21.11.2017.

Application of Simulation Through The Life-cycle of a Process Modeling and Simulation Through Different Phases of a Process

Application of Simulation Through The Life-cycle of a Process

The life-cycle of a chemical compound production or of a chemical process development starts when a new and original idea is advanced taking into account its practical implementation. The former concept with respect to the process lifecycle, which imposed a rigid development from research and development to process operation, has been renewed. It is well known that the most important stages of the life-cycle of a process are

  • research and development,
  • conceptual design,
  • detailed engineering,
  • piloting,
  • and operation.

These different steps partially overlap and there is, as well, some feedback between them. For example, plant operation models can be the origin of valuable tips and potential research topics, obviously, these topics directly concern the research and development steps (R&D). The same models, with some changes, are preferably utilized in all the steps. The good transfer of information, knowledge, and ideas is important for successful completion of all the process phases. 

The models are an explicit way of describing the knowledge of the process and related phenomena. They provide a systematic approach to the problems in all the stages of the process life-cycle.

In addition, the process of writing the theory as mathematical expressions and codes, reveals the deficiencies with respect to the form and content.

Among the factors that influence the amount of work required to develop a model, we can retain the complexity, the novelty and the particular knowledge related to the process in modeling. Otherwise, commercial modeling software packages are frequently used as an excellent platform.

In the following text, we cover typical simulation models used through the process life-cycle which are shown in the Figure below.

1. Process Modeling Through the Research and Development Stage

The models in the R&D stage can first be simple, and then become more detailed as work proceeds. At this stage, attention has to be focused on the phenomena of phase equilibrium, on the physical properties of the materials, on chemical kinetics as well as on the kinetics of mass and heat transfer.

This action requires careful attention, especially because, at this life-cycle stage, the process could be nothing but an idea.

The work starts with the physical properties, as they act as an input to all other components. The guidelines to choose physical properties, phase equilibrium data, characteristic state equations etc. can be found in the usual literature.

For each studied case, we can choose the level of detail such as the complexity of the equations and the number of parameters. If the literature information on the physical properties is restricted an additional experimental step could be necessary. As far as industrial applications are concerned, the estimation of the reaction kinetics is usually semi-empirical. Therefore, a full and detailed form of kinetics equations is not expected for the majority of the investigated cases. Some physical phenomena along with their effects can require special attention. 

The ideal modeling and experimental work have to be realized simultaneously and are strongly related. Models provide a basis to choose, both qualitatively and quantitatively, appropriate experimental conditions. The data obtained from experimental work are used to confirm or reject the theories or the form of equations if an empirical model is being applied. Otherwise, these data are used to estimate the model parameters.

This work is sequential in the sense that starting from an initial guess, the knowledge of the system grows and models get more and more accurate and detailed as the work proceeds.

Based on a good knowledge of the phenomena, valuable tips concerning optimal operating parameters (such as temperature and pressure range as well as restricting phenomena) can be given to the next stages. The degree of detail has to be chosen in order to serve the model usefully. 

Practically, the best solution is to describe the most relevant phenomena in a detailed way, whereas the less important ones will be left approximate or in an empirical state.

2. Simulation Models at Conceptual Design Stage

The establishing of the optimal process structure and the best operating conditions characterizes the process development at this stage. Firstly, attention must be focused on the synthesis of the process. The extent to which models can be used in this phase varies. If we have a new process, information from similar cases may not be available at this stage. In the opposite situation, when the chemical components are well known, which usually means that their properties and all related parameters can be found in databanks, the models can be used to quickly check new process ideas. For example, at this stage, for a multiple-component distillation problem, models are used to identify key and non-key components, optimum distillation sequence, the number of ideal stages, the position of feed, etc. At this stage also, we always focus on the full-scale plant. Another question is how the concept will be carried out in the pilot phase. It is known that for this stage, the equipment does not have to be a miniature of the full scale.

The practice has shown that the choices made here affect both investment and operating costs later on. An image of the full-scale plant should also be obtained.

The researchers who work at this level will propose some design computations which are needed by the piloting stage of process life-cycle. Their flow-sheet is the basis of the pilot design or development.

3. Modeling at Pilot Stage

The whole process concept is generally improved in the pilot plant. We can transform this stage into a process analysis made of models if enough experimental data and knowledge about the process exist (for example when we reuse some old processes). For reference, we should mention that other situations are important, such as, for example, knowing that a pilot plant provides relatively easy access to the actual conditions of the process. Some by-pass or small streams could be taken off from the pilot unit and be used in the operation of apparatuses specially designed for the experimental work. Now the models should be ready, except for the correct values of the parameters related to the equipment.

A special pilot stage feature consists in adding the equations describing the non-ideal process hardware to the model in order to compute efficiency (tray efficiency, heat exchanger efficiency, non-ideality numbers, etc). This stage is strongly limited in time, so, to be efficient, researchers must prepare a careful experimental program. It may be impossible to foresee all the details since the experimentation related to the estimation of parameters is often carried out in sequences, but still, a systematic preparation and organization of the work to be done remains useful.

It is important to remember, that the goal of the pilot stage in terms of modeling is to get a valid mass and energy balance model and to validate the home-made models.

4. Modeling at Detailed Engineering Stage

In this stage, models are used for the purpose for which they have been created: the design and development of a full scale plant which is described in the detailed engineering stage.

On the basis of what has been learned before, the equipment can be scaled-up, taking into consideration pilot phase and related data, as well as the concepts of similitude. Special attention should be paid to the detailed engineering of the possible technical solutions. Depending on their nature, the models can either provide a description of how the system behaves in certain conditions or be used to calculate the detailed geometric measures of the equipment.
For example, we show that all the dimensions of a distillation column can be calculated when we definitively establish the separation requirements. Special consideration should be given to the process of scaling-up because here we must appreciate whether the same phenomena occur identically occur on both scales.

It is useful to have detailed documentation concerning all the assumptions and theories used in the model. The yield and energy consumption of a process are easily optimised using fine-tuned models to design a new unit or process. Depending on the process integration, pinch analysis and other similar analysis procedures can be used to find a solution of heat integration. Various data on streams and energy consumption, which are easily developed from simulation results, can be used to sustain the adopted technical solutions.

5. Modeling at Operating Stage

At this stage of the process life-cycle, the models must include all relevant physical, chemical and mechanical aspects that characterize the process. The model predictions are compared to actual plant measurements and are further tuned to improve the accuracy of the predictions.

This consideration is valuable, especially for the finally adjusted models that create the conditions of use to meet the demand of this operating stage so as to guarantee optimal production. Models can also be used in many ways in order to reduce the operating costs. In the mode of parameter estimation, the model is provided with the process measurement data reflecting the current state of the process, which makes it possible, for example, to monitor the fouling of a plant heat exchanger. 
In simulation mode, the performance of the process can be followed. Discrepancies between the model and the process may reveal instrumentation malfunction, problems of maintenance etc.

Verified flowsheet models can be used to further analyze the process operation. In the optimising mode, the models are especially used when different grades of the product are manufactured with the process. 

The importance of storing process data has been emphasized here. After all, the data are an important link in the creation cycle of the process knowledge.

Future applications concerning the gathering of new data will provide a powerful tool in the use of the stored data or process memory. It is important to keep in mind that, at this stage, the process could be further improved as new ideas, capacity increasing spin-off projects, R&D projects, etc. are developed. These developments frequently require a partial implementation of the methodology described above.

Therefore, the models of the existing process could act as a tool in further developments. In practice, models are often tailor-made and their use requires expertise. Building interfaces, which take into account the special demands arising from man–computer interaction, can greatly expand the use of the models.