Questions
Syllabus
Notes
Qns. By Syllabus

Semester

Subject

Year

Tribhuwan University

Institute of Science and Technology

2080

Bachelor Level / Third Year / Fifth Semester / Science

B.Sc in Computer Science and Information Technology (CSC328)

(Simulation and Modeling)

Full Marks: 60

Pass Marks: 24

Time: 3 Hours

Candidates are required to give their answers in their own words as for as practicable.

The figures in the margin indicate full marks.

Section A

Long Answers Questions

Attempt any TWO questions.
[2*10=20]
1.
Why model of a system is built? What is static model? Differentiate between static and dynamic mathematical models in simulation.[10]

Why Model of a System is Built? Static Model & Difference Between Static and Dynamic Models

Why Model of a System is Built?

A model is a simplified representation of a real system that allows us to study, analyze, and predict system behavior without experimenting on the actual system.

Reasons for building a model:

  • Cost Reduction — Experimenting on real systems is expensive; models provide a cheaper alternative
  • Risk Avoidance — Testing dangerous scenarios (nuclear plants, aircraft) on real systems is unsafe
  • Time Compression — Years of system behavior can be simulated in minutes
  • Impossibility of Experimentation — Some systems cannot be disturbed (economy, weather)
  • Understanding System Behavior — Models help identify how variables interact and affect outcomes
  • Design and Optimization — Models allow testing different configurations before actual implementation
  • Prediction — Models help forecast future behavior of the system under various conditions
  • Training Purpose — Models are used to train operators (e.g., flight simulators)

What is a Static Model?

A static model is a mathematical model that represents a system at a particular point in time, or a system where time does not play a role in the relationships between variables.

  • It provides a snapshot of the system
  • Variables do not change over time
  • Example: A model calculating the total profit of a company based on fixed costs and revenue at one instant

Difference Between Static and Dynamic Mathematical Models

Aspect Static Model Dynamic Model
Definition Represents system at a fixed point in time Represents system as it evolves over time
Time dependency Time is not a variable; no role of time Time is a critical variable
Nature Provides a single snapshot Shows continuous or discrete changes
Variables Variables remain constant Variables change with time
Equations used Algebraic equations Differential equations, difference equations
Complexity Simpler to build and solve More complex due to time-varying behavior
Example Calculating steady-state profit, Monte Carlo simulation Simulating traffic flow, queuing systems, weather forecasting
State change No state transitions State transitions occur over time
Use case When system behavior at one instant is sufficient When understanding system evolution is required

Conclusion

Models are essential tools in simulation because they allow safe, cost-effective, and time-efficient study of real systems. Static models are suitable when time is irrelevant, while dynamic models are necessary when the system's behavior changes over time. The choice between them depends on the nature of the problem being studied.

2.
What is storage in GPSS? Describe the blocks associated to storage in GPSS. A machine tool in a manufacturing shop is turning out parts at the rate off one every 5 minutes. As they are finished the parts go on an inspector who takes 10±310 \pm 3 minutes to examine each one and rejects 1010% of the parts. Represent the system in GPSS using the concept of facility and run the simulation for 500 parts.[10]
3.
What are the two main properties of random numbers? Test whether the 3rd, 7th, 11th, and so on numbers in the sequence in the following random number sample are auto-correlated. (Zα=0.05(Z_{\alpha}=0.05 and Z0.025=1.96)Z_{0.025}=1.96) 0.12, 0.01, 0.23, 0.28, 0.89, 0.31, 0.64, 0.28, 0.83, 0.93, 0.99, 0.15, 0.33, 0.35, 0.91, 0.41, 0.60, 0.27, 0.75, 0.88, 0.68, 0.49, 0.05, 0.43, 0.95, 0.58, 0.19, 0.36, 0.69, 0.87,[10]
Section B

Short Answers Questions

Attempt any Eight questions.
[8*5=40]
4.
Explain Markov chain with suitable example. [5]
5.
What are steps involved in simulation study? Explain. [5]
6.
Generate 10 random integers using Linear congruential method where m=1000m=1000, a=19a=19, c=6c=6 and X0=13X_0=13. [5]
7.
Explain different estimation methods which are used in simulation output analysis. [5]
8.
Define verification and validation. Explain the process of model verification in brief. [5]
9.
What is feedback system? Explain with example. [5]
10.
What is calling population? Explain arrival and service process in a queue. [5]
11.
Explain Monte Carlo simulation method with example. [5]
12.
Write short notes on: a. Non-stationary poisson process b. Poker test [5]