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# Note for Simulation and Modelling - SM By Bput Toppers

• Simulation and Modelling - SM
• Note
• Biju Patnaik University of Technology Rourkela Odisha - BPUT
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#### Note for Simulation and Modelling - SM By Bput Toppers

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Lecture Notes of Modeling and Simulation 7th Sem IT BCS-408 Module I MODELING & SIMULATION (3-1-0) Cr.-4 (10 Lectures) Inventory Concept: The technique of Simulation. : 1 class Major application areas, concept of a System. : 1 class Environment. : 1 class Continuous and discrete systems. : 1 class Systems modeling, types of models. : 1 class Progress of a Simulation Study. : 1 class Monte Carlo Method. : 1 class Comparison of Simulation and Analytical Methods. : 1 class Numerical Computation Technique for discrete and continuous models. Continuous System Simulation. ;1 class Revision Module II : 1 class (12 Lectures)

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Probability Concepts in Simulation: 2 classes Stochastic variables, Discrete and Continuous Probability Functions. 2 classes Numerical evaluation of continuous probability functions, continuous uniformly distributed random numbers. : 2 classes Random Number Generators – Linear congruential Generator, Mid Square Method, Multiplicative Congruential generator, rejection Method. : 2 classes Testing of random Numbers. : 2 classes Generation of Stochastic variants. : 1 class Arrival Patterns Service times. : 1 class Revision Module III (10 Lectures) Discrete System Simulation and GPSS: Discrete Events, Representation of Time, generation of arrival patterns. : 2 classes Fixed time step versus next event simulation, Simulation of a Telephone System, Delayed calls . : 2 classes Introduction to GPSS: Creating and moving transactions, queues. : 2 classes Facilities and storages, gathering statistics, conditional transfers, program control statements, priorities and parameters. : 2 classes Standard numerical attributes, functions, gates, logic switches and tests, Variables, Select and Count. : 2 classes Revision Module IV (10 Lectures) Simulation Languages and Practical Systems : 1 class Continuous and discrete systems languages, factors in the section of discrete systems simulation language. ; 2 classes Computer model of queuing, inventory and scheduling systems. : 2 classes Design and Evaluation of simulation Experiments: Length of simulation runs, validation, variance reduction techniques. : 2 classes Experimental layout, analysis of simulation output, Recent trends and developments. : 1 class Revision Books: 1. 2. System Simulation – Geoffrey Gordon, 2nd Edition, PHI System Simulation with Digital computer – Narsingh Deo, PHI

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Module-I Objectives:    To give an overview of the course (Modeling & simulation). Define important terminologies. Classify systems/models System: any set of interrelated components acting together to achieve a common objective. Examples: 1. Battery • Consists of anode, cathode, acid and other omponents. • These components act together to achieve one objective like preserving electricity. 2. University • Consists of professors, students and employees. • These objects act together to achieve the objective of teaching & learning process. A system consists of • Inputs Elements that cause changes in the systems variables. • Outputs Response • Systems (process) Defines the relationship between the inputs and outputs Some Possible Inputs • Inlet flow rate • Temperature of entering material

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• Concentration of entering material Some Possible Outputs • Level in the tank • Temperature of material in tank • Outlet flow rate • Concentration of material in tank Qn: What inputs and outputs are needed when we want to model the Inventory Control System? Model: A model describes the mathematical relationship between inputs and outputs. Simulation: is the process of using the mathematical model to determine the response of the system in different situations in a Computer system. Classification of Systems Systems can be classified based on different criteria: • • Spatial characteristics: lumped & distributed • Continuity of the time variable: Continuous, discrete-time • Quantization of dependent variable: Quantized & Nonquantized • Parameter variation: time varying & fixed (time-invariant) Superposition principle: linear & nonlinear Continuous-time System: • The signal is defined for all t in an interval [ti, tf] Discrete-time System: • The signal is defined for a finite number of time points {t0, t1,…} A system is linear: • if it satisfies the super position principle. • A system satisfies the superposition principle if the following conditions are satisfied: 1. Multiplying the input by any constant, multiplies the output by the same constant. 2. The response to several inputs applied simultaneously is the sum of individual response to each input applied separately.