introduction to simulation and modeling

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Page 1: Introduction to simulation and modeling

Welcome To Our Presentation

Page 2: Introduction to simulation and modeling

Group name:Shopnochari

Page 3: Introduction to simulation and modeling

Group Member: Name IDDebashish Kumer Shingho

123-15-2054Md. Saddam Hossain

123-15-2010MST.Eshita Katun

123-15-2081Antim 123-15-2162

Page 4: Introduction to simulation and modeling

Importance of simulation & System with model

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Origin of simulation word ---

Middle English simulacion

&Latin simulātiōn- (stem of simulātiō)

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Simulation ---?

Simulation modeling is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world.Simulation modeling is used to help designers and engineers understand whether, under what conditions, and in which ways a part could fail and what loads it can withstand.

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Simulation in Computer science---simulation has some specialized meanings – Alan Turing used the term "simulation" to refer to what happens when a universal machine executes a state transition table that describes the state transitions, inputs and outputs of a subject discrete-state machine.

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Simulation Modeling Workflow ---

Use a 2D or 3D CAD tool to develop a virtual model, also known as a digital prototypeGenerate a 2D or 3D mesh for analysis calculations.Define finite element analysis data based on analysis type.Perform finite element analysis, review results, and make engineering judgments based on results.

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Simulation is Needed experiment with new

designs or policies prior to implementation

can be used to verify analytic solutions

different capabilities for a machine, requirements can be determined.

designed for training allow learning without the cost and disruption of on-the-job learning.

Simulation is not Needed

problem can be solved using common sense

simulation costs exceed the savings

Resources or time are not available

system behavior is too complex or can’t be defined.

isn’t the ability to verify and validate the model.

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Why is Modeling and Simulation Important in Engineering?

Unavailable input and output. Experiment may be too dangerous. Cost of experimentation might be too high. Time constants of the system may not be compatible

with human dimensions. Experimental behavior might be obscured by

disturbances.

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Advantage: New polices, operating procedures, decision

rules, information flows, organizational procedures.

New hardware designs, physical layouts, transportation systems.

Hypotheses about how or why certain phenomena occur can be tested for feasibility.

Insight can be obtained about the interaction of variables.

Insight can be obtained about the importance of variables to the performance of the system.

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Advantage:

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Disadvantages:

There are disadvantages in using a simulation model:-

We have a poor understanding of how some physical systems work so that we do not have sufficient data to produce a mathematical model. For this reason it has not been possible to create simulations that can accurately predict the occurrence and effects of earthquakes and tsunami.

The formula and functions that are used may not provide an accurate description of the system resulting in inaccurate output from the simulation.

Complex simulations can require the use of a computer system with a fast processor and large amounts of memory.

Simulation results may be difficult to interpret. Simulation modeling and analysis can be time consuming and

expensive.

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Areas of Application:

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What is Model?•Representation of a real or theoretical System.•Simplification of the System.•Understanding of the System.

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Why we need modeling ?

Cost effective way to represent a real-world system.

Key aspects of the system, components. And how those components communicate

with one another. To test designs before implementation.

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Model Types

• Visual Models : Graphical sketches, Computer solid models

Physical Models: Prototypes, mock-ups, structural models.

• Logical Models : Algebraic and different equation used for computer simulation.

Empirical Models: Relationship between variables.

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Deterministic Simulation Models

• A model that does not contain probability.

• Every run will result the same.• Single run is enough to evaluate the

result.

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Stochastic Simulation Models

• A model that contains probability. using random numbers.Every run will result differently.• Multiple runs are required to

evaluate the results.

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Define An Achievable Goal

To model the…” is NOT a goal!“To model the…in order to select/determine

feasibility/…is a goal.Goal selection is not cast in concreteGoals change with increasing insight

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Example for process Model

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Diagram of simulation & modeling

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Modeling --- Disadvantages:

Higher software cost . Additional training required. Limited portability.

Advantages: Standard features often needed . Shorter development cycle . Very readable code.

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What is a System:A set of principles or procedures according to which something is done; an organized scheme or method. Primary objective is complete

a task Object are connected together Follow set of defined rules

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System Environment ---where all the system objects are grouped together to accomplish the task.

System Boundary:System boundary are something to detect whether the changes occurs inside the system or outside the system

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Types of System:There are two types of system.

Discrete System Continuous System

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What system made of:Some important key concept of a system is given below

Entity Attribute Activity State Event Endogenous Exogenous

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Entity:Entity is a real world object in the system

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Attribute: A property of an entity

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Activity: A time period or task which is done of specified length.

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State: The collection of variables necessary to describe the system at any time

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Event:An sudden occurrence that may change the state of the system.

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Endogenous: Endogenous describe activities and events occurring within a system.

ExogenousExogenous describe activities and

events in an environment that affect the system