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Simulations and Modeling

Simulations and Modeling focuses on representing real-world systems using mathematical and computational models. It covers model design, simulation techniques, analysis, and validation, enabling prediction, experimentation, and decision-making in scientific, engineering, and business applications.

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Simulation and Modeling

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Course Title: Simulation and Modeling

Course No: CT 753

Nature of the Course: Theory + Lab

Semester: 8

Full Marks: 80 + 20

Pass Marks: 32 + 8

Credit Hours: 3

Course Description

Course Objectives

Course Contents

1. Introduction to Simulation

4 hrs

1.1. system, model and simulation

1.2. Discrete and continuous systems

1.3. Model of a system

1.4. Types of models

1.5. Steps in simulation study

1.6. Model development life cycle

1.7. Advantage and disadvantage of simulation

1.8. Limitations of the simulation techniques

1.9. Areas of application

2. Physical and Mathematical models

4 hrs

2.1. Static physical model

2.2. Dynamic physical model

2.3. Static mathematical models

2.4. Dynamic mathematical models

3. Continuous system simulation

5 hrs

3.1. Differential and partial differential equations

3.2. Continuous system models

3.3. Analog computer

3.4. Analog Methods

3.5. Hybrid simulation

3.6. Digital-Analog simulators

3.7. Continuous System simulation languages(CSSLs)

3.8. Feedback systems

4. Queuing system

6 hrs

4.1. Elements of queuing system

4.2. Characteristics of queuing systems

4.3. Model of queuing system

4.4. Types of queuing system

4.5. Queuing notation

4.6. Measurement of system performance

4.7. Network of queues

4.8. Applications of queuing system

5. Markov chains

3 hrs

5.1. Key features of Markov chains

5.2. Markov process with example

5.3. Application of Markov chain

6. Random Number

10 hrs

6.1. Properties of Random Numbers

6.2. Generation of Pseudo-Random numbers

6.3. Random Number generation methods

6.4. Test for random numbers

6.5. Generating discrete distribution

6.6. Inversion, rejection, composition and Convolution

7. Verification and validation of simulation models

3 hrs

7.1. Verification and validation

7.2. Verification of simulation models

7.3. Calibration and validation of models

8. Analysis of simulation output

4 hrs

8.1. Estimation methods

8.2. Simulation run statistics

8.3. Replication of runs

8.4. Elimination of Initial bias

9. Simulation software

3 hrs

9.1. simulation in Java

9.2. simulation in GPSS

9.3. Simulation in SSF

9.4. Other simulation software

10. Simulation of computer systems

3 hrs

10.1. Simulation tools

10.2. High Level computer-system simulation

10.3. CPU simulation

10.4. Memory Simulation

Laboratory Works

1.Simulation of continuous system
2.Simulation of the R-C amplifier circuit
3.Generation of Random number
4.Simulation mass spring damper system
5.Simulation of National econometric system

Reference Books

1.Jerry Banks, John S. Carson II, Barry L. Nelson, Devid M. Nicol, P. Shahabudeen: Discrete-Event system simulation
2.Geoffrey Gordon: System Simulation
3.A.M. Law and W.D. Kelton: Simulation and Modeling and analysis
4.R. Y. Rubinstein, B. Melamed: Modern Simulation and Modeling
5.S. Shakya: Lab Manual on Simulation and modeling

Notes:

Source:

This course covers the fundamentals of system simulation and modeling, including discrete and continuous systems, physical and mathematical models, continuous system simulation, queuing systems, Markov chains, random number generation, verification and validation of simulation models, analysis of simulation output, simulation software, and simulation of computer systems.

To provide the knowledge of discrete and continuous system, random numbers generation, queuing system and computer system simulation.

There may be minor deviation in marks distribution. This syllabus follows the official BCT curriculum of Tribhuwan University. In case of any doubt or revision, the university's published syllabus shall be considered authoritative.