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ENCT 353Bachelor in Computer Engineering · Semester 61 Paper Available

Simulation and Modeling

Past examination question papers and complete curriculum syllabus for Simulation and Modeling (ENCT 353), Bachelor in Computer Engineering Semester 6 under Institute of Engineering (IOE), Tribhuvan University.

Past Question Papers (PDF)

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Note: This question paper file (8th sem) was archived from an IOE exam session for the common Simulation and Modeling curriculum.

8th-sem_Simulation and Modeling.pdf

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Most Frequently Asked Questions

Top recurring IOE board exam questions for Simulation and Modeling with verified mark schemes, formula notation, and recurrence frequency.

Showing 30 of 30 top repeated questions

Introduction to Simulation

1 Question
#1Repeated 6 Times[8 Marks]Introduction to Simulation
Explain various steps in a simulation study with a detailed block diagram/flowchart. List the advantages and disadvantages of simulation.
Appeared in:2082 Chaitra2082 Shrawan2081 Chaitra2081 Shrawan2080 Chaitra2079 Chaitra

Physical and Mathematical Models

3 Questions
#1Repeated 6 Times[8 Marks]Physical and Mathematical Models
Differentiate between static mathematical model and dynamic mathematical model with necessary mathematical equations and a practical example of each model.
Appeared in:2082 Chaitra2082 Shrawan2081 Chaitra2081 Shrawan2080 Chaitra2079 Chaitra
#2Repeated 3 Times[8 Marks]Physical and Mathematical Models
Explain the Monte Carlo Simulation method. Show how Monte Carlo integration estimates the value of $\pi$ and computes financial investment risk under uncertain revenue/cost probability distributions.
Appeared in:2082 Chaitra2080 Chaitra2079 Chaitra
#3Repeated 3 Times[8 Marks]Physical and Mathematical Models
Explain System Dynamics modeling. Describe Causal Loop Diagrams (CLD), reinforcing feedback loops ($R$), balancing feedback loops ($B$), and Stock and Flow diagrams with an epidemic spreading or population growth model.
Appeared in:2082 Chaitra2081 Chaitra2078 Bhadra

Simulation of Continuous System

3 Questions
#1Repeated 4 Times[8 Marks]Simulation of Continuous System
Define analog methods in simulation. Design and explain the analog computer model of an automobile suspension problem (or liver model) with necessary differential equations and block diagram.
Appeared in:2082 Chaitra2082 Shrawan2081 Shrawan2079 Chaitra
#2Repeated 3 Times[8 Marks]Simulation of Continuous System
Describe the Event-Scheduling / Time-Advance Algorithm for Discrete Event Simulation (DES). Explain Future Event List (FEL), simulation clock advance, event routines, and state variables for a single-server banking queue.
Appeared in:2082 Chaitra2081 Chaitra2079 Chaitra
#3Repeated 3 Times[8 Marks]Simulation of Continuous System
Explain Continuous System Simulation using Differential Equations. Describe Euler's method and 4th-Order Runge-Kutta (RK4) numerical integration methods for simulating a mass-spring-damper physical system.
Appeared in:2082 Chaitra2080 Chaitra2078 Bhadra

