Welcome
To Our Presentation

Group name:
Shopnochari

Group Member:
Name ID
Debashish Kumer Shingho 123-15-
2054
Md. Saddam Hossain 123-15-2010
MST.Eshita Katun 123-15-2081
Antim 123-15-2162

Importance of simulation & Systemwith model

Originof simulation word ---
Middle English
simulacion
&
Latin simulātiōn-
(stem of simulātiō)

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.

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.

SimulationModeling Workflow---
Use a 2D or 3D CAD tool to develop a virtual
model, also known as a digital prototype
Generate 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.

Simulationis 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.

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.

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.

Advantage:

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.

Areas of Application:

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

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.

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.

Deterministic Simulation Models
• A model that does not contain probability.
• Every run will result the same.
• Single run is enough to evaluate the result.

Stochastic Simulation Models
• A model that contains probability.
using random numbers.
 Every run will result differently.
• Multiple runs are required to evaluate the
results.

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 concrete
Goals change with increasing insight

Example for process Model

Diagram of simulation & modeling

Modeling ---
 Disadvantages:
 Higher software cost .
 Additional training required.
 Limited portability.
 Advantages:
 Standard features often needed .
 Shorter development cycle .
 Very readable code.

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

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

Types of System:
There are two types of system.
 Discrete System
 Continuous System

What system made of:
Some important key concept of a system is given below
 Entity
 Attribute
 Activity
 State
 Event
 Endogenous
 Exogenous

Entity:
Entityis a real world object in the system

Attribute:
A property of an entity

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

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

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

Endogenous:
Endogenous describe activities and events occurring within a system.
Exogenous
Exogenous describe activities and events in
an environment that affect the system