.N., Beal, L., Janis, E., Hubbell, C., Hedengren, J.D., Nybø, R., Aghito, M., Bjørkevoll, K., Addressing Control Challenges of Discontinuous Processes with Multi-Fidelity Model Predictive Control, Modeling, Control and Optimization of Energy Systems II, AIChE Annual Meeting, Salt Lake City, UT, Nov 2015. Abstract, Presentation
  3. Park, J., Safdarnejad, M., Asgharzadeh Shishavan, R., Hedengren, J.D., Rastegar, R., Snell, A., Nonlinear Model Predictive Control of Managed Pressure Drilling Based on Hammerstein-Wiener Piecewise Linear Models, AIChE Annual Meeting, Salt Lake City, UT, Nov 2015. Abstract, Presentation
  4. Safdarnejad, M., Gallacher, J., Hedengren, J.D., Baxter, L.B., A New Framework for Dynamic Parameter Estimation and Optimization of Batch Distillation Columns, AIChE Annual Meeting, Salt Lake City, UT, Nov 2015. Abstract
  5. Safdarnejad, M., Hedengren, J.D., Baxter, L.B., Reduction in Cycling of the Boilers By Using Large-Scale Energy Storage of Cryogenic Carbon Capture, AIChE Annual Meeting, Salt Lake City, UT, Nov 2015. Abstract, Presentation
  6. Eaton, A., Beal, L., Thorpe, S.D., Janis, E.H., Hubbell, C., Hedengren, J.D., Nybø, R., Aghito, M., Bjørkevoll, K., El Boubsi, R., Braaksma, J., and van Og, G., Ensemble Model Predictive Control for Robust Automated Managed Pressure Drilling, SPE Annual Technical Conference and Exhibition (ATCE), SPE-174969-MS, Houston, TX: 28-30 Sept 2015.
  7. Franke, K, Hedengren, J.D. and Farrell, R., UAS-Based Infrastructure Monitoring, Center for Unmanned Aircraft Systems (C-UAS), Arlington, VA, Feb 2015. Presentation
  8. Sugiura, J., Samuel, R., Oppelt, J., Ostermeyer, G.P., Hedengren, J.D., and Pastusek, P., Drilling Modeling and Simulation: Current State and Future Goals, SPE IADC Drilling Conference and Exhibition, SPE-173045, 17-19 March 2015, UK, London. Article
  9. Safdarnejad, S.M., Hedengren, J.D., Baxter, L., Effect of Cryogenic Carbon Capture (CCC) on Smart Power Grids, AIChE Spring Meeting, Austin, TX, April 2015. Abstract
2014
  1. Franke, K, Hedengren, J.D. and Farrell, R., LiDAR-like Accuracy with Photogrammetric Methods for Infrastructure Monitoring, Center for Unmanned Aircraft Systems (C-UAS), Snowbird, UT, Aug 2014.
