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PRISM Group APMonitor.com prism.groups.et.byu.net
Process Research and Intelligent Systems Modeling Group Process Systems Engineering
Department of Chemical Engineering, Brigham Young University, Provo, UT, 84602
Dr. John D. Hedengren
Department of Chemical Engineering
350 Clyde Building
Brigham Young University
Provo, UT 84602
Boundary Management interfaces to live systems to
provide advanced diagnostics, meet safety and
environmental constraints, and drive the process to
economic optimum. With changing boundary
constraints, this enables instant and continual
realignment to real operating objectives.
Boundary Management may include fixed or dynamic
constraints. Fixed constraints may include pressure relief
valve burst limits, temperature limits for catalyst deactivation,
or environmental emissions levels. Dynamic constraints may
change constantly. A couple examples include bubble point
for a liquid reactor (changes with composition), operating
conditions for hydrate formation in upstream production, and
start-up or shut-down constraints. Dynamic boundary
management requires a modeling platform for rigorous or
empirical process models, even for large-scale or complex
systems.
Unmanned aerial systems may consist of multiple agents with
coordinated actions. Modeling and control of the system leads to
increasingly complex systems that may be posed as an optimization
problem. In collaboration with BYU’s MAGICC Lab, the groups are
solving the problems with APMonitor modeling language to demonstrate
that complex dynamic systems can perform coordinated and optimal
actions to achieve a shared objective.
One of the major drawbacks to solar
or wind energy is the intermittent
nature of the supply. Energy storage
allows an intermittent source of
energy to be harvested and re-
distributed in accordance with some
demand schedule. The aim of this
research is in creating models and
novel algorithms for Model Predictive
Control and optimization of energy
generating systems such as combined
heat and power plants (CHP) and
solar power plants. The optimization is
targeted at better integrating energy
storage, demand and weather
forecasts, and economic constraints
to increase profitability and energy
conservation.
“Developments in optimization and advanced
control of energy generation systems will
enable the launch of a “smart grid” to bring
the nation’s electricity delivery system into the
21st century” – US Department of Energy
Jose Mojica
MS student
A solid oxide fuel cell (SOFC)
produces electricity directly
from oxidizing a fuel at high
temperatures. The largest
challenge is preserving oxide
integrity and fuel cell lifetime.
SOFC modeling is used to
maintain performance and
operational integrity subject to
load-following, efficiency
maximization, and
disturbances.
Lee Jacobsen
BS graduate
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Biomedical research has generated
a vast amount of experimental data
that can reveal reaction pathways,
molecular transport, and population
dynamics. While simulations of
these biological systems have been
successfully applied for many years,
the alignment to available
measurements for complex systems
continues to be a challenge.
The aim of this project is to apply the
most advanced solution techniques from
the hydrocarbon processing industry to
computational biology by using
APMonitor, a cutting-edge software
package used by petrochemical
companies for large-scale models of
differential and algebraic equations
(DAEs).
Casey Abbott
BS student
David Grigsby
BS graduate
Reza Asgharzadeh
PhD student
James Memmott
BS student
Trevor Slade
BS graduate
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Petroleum exploration and production critically
depends on pipelines to bring oil from remote and
often inhospitable locations in a safe and
environmentally friendly manner. To ensure the flow
of these valuable resources, advanced process
monitoring promises a real-time holistic view of
critical data and provide smart notifications for early
leak detection, reductions of unplanned shutdowns,
and abnormal situation management .
The APMonitor Modeling Language is optimization software
for differential and algebraic equations. It is coupled with
large-scale nonlinear programming solvers for data
reconciliation, real-time optimization, dynamic simulation,
and nonlinear predictive control. It is available as a web
service through APM MATLAB, APM Python, or with a
browser interface at http://apmonitor.com.
A gravity-drained-tank model predictive control (MPC)
application is being developed to demonstrate an
improvement over Proportional-Integral-Derivative (PID)
controllers that are ubiquitous in industrial practice.
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. This involves the
development of novel algorithms and techniques for large-scale and complex
systems. These applications improve safety, reduce environmental impact,
investigate new drug treatments, and maximize profitability.
BYU is the lead institution for the Center for
Friction Stir Processing, a multi-institutional
National Science Foundation Research
Center (I/UCRC). The PRISM group is
collaborating with the CFSP to provide
advanced modeling and control technology
for improved start-up, temperature, and
depth control of Friction Stir Welding. Gravity-drained Tank Model
Boundary management case study for thermal oxidizer
Deep water fiber optic sensor for flow assurance monitoring
Off-shore platform fiber optic sensor
installation
Friction stir welding tool in operation
Multi-scale Modeling of the SOFC system
Schematic of potential components in a “smart” grid operation
Schematics of a highly integrated CHP plant (top),
and solar-thermal power plant (bottom)
Friction stir welding tool
Abraham Martin
BS student