Simulation of Queuing System

6 Questions
#1Repeated 5 Times[8 Marks]Simulation of Queuing System
Explain the characteristics and performance measures of queuing systems. Explain Kendall notation and interpret $M/M/3/20/1500/FCFS$ and $D/M/1/LIFO/20/80$.
Appeared in:2082 Chaitra2081 Chaitra2081 Shrawan2080 Chaitra2079 Chaitra
#2Repeated 4 Times[8 Marks]Simulation of Queuing System
Explain the features of a Markov chain. Given brand switching probabilities where a current user of Brand A has a 70% chance to buy A again and 30% to buy B, while a user of Brand B has an 80% chance to buy B and 20% to buy A: (a) Construct the state transition diagram and transition matrix. (b) Calculate the probability that a current user of Brand A buys Brand B after 3 purchases. (c) If 60% of consumers initially use Brand A, find the market share after 3 purchases.
Appeared in:2082 Shrawan2081 Chaitra2080 Chaitra2079 Chaitra
#3Repeated 3 Times[8 Marks]Simulation of Queuing System
In a single server queue ($M/M/1$), customers arrive according to a Poisson process at a rate of one every 40 minutes and service time takes 30 minutes exponentially distributed. Find the server utilization, average queue length $L_q$, average waiting time in queue $W_q$, and average time spent in the system $W$.
Appeared in:2079 Chaitra2078 Chaitra2075 Chaitra
#4Repeated 3 Times[8 Marks]Simulation of Queuing System
Derive steady-state probabilities, average queue length ($L_q$), average system length ($L$), waiting time in queue ($W_q$), and waiting time in system ($W$) for an $M/M/1$ queuing system using Little's Law ($L = \lambda W$).
Appeared in:2082 Chaitra2080 Chaitra2077 Magh
#5Repeated 3 Times[8 Marks]Simulation of Queuing System
Explain an $M/M/c$ multi-server queuing system. Derive the Erlang-C delay probability formula and calculate the probability that an arriving customer must wait in queue.
Appeared in:2082 Chaitra2081 Chaitra2078 Kartik
#6Repeated 3 Times[8 Marks]Simulation of Queuing System
Explain Markov Chains: Transition Probability Matrix ($P$), Chapman-Kolmogorov equations, absorbing states, and steady-state vector $\pi P = \pi$. Calculate long-term market share for a brand switching process.
Appeared in:2082 Chaitra2080 Chaitra2076 Chaitra

Random Number

7 Questions
#1Repeated 5 Times[8 Marks]Random Number
Explain the Poker test for random number independence. A sequence of 10,000 four-digit numbers yields: 5120 all different, 4230 one pair, 560 two pairs, 75 three of a kind, and 15 four of a kind. Using Chi-Square test at $\alpha = 0.05$ (critical $\chi^2 = 9.49$), determine whether these random numbers are independent.
Appeared in:2082 Chaitra2082 Shrawan2081 Chaitra2081 Shrawan2080 Chaitra
#2Repeated 3 Times[8 Marks]Random Number
Define pseudo-random numbers and their desired properties. Explain the Linear Congruential Method (LCM). Using the mixed congruential formula $X_{i+1} = (17X_i + 43) \pmod{100}$ with seed $X_0 = 27$, generate a sequence of six random numbers.
Appeared in:2082 Shrawan2079 Chaitra2078 Chaitra
#3Repeated 3 Times[8 Marks]Random Number
Write down the algorithm for Kolmogorov-Smirnov (KS) test. Perform a uniformity test using KS test with level of significance $\alpha = 0.05$ on generated numbers: $0.44, 0.81, 0.14, 0.05, 0.93$ (given critical $D_{0.05} = 0.565$).
Appeared in:2081 Chaitra2079 Chaitra2078 Chaitra
#4Repeated 3 Times[6 Marks]Random Number
Write down the algorithm for the Gap test and Autocorrelation test for examining the independence of pseudo-random numbers.
Appeared in:2081 Chaitra2081 Shrawan2078 Chaitra
#5Repeated 3 Times[8 Marks]Random Number
Derive the Kolmogorov-Smirnov (K-S) Test and Chi-Square Goodness-of-Fit Test for verifying uniformity and independence of pseudo-random numbers at significance level $\alpha = 0.05$.
Appeared in:2082 Chaitra2081 Chaitra2078 Bhadra
#6Repeated 3 Times[8 Marks]Random Number
Explain Linear Congruential Generators (LCG) $X_{i+1} = (a X_i + c) \pmod m$. State the Hull-Dobell Theorem for achieving full period $m$. Generate 5 pseudo-random numbers for $a=13, c=7, m=64, X_0=5$.
Appeared in:2082 Chaitra2080 Chaitra2076 Chaitra
#7Repeated 3 Times[8 Marks]Random Number
Explain Inverse Transform Technique, Acceptance-Rejection Method, and Box-Muller Transformation for generating non-uniform random variates (Exponential, Uniform, and Normal distributions).
Appeared in:2082 Chaitra2081 Chaitra2079 Chaitra

