Simulation is normally used in order to analyze systems that are hard or impossible to describe using systems of explicit equations. In particular, this applies to highly complex dynamic systems such as most textile machines and processes.By carrying out a simulation experiment, knowledge about the real system can be gathered comparatively easily in contrast to trials on the machine or during the actual process. This includes practical experiments as well as a simulation using a computer program. Another field of application of simulations are systems that do not yet exist. This comprises the testing of new plant design concepts or for example the development of new spacecraft and aircraft or automobiles using carbon textile reinforced composites.
14.1Simulation with and without ComputerIn general, simulation methods can be divided into those that use a computer and those that do not, as shown in Fig. 14.1. Those simulations without computer can be separated into destructive and nondestructive methods. Simulations that use a computer can either be based on technical models (for example, finite element method for structural composites, computational fluid dynamics for polymer flows), on examples taken from nature (for example, artificial neural networks, evolutionary algorithms for machine setting optimization), and those based on analytical equations (for example, warp tension during weaving). Simulation Coauthor: Y.-S. Gloy 14.3 Modeling
14.3.1Types of ModelingIn order to save time and hence money, most simulation models use a simplified description of the real process or machine. Figure 14.2 shows typical models.
Modeling
Gray box Parts of system known ComponentsBlack box Behavior known Inner structure known White box Inner structure know Abstraction Reduction
Figure 14.2 Principles of modeling
White-Box ModelThis kind of model is suitable if the inner structure of the system is known. This structure is then deliberately abstracted, modified, and reduced to the most important influencing parameters. A typical example is the modeling of a weaving machine.
Black-Box ModelIf the inner structure of a system is unknown but its behavior or its interaction with other systems can be observed and modeled, this is called a black-box model. A typical example is the use of neural networks to simulate textile processes.
Gray-Box ModelIn many cases, only parts of a system are fully known and only a few, but not all, interactions between its components are established. The respective model is then called a gray-box model. In order to save costs, this approach is widely used. A fuzzy model can be regarded as a gray-box model in some cases.
Model SimplificationIn order to simplify a model compared to reality, the following possibilities are often used:Components that are not of crucial significance are not taken into account. A trial based on factorial design can be helpful to determine the important influencing parameters.Unimportant details are neglected.The system is split into its components and these are analyzed separatel...