Unsteady-state or dynamic simulation accounts for process transients, from an initial state to a final state. Dynamic models for complex chemical processes typically consist of large systems of ordinary differential equations and algebraic equations. Therefore, dynamic process simulation is computationally intensive.

Dynamic simulation is most often used for: batch process design and development, control strategy development, control system check-out, the optimization of plant operations, process reliability/availability/safety studies, process improvement, process start-up and shutdown.

There are countless dynamic process simulators available on the market. Some of them are listed here.

What Makes Dynamic Simulation So Important

For the typical case of a process industry, we model the plant subunits and their regulatory control. The relevant equations are solved repeatedly in the time domain and the values of temperature, pressure, flow and composition as well as the valve openings and the process control system output are calculated at every point of interest. Thus, the interactions between the process subunits can become obvious. Further, the process reaction to disturbances (such as feed variation, instruments failure or change of operation strategy) can be fully investigated.

As the industrial process units are becoming increasingly complex with applications of new technologies that include thermal integration, modern process design and advanced process control systems. The units are required to operate non-stop for longer periods of time at optimal conditions. The need for flexibility, regarding processes or equipment, continuously increases. It is, further, well known that big and fast changes in the plant operating conditions should be avoided, since the effects of moving from one operational region to another can be unanticipated and possibly dangerous. Thus, one needs to be aware of the danger zones and when these occur. In brief, the behavior of the process unit on the whole is not a simple sum of the plant’s subunits actions.

Safety, environmental, and economic factors highlight the importance of understanding the design and operating of the plant, as well as the sufficient training of the plant personnel at a time of an ever-increasing worldwide need for highly qualified and capable operators.

Dynamic simulation is the only economically effective solution to these needs, since it yields a lot more information than what traditional steady state simulation offers. This is because dynamic simulation allows us to study a plant’s behavior in a wide range of operation conditions, like during start-up or shutdown or during emergency situations. 

Further, it can incorporate algorithms describing the process unit safety or regulatory control philosophy. Thus, it is possible to use a dynamic model for the investigation and improved understanding of the unit's behavior based on design or operational data.

Applications of Dynamic Simulation

The dynamic simulation applications in the process industry can be used for a variety of
purposes. These include:

• Operator Training Simulators
• Operation Optimization
• Modification of Process and Control System Design
• Investigation of Operational Issues
• Safety and Environmental Issues

Operator Training Simulators

In today’s world, when industry is facing problems of massive retirements of their work force and a skills shortage, dynamic process models integrated with the plant’s Distributed Control Systems (DCS) can be used to capture, maintain and develop existing operating skills. Among others, a fully deployed operator training system can be used to:

• Offer plant operators an improved understanding of the unit operation and handling.
• Familiarize the operators to the process design and the control systems, while emphasizing the interactions between the two.
• Demonstrate the use and explain the advantages of advanced process control.
• Control and verify the operators’ actions.
• Practice without the presence of an instructor.

Operation Optimization

A dynamic model of a process unit can be used to optimize operations. Some typical examples
are:

• Creating, testing and verifying procedures for the safe start-up and shutdown of the process or for the minimization of time that plant equipment stays out of operation.
• Finding ways to move the plant operation to equally feasible and safe but more profitable conditions.
• Addition of new process lines, before or after start up, for improved plant controllability during transients.

Modification of Process and Control System Design

The process design can be relatively easily modified and troubleshoot with a dynamic simulator.

• Technical assessment of alternative design solutions.
• Dynamic studies: Analysis of controllability, de-bottlenecking, depressurising, feed differentiation effects etc.
• Determination of characteristic equipment parameters (instrument minimum sampling time or permissible noise levels, controller tuning parameters, control valves characteristics etc.)
• Compressor performance verification and avoiding compressor surge.
• Effects to plant controllability due to equipment modifications.

Investigation of Operational Issues

Use of dynamic simulation is very efficient in finding answers to problematic process behavior and can help a lot to target process challenges such as:

• Rapid assessment of alternative solutions to what-if scenarios.
• Achievement of optimal plant conditions, after an unanticipated change.
• Incident investigation and procedures for future prevention.
• Estimation of functional parameters for instrumentation.

 Safety and Environmental Issues

• Exhaustive testing of plant procedures and detection of unfavorable conditions (e.g.explosive/toxic mixtures, formation and deposition of hydrates etc.) due to transients normal functions.
• Verification of depressurising procedures.
• Verification of DCS and emergency shutdown system control loops and sequences.

However, although benefits and importance of dynamic simulations are unquestionable, the use of dynamic simulators is still not standardized to the level of steady state simulation.  The problem is that the manufacturing people are not always willing to use the models, even though the advantages are clear.

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REFERENCES
[1] Nisenfeld A. E., 1982. Principles of Operation and Control, ISA, Monograph Series 3.
[2] AspenTech Modelling Philosophy, 1998. AspenTech Ltd.
[3] Gas Injection Plant, 1997. SAST Ltd.