Verification and Validation of Simulation Models

2 Questions
#1Repeated 4 Times[6 Marks]Verification and Validation of Simulation Models
Explain Naylor and Finger's three-step approach used in the validation process of simulation models. How do verification and validation differ in simulation?
Appeared in:2082 Chaitra2081 Chaitra2080 Chaitra2079 Chaitra
#2Repeated 3 Times[8 Marks]Verification and Validation of Simulation Models
Explain Model Verification vs Model Validation in simulation. Describe Face Validity, Historical Data Validation, Turing Test, and Sensitivity Analysis techniques.
Appeared in:2082 Chaitra2081 Chaitra2077 Magh

Analysis of simulation output

4 Questions
#1Repeated 4 Times[6 Marks]Analysis of simulation output
How can you analyze simulation output using simulation run statistics? Explain methods for the elimination of initial bias (warm-up period) in steady-state simulations.
Appeared in:2082 Chaitra2081 Chaitra2081 Shrawan2079 Chaitra
#2Repeated 3 Times[5 Marks]Analysis of simulation output
Explain the Replication of Runs method for a single-server queue ($M/M/1$) simulation. How does it enable constructing confidence intervals for performance measures?
Appeared in:2082 Chaitra2080 Chaitra2078 Chaitra
#3Repeated 3 Times[8 Marks]Analysis of simulation output
Explain Simulation Output Analysis for terminating vs steady-state non-terminating systems. Describe the replication method, batch means method, and Welch's graphical procedure for identifying initialization warmup bias.
Appeared in:2082 Chaitra2080 Chaitra2078 Kartik
#4Repeated 3 Times[8 Marks]Analysis of simulation output
Explain Variance Reduction Techniques in stochastic simulation: Common Random Numbers (CRN), Antithetic Variates, and Control Variates. Prove how Antithetic Variates reduce variance of estimator $\bar{X}$.
Appeared in:2082 Chaitra2081 Chaitra2076 Chaitra

Simulation software

4 Questions
#1Repeated 5 Times[6 Marks]Simulation software
How is memory and CPU simulation conducted in a computer system? Explain the different levels of abstraction in computer system simulation.
Appeared in:2082 Chaitra2082 Shrawan2081 Chaitra2080 Chaitra2079 Chaitra
#2Repeated 4 Times[6 Marks]Simulation software
Explain the implementation of a single-server queuing simulation model using Java with flowcharts, event scheduling, and simulation clock advancement.
Appeared in:2082 Chaitra2082 Shrawan2081 Chaitra2081 Shrawan
#3Repeated 3 Times[6 Marks]Simulation software
What do you mean by simulation software? Explain at least three GPSS block diagrams (GENERATE, QUEUE, SEIZE, DEPART, ADVANCE, RELEASE, TERMINATE) with an example of a service facility.
Appeared in:2080 Chaitra2079 Chaitra2078 Chaitra
#4Repeated 3 Times[6 Marks]Simulation software
Describe Simulation Languages and Software Tools: GPSS, SIMSCRIPT, Arena, and MATLAB/Simulink. Compare general-purpose high-level programming languages (Python/C++) with special-purpose simulation packages.
Appeared in:2082 Chaitra2080 Chaitra2077 Magh

Curriculum Syllabus & Course Topics

Sourced from TU curriculum portal
Full Syllabus (PDF)
Chapter-wise Units & Micro-Syllabus Topics (10 Units)

  1. 1. Introduction to Simulation

    • 1.1System and system environment concepts
    • 1.2Continuous and discrete systems
    • 1.3Types of models
    • 1.4Model development life cycle
    • 1.5Simulation and steps in simulation study
    • 1.6Advantages and disadvantages of simulation
    • 1.7Monte-Carlo simulation
    • 1.8Discrete-event system simulation

