**1.2. Computer modeling and computer simulation**

Simulation in everyday life can be related to various activities. If this word is used in the computer technology, then the term simulation represents the process of creating the abstract system models from the real environment and carrying out the appropriate number of experiments on them. When the experiments are carried out on a computer, then they are named computer modeling and computer simulation (**Figure 1**).

• It is impossible to determine the analytical solution of the analytical model.

real system, whose structure is barely known or cannot be approached to.

• The experiment within a real system or the experiment on the real system is, in most cases, either unprofitable or too complex. Modeling and simulation can show whether a further

Introductory Chapter: Computer Simulation http://dx.doi.org/10.5772/intechopen.84198 3

• Often the aim of modeling and simulation is to perceive the functionality of the existing

• When the optimal or optimized functioning of a system is needed, it is necessary to change various parameters. If the real system is taken into account, this is often impossible because there is no such a system. In other words, that kind of a system has not been built yet, or the prices of such an experiment are excessive. In such situations, modeling and simulation

• Sometimes it is necessary to simulate the conditions that lead to the destruction of the system. The destruction of the real system, in most cases, is not allowed, so the computer

• When it comes to long-term processes of real system or within the real system, then time can be a problematic factor. In such situations, computer simulation can "accelerate" the

• When it comes to extremely fast processes of the real system or within the real system, computer simulation is a solution which allows the monitoring of high-speed processes gradually or slowly. This is very important, since it is not possible in real life or in real

• Sometimes the experiment should be stopped for various reasons, and it is often impossible in real terms. When it comes to computer simulation of such an experiment, there is no problem, because the simulation can be stopped and continued when it is necessary.

Like everything in life, computer simulations are not perfect and there are different problems. Simulations are, generally speaking, very useful, but they have advantages as well as disad-

• When a model is created, then it can be used repeatedly for the analysis of required process,

• Computer simulations can be extremely helpful, even if the input data are incomplete and

• In most cases it is easier and cheaper to get the output data of the simulation than the output

• Computer simulation generates the necessary data that can be used for the evaluation and

assessment of any system characteristic and without big restrictions.

• The system is too complex and it is impossible to describe it analytically.

investment in the experiment is justified or not.

simulation, in such situations, is the only solution.

**1.4. Advantages and disadvantages of computer simulations**

vantages. The basic advantages of computer simulations are:

are the best solutions.

environment.

process and shorten it artificially.

structures, and similar elements.

data of the real system.

with a certain amount of arbitrariness.

**Figure 1.** Link between real system modeling and computer simulation.

The input data vary and depend on many factors when the models and simulations are taken into consideration. For example, some models require very simple inputs (e.g., the input for the simulation of an AC sinusoid is based on few numbers), while other models require terabytes of input data (e.g., simulation of weather or climate changes).

Input data are provided by various devices which are:


It should be noted that the systems that receive data from external sources must be "careful": they should know what these data represent and to which elements are actually connected. The precision must be taken into account and the errors should not occur. If the errors appear, they should be reduced to the minimum. The mathematics integrated in the computer is not perfect, so the approximate results, result abbreviations, or neutralization of small errors can lead to an increase of potential errors. It is necessary, in some cases, to analyze the resulting error in order to verify that the simulation output is valid and that it can be used in further calculations and simulations. Even small errors in the original input data can accumulate in significant errors in further simulations [1, 4, 5].

#### **1.3. Why do we need computer modeling and computer simulations?**

What do we use modeling and simulation for? Are they necessary? These questions are asked very often, and there are plenty of reasons for their creation and usage, and the most important are the following ones:


**1.2. Computer modeling and computer simulation**

2 Modeling and Computer Simulation

modeling and computer simulation (**Figure 1**).

