Simulation and Modelling - Syllabus
Embark on a profound academic exploration as you delve into the Simulation and Modelling course (simulation) within the distinguished Tribhuvan university's CSIT department. Aligned with the 2074 Syllabus, this course (CSC317) seamlessly merges theoretical frameworks with practical sessions, ensuring a comprehensive understanding of the subject. Rigorous assessment based on a 60 + 20 + 20 marks system, coupled with a challenging passing threshold of , propels students to strive for excellence, fostering a deeper grasp of the course content.
This 3 credit-hour journey unfolds as a holistic learning experience, bridging theory and application. Beyond theoretical comprehension, students actively engage in practical sessions, acquiring valuable skills for real-world scenarios. Immerse yourself in this well-structured course, where each element, from the course description to interactive sessions, is meticulously crafted to shape a well-rounded and insightful academic experience.
Course Description: The syllabus consists of introduction to system, modelling and simulation
of different types of systems. It includes the modelling of systems, its validation, verification and
analysis of simulation output. It comprises the concept of queuing theory, random number
generation as well as study of some simulation languages.
Course Objective: To make students understand the concept of simulation and modelling of real
time systems.
Units
System and System Environment, Components of System, Discrete and Continuous System,
System Simulation, Model of a System, Types of Model, Use of Differential and Partial differential
equations in Modeling, Advantages, Disadvantages and Limitations of Simulation, Application
Areas, Phases in Simulation Study
Simulation of Continuous and Discrete System
Continuous System Models, Analog Computer, Analog Methods, Hybrid Simulation, Digital-
Analog Simulators, Feedback Systems
Discrete Event Simulation, Representation of time, Simulation Clock and Time Management,
Models of Arrival Processes - Poisson Processes, Non-stationary Poisson Processes, Batch Arrivals;
Gathering statistics, Probability and Monte Carlo Simulation
Queuing System
Characteristics and Structure of Basic Queuing System, Models of Queuing System, Queuing
notation, Single server and Multiple server Queueing Systems, Measurement of Queueing System
Performance, Elementary idea about networks of Queuing with particular emphasis to computer
system, Applications of queuing system
Markov Chains
Features, Process Examples, Applications
Random Numbers
Random Numbers and its properties, Pseudo Random Numbers, Methods of generation of Random
Number, Tests for Randomness - Uniformity and independence, Random Variate Generation
Verification and Validation
Design of Simulation Models, Verification of Simulation Models, Calibration and Validation of the
models, Three-Step Approach for Validation of Simulation Models, Accreditation of Models
Analysis of Simulation Output
Confidence Intervals and Hypothesis Testing, Estimation Methods, Simulation run statistics,
Replication of runs, Elimination of initial bias
Simulation of Computer Systems
Simulation Tools, Simulation Languages: GPSS, Case Studies of different types of Simulation
Models and Construction of sample mathematical models
Lab works
Laboratory Work:
After completing this course, students should have practical knowledge regarding simulation of
some real time systems (continuous and discrete event systems), Queuing Systems, Random
Number generations as well as study of Simulation Tools and Language. Verification and
validation of models can be done, the analysis of outputs produced in the laboratory exercise can
also be performed. The laboratory work should include:
- Implement different methods of random number generation
- Simulating games of dice that generate discrete random variate, using random number generation
- Testing of random numbers (K-S and Chi Square Test)
- Implementing applications of Monte Carlo methods
- Implement applications of Markov’s chain
- Simulation of single queue server system
- GPSS models - queue, storage, facility, multi-server queue, decision making problems