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Dynamic Process Simulation: When do we really need it?

Introduction

Process simulation is the representation of industrial processes by means of the application of mathematics and first principles (i.e. conservation laws, thermodynamics, transport phenomena and reaction kinetics). Steady State models have been widely used in the industry, becoming a common or even more, a required practice. Steady state modeling is key for process conceptualization, design and evaluation and it is indeed a mature technology tool. However, the steady state is an idealistic definition used by engineers as a representation of “design” conditions which are not always accomplished due to change in raw materials, product specification, change in capacity due to marketing requirements, and the inherent dynamic behavior of processes. This article will help the reader to easily identify typical engineering problems where dynamic modeling would be an ideal tool to answer their questions.


What is a Dynamic Model?

Similar to a steady state model, dynamic models are based on first principles that cannot be violated. Conservation laws, phase equilibria, heat and mass transfer, and kinetics are also applied in dynamic models. The most significant difference between steady state and dynamic simulation is that steady state assumes that variables are constant with respect to the time. This means that in steady state there is no accumulation in the system so the overall mass and energy input matches its output. Conversely, dynamic models take into account the mass and energy rate of accumulation within the system, which allows one to determine the how long it would take to reach a stable condition starting from a specified initial state. Figure 1, below, represents the simulation scope for steady state and dynamic simulation models.



Figure 1. Comparison of Steady State and Dynamic model scopes



Why use dynamic simulation?

The industrial application of dynamic simulation was limited decades ago, however, with the development in the computing sciences and the improvement of computer processor speeds those limitations have been overcome. Now, we can incorporate a high level of detail in modelling and we can also develop fairly large models. Some application areas of this technology are:

  • Process design is a task that can be performed by using dynamic simulator. Since dynamic models consider equipment holdup, equipment size is required for running simulations. In the case of a new design, an initial sizing can be obtained by means of a steady state simulation and then it can be optimized based on its dynamic behaviour. Significant reduction in CAPEX is possible using dynamic simulation in different types of equipment, such as pressure vessels, tanks, control valves, etc.
  • Process evaluation and de-bottlenecking involves performance evaluation of an existing piece of equipment or facility running under process conditions different from the design case(s). If the analysis shows that its capacity is limiting the process then the “bottleneck” has been identified. The use of a dynamic model will quickly allow the engineer to determine the optimum design, if equipment resizing is an option, stream rerouting options (change in topology), and storage capacities among other options.
  • Safety analyses (what-if) can be easily run with dynamic models which allow the determination of unsafe and hazardous conditions during operation. The impact of equipment malfunction scenarios, such as distillation column overpressure, heat exchanger pipe ruptures, valve leakage, pump failure, indicator drift, and many others can also be studied.
  • Distribution and gathering system piping network studies can be also carried out due to the nature of the “pressure-driven” solver typically implemented in dynamics simulators, which allows a more accurate representation of real processes in which hydraulics and fluid mechanics are of vital importance (Luyben, 2002). Flow and fluid velocity estimation, change in production rates, pressure specifications and evaluation of pigging scenarios are some of the features available in this sort of model.
  • Relief and blowdown systems is a specific application where dynamic simulation can improve design. Blowdown valves and pressure safety valves may be oversized if API 521 is applied. The application of dynamic simulation leads to more precise calculations of relief loads. Consequently there would be decreased flare loads, with reduced CAPEX. Dynamic simulation also allows the study of controlled blowdown procedures to avoid unnecessary flowrate peaks especially in the initial stages.
  • Batch and semi-batch processes can only be successfully modelled in dynamic simulators. Examples of these processes are: batch distillation, batch reactors, catalyst regeneration processes, delayed coking process, etc.
  • Process control strategies can be evaluated and compared in order to determine the best, most cost-effective solution. Traditional and advanced process controllers can be easily “pre-tuned” using dynamic simulation models saving hours of expensive steps tests performed in plants. A current trend is to test Distributed Control Systems (DCS) using these models. Anti-surge controller evaluation on centrifugal compressors is a major area of this application. 
  • Start-up and shutdown procedures can developed, tested and optimized with dynamic models. Tens or hundreds of hours of stabilization time and tons of out-of-spec products can be saved by the determination of optimum start-up/shutdown sequences, in addition to the identification of potential hazardous conditions during these activities. 
  • Operator training is an area that has been gaining an important place in engineering practice. Complete replication of the control room is commonly installed on site to help train operators before plant experience. Operator Training Simulators (OTS), for which a dynamic simulation is essential, include grading methodologies which allow for  certifying operators before they face routine (normal operation, start-up and shutdown) and non-routine (equipment malfunction) scenarios in real plants.


Drain Tank Pressure Evaluation Project

This simple example involved a dynamic study performed for a Process Ecology client.  By using dynamic simulation, a process evaluation was completed and a design solution was provided. The study consisted of the depressurization of a condensate pipeline into a drain tank as pictured in Figure 2. Since the condensate (RVP = 101.3 kPa @ 38.7 °C) initial temperature was 60 °C, as soon as the drain valve opened, an important amount of vapour is expected to be flashed which would increase the Drain Tank pressure. The technical question was: Will the pressure buildup in the drain tank exceed the design pressure?



Figure 2. Practical Example Scheme


A dynamic model was built in Aspen HYSYS® V8.6 to determine whether or not the design pressure in the drain tank would be exceeded. Piping size and elevation data were included in the model. Figure 3 shows the results of the dynamic model. This was run at initial conditions for 10 seconds, then the drain valve was instantaneously opened fully (worst case scenario). The condensate flowed from the pipeline to the drain tank which was at ambient pressure. Condensate started flashing and then vented into the atmosphere (through the vent line). The original vent diameter was 6 inches and as can be seen it would have caused vapours to accumulate creating a buildup in pressure in the drain tank which would have exceed the design pressure (green curve) causing damage to the drain tank. Several configurations and designs were tested with the model. In the end, the best, most cost-effective solution was to increase the vent diameter up to 8 inches (see Figure 3, blue curve).



Figure 3. Drain Tank Pressure Results


Final Remarks

Dynamic simulation provides a higher level of process analysis. This allows the process engineer to answer difficult questions that may be complex if not impossible to answer with traditional steady state simulation. It is the proper tool for processes which involve transient conditions, real time behaviour and batch and semi-batch process. Remember there is no such as thing as “steady state”, the world is always changing!


Try to identify your case with the list provided above to determine whether or not dynamic simulation will provide benefits for your project. If you have any further queries, please do not hesitate to contact us here. Process Ecology will be glad to help you get one step ahead!


Bibliography

Aspen Technology Inc. (2015, May 5). Retrieved from Oil and Gas Process Simulation Software: http://www.aspentech.com/hysys/

Luyben, W. (2002). Plantwide Dynamic Simulators in Chemical Processing and Control. New York: Marcel Dekker, Inc.



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