How modeling and Simulation works

what is numerical simulation and modeling,what is difference between simulation and modeling, lecture notes on system simulation and modeling, what is modeling virtual environments and simulation
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Published Date:23-07-2017
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Si Simullattiion and d M Mod deli ling By Pf Prof. SS.Sh Shakkya 1Si Simullati tion and d M Mod deli ling L L-3T 3, T-1P 1, P-1 15 .5 2References: 1. G. Gorden, “ System simulation” 2. Jerry Banks, John S. Carson, II Barry L. Nelson , David M. Nocol, “Discrete Event system simulation” 3Introduction to Modeling and simulation 4System  The term system is derive from the Greek word systema, which means an organized relationship among functioning units units or or components components.  System exists because it is designed to achieve one or more objectives.  We We come come into into daily daily contact contact with with tthe he transportation transportation system system, the telephone system, the accounting system, the production system, and for two decades the computer system.  There There a are re more more than than a a hundred hundred d definitions efinitions of of the the word word system, but most seem to have a common thread that suggests that a system is an orderly grouping of interdepp pendent components linked tog gether according g to a plan to achieve a specific objective. 5System  The The study study of of the the systems systems concepts concepts, tthen hen, has has three basic implications: 1. 1. A A system system must must be be designed designed to to achieve achieve a a predetermined objective 2. Interrelationships and interdependence must exist among the components 3. The objectives of the organization as a whole hh have a hiigh her priioriitty tthhan tthhe ob bjjecttiives off iitts subsystems. 6System  Klir Klir gives gives a a collection collection o of f 2 24 4 definitions definitions one one such such definition is “ A system is a collection of components wherein individual components are consttraiinedd b by connect tiing it interrelt latiionsh hiips such h that the system as a whole fulfills some specific functions in response to varying demands” Klir, George J. , an approach to general systems theory theory, New New York: York: Van Van Nostrand Nostrand Reinhold Reinhold Co Co, 1969 7SSk ome keyword ds t to k know …  System  It It iis a coll llect tiion off entiti tities th thatt actt and d iintteractt together toward the accomplishment of some logg( ical end (comp puter,, network,, communication systems, queuing systems etc.)  Simulation  It is an experiment in a computer where the real system is replaced by the execution of the program  It is a program that mimics (imitate) the behaviour of of the the real real system systemSome keywords to know …  Model  It is a simplification of the reality  A (usually miniature) representation of something; an example for imitation or emulation  A model can be Analytical (Queuing Theory) or by Simulation.  Performance evaluation (of a system)  It means quantifying the service delivered by the System  E Experiimenttall, A Anallyti ticall, or b by siimullati tionIntroduction St System · A system exists and operates in time and space.  Model · A model is a simplified representation of a system at some some particular particular point point in in time time or or space space iintended ntended tto o promote understanding of the real system.  Simulation · A simulation is the manipulation of a model in such a way way tthat hat it it operates operates on on time time or or space space to to compress compress it, it, thus enabling one to perceive the interactions that would not otherwise be apparent because of their separation separation in in ttime ime o or r s space. pace. 10EEl xamples Models of the sy ystem Real System (Motherboard)EEl xamples Simulation models of the systemEEl xamplesEEl xample Models of the SystemExamples Models of the sy ystem Circuit SimulatorConcept of Simulation  Simulation Simulation is is the the representation representation o of f a a real real life life system by another system, which depicts the important characteristics of the real system and all llows experiimenttati tion on it it.  In another word simulation is an imitation of the reality y.  Simulation has long been used by the researchers, analysts, designers and other professionals professionals in in the the physical physical and and non non-physical physical experimentations and investigations. 16Why Why S Simulate? imulate?  It mayy, be too difficult, hazardous,, or exppensive 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 Analyze systems systems before before tthey hey are are built built  Reduce number of design mistakes  Optimize design  Analyze Analyze operational operational systems systems  Create virtual environments for training, entertainment 17When to use Simulation  Over the years tremendous developments have taken place in computing capabilities and in special purpose simulation languages, and in simulation methodologies.  Th The use off siimullat tiion ttech hniiques h has allso b become widespread.  Following are some of the purposes for which simulation may may b be e u used sed. 1. Simulation is very useful for experiments with the internal interactions of a complex system, or of a subsystem within a a c complex omplex system system. 2. Simulation can be employed to experiment with new designs and policies, before implementing 3 3. S Simulation imulation c can an be be used used to to verify verify the the r results esults obtained obtained by by analytical methods and reinforce the analytical techniques. 4. Simulation is very useful in determining the influence of changes changes in in input input variables variables on on the the output output of of the the system. system. 5. Simulation helps in suggesting modifications in the system 18 under investigation for its optimal performance.TTf ypes of SiSimullatition MModdells SSt ystem moddell stochastic deterministic static dynamic static dynamic Monte Carlo simulation continuous continuous discrete discrete Continuous Discrete-event Continuous Discrete-event simulation simulation simulation simulationTypes of Simulation Models  Simulation models can be classified as being static or dynamic, deterministic or stochastic and discrete or continuous continuous.  A static simulation model represents a system, which does not change with time or represents the system at a particular p point in time.  Dynamic simulation models represent systems as they change over time.  Deterministic models have a known set of inp, puts, which result into unique set of outputs.  In stochastic model, there are one or more random input variables, which lead to random outputs.  System in which the state of the system changes continuously with time are called continuous systems while the systems in which the state changes abruptly at discrete poiit nts iin t tiime calllled d d diiscrette systtems. 20

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