Lecture-01

Outline

Modeling and SimulationWhat?Why?UsesTaxonomy

Model Development Life Cycle

Modeling and Simulation

ModelA model (usually miniature) is a

representation of the construction and working of some system of interest

It is similar to but simpler than the system it represents

A good model is a tradeoff between realism and simplicity.

Modeling and Simulation (Cont…)

It is description of observed behavior, simplified by ignoring certain details. Models allow complex systems to be understood and their behavior predicted within the scope of the model, but may give incorrect descriptions and predictions for situations outside the realism of their intended use.

Modeling and Simulation (Cont…)Simulation

simulation is a tool to evaluate the performance of a system , existing or proposed, under different configurations of interest and over long periods of real time.

Simulation of a system is the operation of a model of the system. The operation of the model can be studied, and hence, properties concerning the behavior of the actual system or its subsystems can be inferred.

Why Simulate?It may be too difficult, dangerous, or expensive to observe

a real, operational system

Parts of the system may not be observable (e.g., internals of a silicon chip or biological system)

Uses of simulations • Analyze systems before they are built Reduce number of design mistakesOptimize designAnalyze operational capabilities of systemsCreate virtual environments for training, entertainment

Applications: System Analysis“Classical” application of simulation

Telecommunication networksTransportation systemsElectronic systems (e.g., microelectronics,

computer systems)Battlefield simulationsManufacturing systemsLogistics

Applications

Virtual EnvironmentsUses: training (e.g., military, medicine,

emergency planning), entertainmentSimulations are often used in virtual

environments to create dynamic computer generated entitiesAdversaries and helpers in video gamesDefense: Computer generated forces (CGF)

Automated forces Semi‐automated forces

Virtual Environments (Cont…)

Physical phenomena Trajectory of projectiles Buildings “blowing up” Environmental effects on environment (e.g., rain

washing out terrain)

Examples

Simulation FundamentalsA computer simulation is a computer program

that models the behavior of a physical system over time.Program variables (state variables) represent

the current state of the physical systemSimulation program modifies state variables to

model the evolution of the physical system over time.

Defense SimulationsTypes of simulation

Constructive: simulated people operating simulated equipment

Virtual: real people operating simulated equipment,

Live: real people operating real equipmentMajor application areas

AnalysisWar gaming, logistics

Defense SimulationsTraining

Platform level, Command levelTest and evaluation

Hardware‐in‐the‐loop

Types of Simulation Models

Stochastic vs. DeterministicStochastic simulation: a simulation that

contains random (probabilistic) elements, e.g.,Examples

Inter‐arrival time or service time of customers at a restaurant or store

Amount of time required to serve a customer

Output is a random quantity (multiple runs required analyze output)

Stochastic vs. DeterministicDeterministic simulation: a simulation

containing no random elementsExamples

Simulation of a digital circuit Simulation of a chemical reaction based on

differential equations

Output is deterministic for a given set of inputs

Static vs. Dynamic ModelsStatic models

Model where time is not a significant variableExamples

Determine the probability of a winning solitaire hand

Static + stochastic = Monte Carlo simulation Statistical sampling to develop approximate

solutions to numerical problems

Dynamic modelsModel focusing on the evolution of the system

under investigation over time

Continuous vs. DiscreteDiscrete

State of the system is viewed as changing at discrete points in time

An event is associated with each state transition Events contain time stamp

ContinuousState of the system is viewed as changing

continuously across timeSystem typically described by a set of differential

equations

Overall View of M&S

Model Development Life Cycle

Determine Goals and ObjectivesWhat do you (or the customers) hope to

accomplish with the modelMay be an end in itself

Predict the weather Train personnel to develop certain skills (e.g.,

driving)

More often a means to an end Optimize a manufacturing process or develop the

most cost effective means to reduce traffic congestion in some part of a city

Determine Goals and ObjectivesOften requires developing a business case to

justify the costImproved efficiency will save the company

moneyEven so, may be hard to justify in lean times

Goals may not be known when you start the project!One often learns things along the way

Develop Conceptual ModelAn abstract (i.e., not directly executable)

representation of the systemWhat should be included in model? What can

be left out?What abstractions should be used

Level of detailOften a variation on standard abstractions

Develop Conceptual Model

Example: transportation Fluid flow? Queuing network? Cellular automata?

What metrics will be produced by the model?Appropriate choice depends on the purpose of

the model

Develop Computational ModelExecutable simulation modelSoftware approach

General purpose programming languageSpecial purpose simulation languageSimulation package

Approach often depends on need for customization and economicsWhere do you make your money?Defense vs. commercial industry

Other (non‐functional) requirementsPerformance Interoperability with other models/tools/data

VerificationDid I build the model right?Does the computational model match the

specification model?Largely a software engineering activity

(debugging)Not to be confused with correctness (see

model validation)!

ValidationDid I build the right model?Does the computational model match the actual (or

envisioned) system?Typically, compare against

Measurements of actual systemAn analytic (mathematical) model of the systemAnother simulation model

By necessity, always an incomplete activity!Often can only validate portions of the model If you can validate the simulation with 100% certainty

why build the simulation?

Steps in Model Development

SummaryModeling and simulation is an important, widely

used technique with a wide range of applicationsComputation power increases (Moore’s law) have

made it more pervasiveIn some cases, it has become essential (e.g., to be

economically competitive)Rich variety of types of models, applications, uses

As easy (actually, easier!) to get wrong or misleading answers as it is to get useful results

Appropriate methodologies required to protect against major mistakes. Even so…