PRISM Group at BYU
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%width:30px%Attach:pdf.png [[Attach:prism_newsletter_2021_11.pdf|BYU PRISM Newsletter (November 2021)]]
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%width:30px%Attach:pdf.png [[Attach:prism_newsletter_2021_11.pdf|BYU PRISM Newsletter]]
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%width:30px%Attach:pdf.png [[Attach:prism_newsletter_2021_12.pdf|BYU PRISM Newsletter (December 2021)]]
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%width:30px%Attach:pdf.png [[Attach:prism_newsletter_2021_11.pdf|BYU PRISM Newsletter (November 2021)]]
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[[Attach:prism_newsletter_2021_12.pdf|BYU PRISM Newsletter (December 2021)]]
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%width:30px%Attach:pdf.png [[Attach:prism_newsletter_2021_12.pdf|BYU PRISM Newsletter (December 2021)]]
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Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science
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Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science.
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Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science applied to:
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Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science
[[Attach:prism_newsletter_2021_12.pdf|BYU PRISM Newsletter (December 2021)]]
Some of the recent research applications include:
[[Attach:prism_newsletter_2021_12.pdf|BYU PRISM Newsletter (December 2021)]]
Some of the recent research applications include:
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John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab)]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control.
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[[Members/JohnHedengren|John Hedengren]] leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab)]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control.
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John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab)]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control.
John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab)]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control.
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||%width=180px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab) Arduino microcontroller]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control. ||
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||%width=180px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab)]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab) Arduino microcontroller]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control. ||
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||%width=180px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab) Arduino microcontroller]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, data science, and machine learning are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, and machine learning are accessed by 10,000 learners each day. The [[https://apmonitor.com/heat.htm|Temperature Control Lab (TCLab) Arduino microcontroller]] is used at 70 universities and by 3000 professionals to learn programming, data science, dynamics, and control. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. The [[Site/OnlineCourses|online courses]] on programming, optimization, dynamics, control, data science, and machine learning are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=200px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=250px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=200px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques advance the area of Process Systems Engineering (PSE).
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The group includes graduate and undergraduate students who are taking a lead role in data science, machine learning, optimization, estimation, and control applications. The PRISM group also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques advance the area of Process Systems Engineering (PSE).
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||%width=250px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. ||
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||%width=250px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. His [[Site/OnlineCourses|online courses]] are accessed by 10,000 learners each day and the TCLab Arduino module is used at 70 universities. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. ||
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||%width=250px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. ||
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||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. He served as a Society of Petroleum Engineers (SPE) Distinguished Lecturer for 2018-2019 and completed a sabbatical in 2020 to collaboratively develop combined physics-based and machine learned methods for optimization and automation. ||
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John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011.
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|| border=0
||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. ||
||%width=150px%Attach:john_hedengren2021.jpg ||John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011. ||
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Increased computational resources and machine learning methods have triggered a new era of data science that has transformative potential across many fields, but these possibilities have yet to come to fruition because physics-based and other a priori information cannot be incorporated into the current machine learning algorithms. Hybrid machine learning developed in the BYU PRISM group overcomes current limitations by including physics-based activation functions and developing solver methods for hybrid deep learning.
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Increased computational resources and machine learning methods have triggered a new era of data science that has transformative potential across many fields, but these possibilities have yet to come to fruition because physics-based and other a priori information cannot be incorporated into the current machine learning algorithms. Hybrid machine learning developed in the BYU PRISM group overcomes current limitations by including physics-based activation functions and developing solver methods for hybrid deep learning.
Attach:john_hedengren2021.jpg
John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011.
Attach:john_hedengren2021.jpg
John Hedengren leads the [[https://apm.byu.edu|BYU PRISM group]] with interests in combining data science, optimization, and automation. He earned a doctoral degree at the University of Texas at Austin and worked 5 years with ExxonMobil Chemical prior to joining BYU in 2011.
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science applied to:
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Process Research and Intelligent Systems Modeling (PRISM) is a collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science applied to:
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Increased computational resources and machine learning methods have triggered a new era of data science that has transformative potential across many fields, but these possibilities have yet to come to fruition because physics-based and other a priori information cannot be incorporated into the current machine learning algorithms. Hybrid machine learning developed in the BYU PRISM group overcomes current limitations by including physics-based activation functions and developing solver methods for hybrid deep learning.
