Simulations Invade Model-Predictive, Abnormal Situations on Way to Real-Time

Process Simulations Are Bursting Their Former Boundaries and Storming into Optimization, Model-Predictive Control, Abnormal Situations Management and Closing In on Real-Time Operations

By Jim Montague

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"Ongoing operator training is important to power generators preparing for the retirement of experienced operators. However, beyond training operators, our customers are achieving added benefits by using our simulation technology for engineering analyses and validating new control logic," adds Bob Yeager, president of Emerson's Power and Water Solutions division.

More Data + Better Math = More Reality

So what's at the root of all simulations and what's driving them and their software's increasingly sophisticated capabilities? You guessed it—a huge and growing pile of mathematical calculations.

For instance, GenCorp's Aerojet ( division in Sacramento, Calif., is using the MathWorks' ( MATLAB and Simulink software to build a control system to deliver constant pressure in the fuel tanks of Kistler Aerospace's K-1 space launch vehicle. When finished, K-1 will be the first commercial, reusable launch vehicle with low-cost access to space for low-earth-orbiting satellites. K-1's modified Russian rocket engine from Aerojet burns liquid oxygen (LOX) and kerosene, but as LOX levels in the tank drop, more pressure is needed to force it to the combustion chamber. To restore pressure, LOX consumed during firing is replaced with helium from external storage tanks. However, helium creates a new control engineering problem, because LOX requires steady pressure, while the helium requires constantly increasing pressure.

As a result, Perry Stout, K-1's controls engineer, developed a solution in which flow between the high-pressure helium storage tanks and the low-pressure LOX tanks is controlled by a series of flow-regulating solenoid valves and an orifice that can vary in size with ambient conditions, and used MATLAB and Simulink to design a control system that regulates valve operations and orifice size. First, he derived and wrote out the physical equations, moved these core equations into Simulink, developed and tested a model and graphically added heat-transfer equations and closed-loop control laws without writing added code. Next, he used MATLAB to analyze the design and modified it in search of optimal conditions, a task that would have taken several months using a conventional engineering process.

"If this was a Fortran project, the control system design would have involved an entire team," says Stout. "A manager would have been required to divide the modeling, simulation and control tasks among several people, closely monitor and coordinate all activity and summarize the results."

Jason Ghidella, Simulink process marketing manager for MathWorks, adds that, "Simulators are becoming more dynamic and non-linear because high-end users want better performance and safety. They want to see if their control strategy is in the ballpark, but they also want to throw all kinds of unusual conditions at it too," says Ghidella "Non-linear simulations are based on partial differential equations (PDEs) and differential algebraic equations (DAEs), and these require a lot of calculating that can't be done in traditional ways. So simulator developers must find other ways to understand and solve these dynamic problems and then generate a response."

Start-Up and Incidents Handling

Similarly, simulations are even being used to assist routine operations, as well as evaluate and respond to alerts and events. For instance, Rio Tinto Alcan's ( Gove bauxite mine and alumina refinery is located at Nhulunbuy in Australia's Northern Territory, and it just completed a $3-billion expansion that will increase its alumina production from 2 million to 3.8 million tonnes per year and allow the refinery to run independent of its local bauxite reserves. As part of its expansion and to improve plant capacity, RTA Gove chose a new double-digestion technology, which uses low-temperature digestion for removal of trihydrate alumina, followed by high-temperature digestion for monohydrate alumina. Few double-digestion circuits are established yet, so RTA Gove needed a simulator to train its operators without adversely affecting plant operations, and to help its multi-DCS controls architecture avoid data mismatches.

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