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Simulation

Simulation : what for ?

Even if the majority of industrialists trust the power of simulation when it comes to designing and optimizing structures, there are still some sectors where this approach is not in use, sometimes owing to the unawareness of potential benefits.

Thanks to the improvement of computation performance, and particularly with numerical computation, modeling and simulation have become key elements when studying a system. Through simulation, we are able to explore a lot of situations in a relatively short time. According to the need, modeling can cover several shapes (knowledge-base model, black box…) with different levels of detail (global model, simplified model, finite element…).

In this article, we will present a (non-exhaustive) overview of the modeling approach in industry. It is illustrated with examples that are derived from Acsystème experience in which simulation is employed for:

  • operational and behavioral analysis,
  • sizing and optimizing process.

Behavioral analysis

In this case, simulation is used to check some aspects of system principle. Thus, EDF designs control systems for automatons based on numerical models that will help to expand its hydro-electrical facilities. These models also guarantee safety and security standards.

Simulation is also applied to elaborate strategies in case of an incident: it will validate the quality of corrective and preventive measures under non-replicable scenarios (10-year flood…) or requiring expensive or dangerous tests.

Design, optimization

To design and optimize, it is possible to create a model and simulate it according to different operational scenarios. Afterwards, we know information like the efficiency of a machine, the energy cost to manufacture a product, the equipment wear… Then, the designer will be able to change (manually or with a specific algorithm) several parameters so as to optimize system performance.

For instance, if we consider an industrial furnace, simulation can help to improve product quality and productivity while limiting energetic consumption or pollutant emissions.

Knowledge-based model and behavioral model

In any case, modeling may be performed in various manners. We are used to hearing about knowledge-based or behavioral models.

A knowledge-based model is drawn from physical links between system quantities. These relations are built by reasoning from specific hypothesis and general laws of physics applied to the system. So, to model the movement of a mechanical element, we can assimilate it to its gravity center, neglect friction and apply fundamental principles of dynamics.

On the other hand, behavioral models constitute a purely mathematical description of the relations observed between input (causes) and output (effects) quantities, without relying on system physics. For instance, the characteristic curve of a piezoelectric injector is a complete behavioral model. Identification techniques like neural network or parametric estimation are a good way to obtain more complex behavioral models.

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Control system designed in Simulink

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Behavioral analysis of a flow arrangement

Practical application

Autonomous vehicles inside harbours

BA Systèmes and Gaussin : two french companies proposing to harbour terminal an automated logistic treatment solution of their containers.

Optimization of an ammonia evaporator level control

Yara, a chemical company producing fertilizer, wished to improve the level control dynamic behaviour of the workshop producing ammonium nitrate. A strategic project due to the precision required for the chemical formulas.