  2. Asgharzadeh Shishavan, R., Perez, H., and Hedengren, J.D., Multivariate nonlinear model predictive controller for managed drilling processes, AIChE Annual Meeting, Atlanta, GA, Nov 2014. Abstract Presentation
  3. Nikbakhsh, S. and Hedengren, J.D., Genetic fuzzy decoupling of nonlinear multiple-input multiple-output processes, AIChE Annual Meeting, Atlanta, GA, Nov 2014. Abstract
  4. Safdarnejad, S.M., Hall, T., Hedengren, J.D., Baxter, L., Dynamic Optimization of Cryogenic Carbon Capture with Large-scale Adoption of Renewable Power, AIChE Annual Meeting, Atlanta, GA, Nov 2014. Abstract
  5. Hedengren, J.D., Model Predictive Control in Drilling, SPE Annual Technical Conference and Exhibition (ATCE), Amsterdam, The Netherlands: 27-29 Oct 2014. Invited Session
  6. Asgharzadeh Shishavan, R., Hubbell, C., Perez, H.D., Hedengren, J.D., Pixton, D.S., and Pink, A.P., Multivariate Control for Managed Pressure Drilling Systems Using High Speed Telemetry, SPE Annual Technical Conference and Exhibition (ATCE), Amsterdam, The Netherlands: 27-29 Oct 2014. Article
  7. Asgharzadeh Shishavan, R., Hubbell, C., Perez, H.D., Hedengren, J.D., and Pixton, D.S., Combined Rate of Penetration and Pressure Regulation for Drilling Optimization Using High Speed Telemetry, SPE Deepwater Drilling and Completions Conference, Galveston, TX: 10-11 Sept 2014. Article
  8. Franke, K, Hedengren, J.D. and Farrell, R., Infrastructure Monitoring: Sensing for Change Detection, Volume Estimation, and Proactive Remediation, Center for Unmanned Aircraft Systems (C-UAS), Boulder, CO, Jan 2014. Presentation
  9. Mojica, J.L. and Hedengren, J.D., APMonitor: Modeling Platform for Dynamic Optimization, Invited Session on Optimization Modeling Languages and Software at APMOD 2014, 11th International Conference on Applied Mathematical Optimization and Modelling, 9-11 April 2014, Warwick Business School, Coventry, UK. Abstract
  10. Pixton, D., Asgharzadeh Shishavan, R., Hedengren, J.D., and Craig, A., Addressing UBO and MPD Challenges with Wired Drillpipe, SPE/IADC MPD & UBO Conference & Exhibition, Madrid, Spain: 8 - 9 Apr 2014. Article
  11. Asgharzadeh Shishavan, R. and Hedengren, J.D., Improved Estimator Insensitivity to Outliers, Measurement Drift, and Noise, AIChE Spring Meeting, New Orleans, LA, April 2014. Abstract
  12. Asgharzadeh Shishavan, R., Memmott, J.A., Hedengren, J.D., and Pixton, D., Pressure Regulation and Kick Attenuation with Wired Pipe Technology in Managed Pressure Drilling, AIChE Spring Meeting, New Orleans, LA, April 2014. Abstract
  13. Brower, D., Brower, A., Memmott, J.A., Asgharzadeh Shishavan, R., and Hedengren, J.D., Advanced Monitoring Systems on Existing Deepwater Infrastructure for Intelli-Field Advances, AIChE Spring Meeting, New Orleans, LA, April 2014. Abstract
2013
  1. Mojica, J.L., Chen, M., Petersen, D., Hedengren, J.D., Planning of Capacity Investments using a Model Predictive Control Approach, INFORMS Annual Meeting, Minneapolis, MN, Oct 2013. Abstract | Session | Presentation
  2. Hedengren, J.D., Mojica, J.L., Lewis, A.D. and Nikbakhsh, S., MINLP with Combined Interior Point and Active Set Methods, INFORMS Annual Meeting, Minneapolis, MN, Oct 2013. Abstract | Session | Presentation
  3. Hedengren, J.D. and Franke, K., Infrastructure Monitoring: Displacement Detection with Optical Sensors, Center for Unmanned Aircraft Systems (C-UAS), Snowbird, UT, Aug 2013. Presentation
  4. Martin, R.A., Pulsipher, J., Lund, C., Clark, J., Hedengren, J.D., and Franke, K., UAV-Based Infrastructure Monitoring, Poster Session: Center for Unmanned Aircraft Systems (C-UAS), Snowbird, UT, Aug 2013. Poster 1 Poster 2
  5. Mojica, J.L., Greenquist, I., Hedengren, J.D., Dynamic Optimization: Energy System Planning Under Uncertainty, INEST Nuclear Hybrid Energy Systems CORE Workshop, Idaho Falls, ID, July 2013. Presentation
  6. Greenquist, I., Hedengren, J.D., Opportunities for Hybrid Nuclear System Integration in the Petrochemical Industry, INEST Nuclear Hybrid Energy Systems CORE Workshop, Idaho Falls, ID, July 2013. Poster
  7. Hedengren, J.D., Monitoring Energy Infrastructure, Invited Session, Clear Gulf Joint Industry Project Review Meeting, Johnson Space Center, Houston, TX, April 2013.
