Process simulation, long indispensable for design, is finding wider use in plant operations and beyond. Several developments promise to ease the use and expand the capabilities of the software.
Such simulations rely on first principles and so provide a more fundamental representation of what is happening than empirical and statistical models often used for advanced process control, scheduling and other chores. However, the simulations; rigor comes at a price considerable effort and expense to develop the models. So, several companies are exploring how to leverage their investment in process models and the power their rigor affords.
One result is that the traditional boundary between offline and online model applications is becoming increasingly permeable, says Costas Pantiledes, technology director for software-maker Process Systems Enterprise, London, England (Figure 1).
[Editor's Note: To view Figures 1 and 3, click on the Download Now button at the bottom of this article.]
Keeping tab on the process
EKA Chemicals, Gothenberg, Sweden, uses a simulator as a soft sensor to monitor chlorine emissions at its plants, which make bleaching chemicals for the paper industry. The first system was installed about two years ago, says Nathan Massey, president of Chemstations, Houston. EKA uses Chemstations; ChemCAD simulator, and now is adopting the approach in its other plants.
Previously, monitoring required six laboratory analyses per day. Switching to the software approach has saved more than $100,000 per year just for analysis. More than that, though, Massey says, it has allowed plants to run less conservatively, which has led to 1% to 2% overall energy savings. In addition, the simulator provides operators with insights about when to calibrate or clean instruments and equipment.
Peter Henderson, London, Ontario-based product manager of simulation for Honeywell which just bought the Hysys simulation business from Aspen Technology foresees models filling a broad online monitoring void left by instruments, such as for analysis of gas turbines and compressors, catalyst aging and the fouling of complex heat-transfer equipment.
Some properties that are easily measured are being used to infer ones that can;t be, says Marco Satyro, chief technology officer of Virtual Materials Group, Calgary, Alberta, which offers VMG Sim. For compressor monitoring, simulators enable measurement of water content in gas, he says. More broadly, the software can serve as a pseudo-analyzer. When the specific gravity and the roster of constituents are known, it can determine the actual composition.
At NOVA Chemicals, Peter Dolsinek, leader of process automation and engineering systems, based in Sarnia, Ontario, notes that steady-state models are being used for performance monitoring on equipment like distillation columns.
A model validated with field data (Figure 2) can help plant engineering staff identify the root cause of problems like equipment degradation and line plugging, and allow quantitative evaluation of options to solve these problems, says Todd Willman, president of EPCON International, Houston. EPCON offers a simulator, System 7 Process Explorer, specifically geared for use by plant personnel.
Figure 2. Field validation
Readings from an ultrasonic flowmeter are used to verify flow rates predicted from a simulation model.
In developed countries, emphasis has shifted from investing in new plants to making the most of existing assets, and this is spurring more interest in using the models for optimization and productivity improvement, says Gilles Hameury, sales and marketing manager for ProSim SA, Labege, France.
Alastair Fraser, Lake Forest, Calif.-based vice president of the SimSci simulator business of Invensys, sees increasing demand for simulator use for predictive maintenance. He predicts that in four to five years use of models for performance monitoring will be widespread. Massey of Chemstations adds, I believe that performance monitoring and predictive maintenance [using simulators] are both near the beginning of their product cycles and eventually will become standard for any processing company that wants to remain competitive.
Further in the future, Satyro hopes that such models will be built right into the control chips for process equipment. Hardware developers must be aware of this capability so they can drive the dream, he says.
Improving operator training
Rigorous models have played a limited role in operator training because they often aren;t fast enough, but that may be changing. To be useful for training, a model must be able to run at a minimum of three times and sometimes up to 10 times real time, Massey says. Major discontinuities, such as a pump or valve trip, can slow down performance. First-principles simulations can;t keep up now, he says, so companies rely on shortcut models to provide qualitative results.
Improved numerical techniques plus faster computer hardware will make performance of rigorous models sufficient within five years, he believes, opening up the prospect of providing quantitative as well as qualitative results for training.
NOVA;s Dolsinek certainly sees the value of using rigorous models to broaden operator training from qualitative to quantitative. He also points to another strong motivator increasing the return on the investment in high-fidelity models.
Honeywell also sees potential for maximizing the return on rigorous models by using them for operator training, Henderson says. Indeed, its initial thrust with Hysys will be in that area, he adds. Operator training often is considered after the completion of control system design, but the same model also could play a role during design, he says, and later to assess the root cause of operating problems.