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* [[Projects/DeepwaterMonitoring|Fiber Optic Sensors]]
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* [[Projects/DeepwaterMonitoring|Fiber Optic Sensing for Infrastructure Monitoring]]
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* [[Projects/DeepwaterMonitoring|Flow assurance]]
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* [[Projects/DeepwaterMonitoring|Fiber Optic Sensors]]
* [[Projects/HybridNuclear|Hybrid Nuclear Energy Systems]]
* [[https://machinelearning.byu.edu|Optimization Methods]]
* [[Projects/HybridNuclear|Hybrid Nuclear Energy Systems]]
* [[https://machinelearning.byu.edu|Optimization Methods]]
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to:
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control, optimization, cybersecurity, estimation, digital twin modeling, machine learning, and data science applied to:
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The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group is also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques advance the area of Process Systems Engineering (PSE).
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The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques advance the area of Process Systems Engineering (PSE).
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%width=550px%Attach:prism_group2017.png
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* [[Projects/BiologicalSystems|Computational biology]]
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* [[Projects/HydraulicRodPumping|Artificial Lift]]
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Attach:prism_group2016.png
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* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to [[Projects/BiologicalSystems|Computational biology]], [[Projects/DrillingAutomation|Drilling automation]], [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]], [[Projects/DeepwaterMonitoring|Flow assurance]], [[Projects/DynamicEnergyStorage|Sustainable energy systems]], and [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]].
to:
Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to:
* [[Projects/BiologicalSystems|Computational biology]]
* [[Projects/DrillingAutomation|Drilling automation]]
* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
* [[Projects/DeepwaterMonitoring|Flow assurance]]
* [[Projects/DynamicEnergyStorage|Sustainable energy systems]]
* [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]]
* [[Projects/BiologicalSystems|Computational biology]]
* [[Projects/DrillingAutomation|Drilling automation]]
* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
* [[Projects/DeepwaterMonitoring|Flow assurance]]
* [[Projects/DynamicEnergyStorage|Sustainable energy systems]]
* [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]]
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to:
* [[Projects/BiologicalSystems|Computational biology]]
* [[Projects/DrillingAutomation|Drilling automation]]
* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
* [[Projects/DeepwaterMonitoring|Flow assurance]]
* [[Projects/DynamicEnergyStorage|Sustainable energy systems]]
* [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]]
*
to:
Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to [[Projects/BiologicalSystems|Computational biology]], [[Projects/DrillingAutomation|Drilling automation]], [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]], [[Projects/DeepwaterMonitoring|Flow assurance]], [[Projects/DynamicEnergyStorage|Sustainable energy systems]], and [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]].
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* Drilling automation and flow assurance
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* [[Projects/DrillingAutomation|Drilling automation]]
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* [[Projects/DeepwaterMonitoring|Flow assurance]]
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* Biological and medical systems
* Sustainable energy systems
* Improved petrochemical manufacture
* Enhanced recovery of oil and gasreserves
Unmanned Aerial Vehicle (UAV) control
* Sustainable energy systems
* Enhanced recovery of oil and gas
to:
* [[Projects/BiologicalSystems|Computational biology]]
* Drilling automation and flow assurance
* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
* [[Projects/DynamicEnergyStorage|Sustainable energy systems]]
* [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]]
* Drilling automation and flow assurance
* [[http://dev.cheme.byu.edu/international-reservoir-simulation-research-institute|Enhanced recovery of oil and gas reserves]]
* [[Projects/DynamicEnergyStorage|Sustainable energy systems]]
* [[Projects/PathPlanning|Unmanned Aircraft Systems (UAS)]]
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The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group is also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques provide meaningful advancements in the area of Process Systems Engineering (PSE).
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The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group is also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques advance the area of Process Systems Engineering (PSE).
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Process Research and Intelligent Systems Modeling (PRISM) is developing a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to:
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Process Research and Intelligent Systems Modeling (PRISM) is a world class collaborative research group for the application of innovative advanced process control and optimization techniques to be applied to:
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The group includes graduate and undergraduate students who are taking a development role in the specific applications mentioned above. The PRISM group is also involved in the development of novel algorithms and techniques for large-scale and complex systems. These applications and techniques have the common objective of providing meaningful advancements in the area of Process Systems Engineering (PSE).
to:
The group includes graduate and undergraduate students who are taking a lead role in the specific applications mentioned above. The PRISM group is also develops novel algorithms and techniques for large-scale and complex systems. These applications and techniques provide meaningful advancements in the area of Process Systems Engineering (PSE).
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* Control Engineering Practice (CEP) Special Issue
** Topic: [[Attach:CEPCallForPapers2012.pdf | Applications of advanced process control technology on industrial systems]]
** Submission Due Date: August 15, 2012
* PRISM Group Visitors
** [[Attach:JeffRenfro2012.pdf | Jeff Renfro (Honeywell) - March 8, 2012]]
** [[http://www.linkedin.com/pub/mark-darby/1/92/521 | Mark Darby (CMiD Solutions) - March 13-14,2012]]
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[[Attach:prism_poster.pdf|Attach:prism_poster.png]]