  8. Hedengren, J.D., Mojica, J.L., Asgharzadeh Shishavan, R., Safdarnejad, S.M., Recent Advances in the Application of MIDAE Systems, AIChE National Meeting, San Francisco, CA, Nov 2013. Abstract
  9. Mojica, J.L., Hedengren, J.D., A Model Predictive Control Approach for Long Term Planning of Capacity Investments in a District Heating System, AIChE National Meeting, San Francisco, CA, Nov 2013. Abstract
  10. Hedengren, J.D., Dynamic Data Reconciliation and Optimization, Invited Lecture at the University of Utah, Graduate Seminar, 30 Oct 2013. Presentation
  11. Hedengren, J.D., Dynamic Optimization Across Disciplines, Invited Lecture at Oklahoma State University, Graduate Seminar, 17 Sept 2013. Abstract Presentation
2012
  1. Abbott, C.S., Haseltine, E.L., Martin, R.A., and Hedengren, J.D., New Capabilities for Large-Scale Models in Computational Biology, Computing and Systems Technology Division, AIChE National Meeting, Pittsburgh, PA, Oct 2012. Session | Abstract
  2. Asgharzadeh Shishavan, R. and Hedengren, J.D., Nonlinear Model Predictive Control of a Thermal Oxidizer System, Computing and Systems Technology Division, AIChE National Meeting, Pittsburgh, PA, Oct 2012. Session | Abstract
  3. Powell, K.M., Hedengren, J.D., and Edgar, T.F., Dynamic Optimization of Solar Thermal Systems with Storage, Computing and Systems Technology Division, AIChE National Meeting, Pittsburgh, PA, Oct 2012. Session | Abstract
  4. Hedengren, J.D., Mojica, J.L., Cole, W., Edgar, T.F., APOPT: MINLP Solver for Differential Algebraic Systems with Benchmark Testing, INFORMS Annual Meeting, Phoenix, AZ, Oct 2012. Abstract | Session | Presentation
  5. Hedengren, J.D., APMonitor Modeling Language for Mixed-Integer Differential Algebraic Systems, Computing Society Sponsored Session on Optimization Modeling Software: Design and Applications, INFORMS Annual Meeting, Phoenix, AZ, Oct 2012. Abstract | Session | Presentation
  6. Liang Sun, Hedengren, J.D., Beard, R.W., Real-time Moving Horizon Estimation for an Unmanned Aerial System, OPTEC Workshop on Moving Horizon Estimation and System Identification, Leuven, Belgium, Aug 2012. Abstract
  7. Hedengren, J.D., A Simulation Platform to Enhance Engineering Laboratory Experiences, ASEE: American Society for Engineering Education, Summer School, Orono, Maine, July 2012. Abstract | Poster
  8. Jensen, K.R. and Hedengren, J.D., Improved Load Following of a Boiler with Advanced Process Control, AIChE Spring Meeting, Houston, TX, April 2012. Abstract | Presentation
  9. Hedengren, J.D., Brower, D., and Mojica, J., Advanced Process Monitoring of Flow Assurance with Fiber Optics, AIChE Spring Meeting, Houston, TX, April 2012. Abstract | Presentation
2010
  1. Soderstrom, T.A., Zhang, Y., and Hedengren, J.D., Advanced Process Control in ExxonMobil Chemical Company: Successes and Challenges, CAST Division, AIChE National Meeting, Salt Lake City, UT, Nov 2010. Presentation
2009
  1. Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Monitoring of Process Fouling Using First-Principles Modeling and Moving Horizon Estimation, Proc. Applications of Computer Algebra (ACA) Conference, Montréal, Canada, 2009.