  2. 2. Physical and Mathematical Models

    • 2.1Differential and partial differential equations
    • 2.2Static physical model
    • 2.3Dynamic physical model
    • 2.4Static mathematical models
    • 2.5Dynamic mathematical models

  3. 3. Simulation of Continuous System

    • 3.1Continuous system models
    • 3.2Analog computer
    • 3.3Analog methods
    • 3.4Hybrid simulation
    • 3.5Digital-analog simulators
    • 3.6Continuous system simulation languages (CSSLs)
    • 3.7Feedback systems

  4. 4. Simulation of Queuing System

    • 4.1Elements of queuing system
    • 4.2Characteristics of queuing systems
    • 4.3Model of queuing system
    • 4.4Types of queuing system
    • 4.5Queuing notation (Kendall’s notation)
    • 4.6Measurement of system performance
    • 4.7Network of queues
    • 4.8Applications of queuing system

  5. 5. Markov Chains

    • 5.1Key features of Markov chains
    • 5.2Markov process with examples
    • 5.3Applications of Markov chains

  6. 6. Random Number

    • 6.1Properties of random numbers
    • 6.2Generation of pseudo-random numbers
    • 6.3Random number generation: Linear and arithmetic congruential methods
    • 6.4Tests for random numbers
    • 6.4.1Kolmogorov-Smirnov test
    • 6.4.2Chi-Square (𝛘2) test
    • 6.4.3Gap test
    • 6.4.4Poker’s method
    • 6.4.5Testing for auto correlation
    • 6.5Generating discrete distribution
    • 6.6Inversion, rejection, composition and convolution

  7. 7. Verification and Validation of Simulation Models

    • 7.1Verification and validation
    • 7.2Verification of simulation models
    • 7.3Calibration and validation of models
    • 7.4Naylor and finger validation process
    • 7.5Validation: Errors

  8. 8. Analysis of simulation output

    • 8.1Confidence intervals and hypothesis testing
    • 8.2Estimation methods
    • 8.3Simulation run statistics
    • 8.4Replication of runs
    • 8.5Elimination of initial bias

  9. 9. Simulation software

    • 9.1Simulation in Java
    • 9.2Simulation in GPSS
    • 9.3Simulation in Python
    • 9.4Other simulation software

  10. 10. Simulation of Computer Systems

    • 10.1Simulation tools
    • 10.2High level computer: System simulation
    • 10.3CPU simulation
    • 10.4Memory simulation
    • 10.5Simulation of computer networks

Examination Scheme & Marks Distribution

Evaluation Structure

  • Final Board Theory Exam: 60 Marks (Pass mark: 24)
  • Internal Assessment: 40 Marks (Pass mark: 16)
  • Practical / Lab Exam: 25 or 50 Marks (Continuous lab evaluation + viva, where applicable)

* This is the general current IOE 60/40 scheme; verify course-specific details in the syllabus above.

Exam Preparation Guidelines

  • Review the available past examination paper to understand question styling, typical derivation topics, and marks allocation.
  • Cross-reference key answers with official syllabus units, standard textbooks, and lecture notes.
  • Structure answers with labeled diagrams, concise bullet points, and highlight final answers in numerical solutions.

Frequently Asked Questions (Simulation and Modeling)

Q: How can I download Simulation and Modeling past question papers?

You can preview or download the Simulation and Modeling question papers (PDF) directly using the built-in viewer on this page with zero redirects or paywalls.

Q: What is the pass mark for Simulation and Modeling?

The general current scheme is a 60-mark final theory exam and a 40-mark internal assessment, with pass marks of 24 and 16. Verify the course-specific syllabus above.

Q: Where can I find the complete syllabus for this subject?

The available chapter-wise syllabus and topic breakdown is indexed in the Syllabus section above, with links to the curriculum PDF source.

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