Simulation in everyday life can be related to various activities. If this word is used in the computer technology, then the term simulation represents the process of creating the abstract system models from the real environment and carrying out the appropriate number of experiments on them. When the experiments are carried out on a computer, then they are named computer

The input data vary and depend on many factors when the models and simulations are taken into consideration. For example, some models require very simple inputs (e.g., the input for the simulation of an AC sinusoid is based on few numbers), while other models require tera-

bytes of input data (e.g., simulation of weather or climate changes).

• Sensors and other physical devices that are connected to the model

• Values that represent output elements of other models or simulations

**1.3. Why do we need computer modeling and computer simulations?**

• Control panel that directly affect the progress of the simulation itself in some way

• The values that represent the output products from other processes or operations

It should be noted that the systems that receive data from external sources must be "careful": they should know what these data represent and to which elements are actually connected. The precision must be taken into account and the errors should not occur. If the errors appear, they should be reduced to the minimum. The mathematics integrated in the computer is not perfect, so the approximate results, result abbreviations, or neutralization of small errors can lead to an increase of potential errors. It is necessary, in some cases, to analyze the resulting error in order to verify that the simulation output is valid and that it can be used in further calculations and simulations. Even small errors in the original input data can accumulate in

What do we use modeling and simulation for? Are they necessary? These questions are asked very often, and there are plenty of reasons for their creation and usage, and the most impor-

Input data are provided by various devices which are:

**Figure 1.** Link between real system modeling and computer simulation.

• Current or older data brought in manually

significant errors in further simulations [1, 4, 5].

tant are the following ones:


#### **1.4. Advantages and disadvantages of computer simulations**

Like everything in life, computer simulations are not perfect and there are different problems. Simulations are, generally speaking, very useful, but they have advantages as well as disadvantages. The basic advantages of computer simulations are:


• In some cases, the computer simulation may be the only way to resolve the problems appropriately.

**Chapter 2**

Provisional chapter

**Modeling, Simulation, and Control of Steam**

Modeling, Simulation, and Control of Steam Generation

DOI: 10.5772/intechopen.79410

This chapter describes a modeling methodology to provide the main characteristics of a simulation tool to analyze the steady state, transient operation, and control of steam generation processes, such as heat recovery steam generators (HRSG). The methodology includes a modular strategy that considers individual heat exchangers such as: economizers, evaporators, superheaters, drum tanks, and control systems. The modular strategy consists of the development of a numerical modeling tool that integrates sub-models based upon first principle equations of mass, energy, and momentum balance. The main heat transfer mechanisms characterize the dynamics of steam generation systems during normal and abnormal operations, which include the response of key process variables such as vapor pressure, temperature, and mass flow rate. Other important variables are: gas temperature, fluid temperature, drum pressure, drum's liquid level, and mass flow rate at each module. Those variables are usually analyzed with design predicted performance of real industrial equipment such as HRSG systems. Finally, two case studies of the application of the modeling

strategy are provided to show the effectiveness and utility of the methodology.

Keywords: steam generation, modeling methodology, first principle equations, heat recovery steam generators (HRSG), boiler modeling, economizer, superheater, heat

Electric energy production and conservation has become a key technological challenge in the development of nations to promote their steady and healthy socioeconomic development. Also,

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

Graciano Dieck-Assad, José Luis Vega-Fonseca,

Graciano Dieck-Assad, José Luis Vega-Fonseca,

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

**Generation Processes**

Processes

Isaías Hernández-Ramírez and Antonio Favela-Contreras

Isaías Hernández-Ramírez and Antonio Favela-Contreras

http://dx.doi.org/10.5772/intechopen.79410

exchange surfaces, heat exchanger

Abstract

1. Introduction

• Computer simulation can describe and solve complex problems by using dynamic random variables, which are unavailable in mathematical modeling.

The major disadvantages of computer simulations are:


No matter what, computer simulation is a very useful thing, and its use is rapidly increasing in environments and situations where it is possible. Obviously, the application of computer simulation has many more advantages than disadvantages, and it is certain that computer simulations are going to be dominant in almost every area and environment of everyday life [4, 6].