  2. Spivey, B.J., Hedengren, J.D., and Edgar, T.F., Monitoring of Process Fouling Using First-Principles Modeling and Moving Horizon Estimation, Proc. Texas, Wisconsin, California Control Consortium (TWCCC), Austin, TX, February 2009.
2007
  1. Ramlal, J., Naidoo, V., Allsford, K.V., and Hedengren, J.D., Moving Horizon Estimation for an Industrial Gas Phase Polymerization Reactor, Proc. IFAC Symposium on Nonlinear Control Systems Design (NOLCOS), Pretoria, South Africa, 2007. Preprint
2005
  1. Hedengren, J.D. and Edgar, T.F., Order Reduction of a Large-Scale Index-2 DAE Model, Computing and Systems Technology Division, AIChE National Meeting, Cincinnati, OH, Nov 2005.
  2. Hedengren, J. D. and Edgar, T. F., Efficient Moving Horizon Estimation of DAE Systems, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Austin, TX, Feb 2005.
2004
  1. Hedengren, J. D. and Edgar, T. F., Adaptive DAE Model Reduction, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Madison, WI, Sept 2004.
  2. Hedengren, J. D. and Edgar, T. F., Order Reduction of Large Scale DAE Models, Computing and Systems Technology Division, AIChE National Meeting, Austin, TX, Nov 2004.
  3. Hedengren, J. D. and Edgar, T. F., Dependency Analysis for DAE to ODE Conversion and Model Reduction, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Austin, TX, Feb 2004.
2003
  1. Hedengren, J. D., In Situ Adaptive Tabulation for Real-time Control, Admission to Candidacy, 9 Dec. 2003 - Himmelblau Library (CPE 4.446).
  2. Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Nonlinear MPC, Poster Session: Systems and Process Control, AIChE National Meeting, San Francisco, CA, Nov 2003.
  3. Hedengren, J. D. and Edgar, T. F., In Situ Adaptive Tabulation for Nonlinear MPC, Texas-Wisconsin Modeling and Control Consortium (TWMCC), Madison, WI, Sept 2003.
2002
  1. Hedengren, J. D., Beckstead, M. W., and Spinti, J., Implementation of Automatically Simplified Chemical Kinetics through Intrinsic Low-Dimensional Manifolds for Gaseous HMX, Joint Army-Navy-NASA-Air Force (JANNAF) 20th Propulsion Systems Hazards Subcommittee (PSHS), 38th JANNAF Combustion Subcommittee Meeting, and 2nd Modeling and Simulation Subcommittee Meeting, Destin, FL, Apr 2002. Preprint

Patents

  1. Lawson, K. W., Hedengren, J. D., Smith, L. C., Method for Controlling Bubble Formation in Polymerization Reactors, International Patent WO2012005740, Issued January 12, 2012, United States Patent Application 20130203946, Issued August 8, 2013.

Other Publications

  1. Hedengren, J.D., Kantor, J., Computer Programming and Process Control Take-Home Lab, Computer Aids for Chemical Engineering (CACHE) News, Summer 2020. Article
  2. Parkinson, A., Balling, R., Hedengren, J.D., Optimization Methods for Engineering Design, Brigham Young University, Edition 1 (2013), Edition 2 (2018). Book
  3. Derricott, J.C., Willis, J.B., Peterson, C.K., Franke, K.W., Hedengren, J.D., Disaster Reconnaissance Using Multiple Small Unmanned Aerial Vehicles, Mechanical Engineering Magazine, 141, 16, doi: 10.1115/1.2019-JUN5, 2019. Article
  4. Yu, J., Karra, S., Huang, R., and Hedengren, J.D., Guest Editors for Special Issue section on Advanced Process Control, Control Engineering Practice, 2013. Abstract
  5. Hedengren, J. D., A Nonlinear Model Library for Dynamics and Control, Computer Aids for Chemical Engineering (CACHE) News, Summer 2008. Link
  6. Contributor to: Beucher, O. and M. Weeks, Introduction to MATLAB & SIMULINK: A Project Approach, 3rd Edition, Infinity Science Press, 2008.

Education

  • The University of Texas at Austin, Austin, TX
    • Doctor of Philosophy in Chemical Engineering, May 2005 GPA: 4.0/4.0
    • Hedengren, J. D., Real-Time Estimation and Control of Large-Scale Nonlinear DAE Systems, Doctoral Dissertation, The University of Texas at Austin, 2005. Download PDF
  • Brigham Young University, Provo, Utah
    • Bachelor of Science in Chemical Engineering, May 2001 GPA: 3.96/4.00
    • Master of Science in Chemical Engineering, Aug. 2002 GPA: 3.90/4.00
    • Hedengren, J. D., Implementation of Automatically Simplified Chemical Kinetics through Intrinsic Low-Dimensional Manifolds for Gaseous HMX, Masters Thesis, Brigham Young University, 2002. Download PDF

Experience

  • Assistant Professor (2011-16) / Associate Professor (2016-present), Brigham Young University, Provo, UT
    • Develop efficient modeling and optimization methods for large-scale dynamic systems
    • Analyze measurements of complex systems to gain fundamental process insight
    • Design, monitor, and optimize energy systems
  • ExxonMobil Chemical Senior Engineer, Baytown, Texas (April 2007-August 2011)
    • Developed advanced process control for polymer production
    • Worked with plant operators and technical specialists to commission nonlinear control (NLC) applications
  • APMonitor Software Developer, Web-site, Houston, Texas (Feb 2007-March 2007)
    • Developed innovative modeling, simulation, and control software
    • Applied software to monitor developmental and industrial applications
  • Advanced Process Control and Optimization Software Development, PAS, Inc., Clearlake, TX (May 2005-Jan 2007)
    • Developed first principles models for homopolymer and impact co-polymer polypropylene reactors
    • Commissioned 3 Unipol polypropylene nonlinear model predictive controllers (NMPC)
    • Conducted APC training seminars for internal and external clients
    • Worked on a team to commission a HIPS (High-Impact Polystyrene) APC application
  • Advanced Process Control Research, University of Texas at Austin, Austin, TX (Sept. 2002-May 2005)
    • Developed methods to significantly reduce nonlinear model predictive control (MPC) computational time
    • Explored large-scale model reduction for differential algebraic models (DAEs)
    • Currently developing real-time advanced control strategies for industrial use
  • ExxonMobil Process Control Internship, Baytown, Texas (April 2004-June 2004)
    • Developed advanced process control (APC) for polymer production
    • Worked with plant operators and technical specialists to develop a model
    • Trained fellow engineers to use advanced control technology
  • Rocket Propellant Combustion Modeling, Brigham Young University, Provo, UT (May 2001-Aug. 2002)
    • Worked on University of Utah’s ASCI C-SAFE program (www.csafe.utah.edu)
    • Explored ‘time to detonation’ of a rocket motor in a pool fire
    • Developed an algorithm to reduce computational time of a chemistry calculation by ten times
  • CH2MHill Internship, Hanford, Washington (June 2000-Aug. 2000)
    • Determined pipe flushing requirements for radioactive waste
    • Worked on a team to maintain liquid pumping from radioactive waste tanks
  • BNFL Inc. Internship, Hanford, Washington (June 1999-Aug. 1999)
    • Performed design work for a vitrification facility through extensive corrosion analysis
    • Prepared reports for the US Department of Ecology and other clients
  • BYU DIPPR Thermophysical Properties Lab, Brigham Young University, Provo, UT (April 1999-June 1999)
    • Predicted surface tensions for over 700 compounds using Parachor values