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Mesleki İngilizce - Technical English

II • Notes: Prof. Dr. Nizamettin AYDIN – In the slides, • texts enclosed by curly parenthesis, {…}, are examples. • texts enclosed by square parenthesis, […], are [email protected] explanations related to examples.

http://www.yildiz.edu.tr/~naydin

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Computer Simulation

• Learning Objectives • Keywords – to acquire basic knowledge about simulation kinds and – history • an abstract model that uses mathematical language to – to understand difference between simulation and describe a system modelling – to understand the power of simulation and its influence – process on modern science • a process with an indeterminate or random element as • Sub-areas covered opposed to a deterministic process that has no random element – Computer simulation – Discrete – – Mathematics • not supporting or requiring the notion of continuity – discrete objects are countable sets such as integers

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Computer Simulation Computer Simulation

• Keywords • Reading text – Computer Generated Imagery (CGI) • an application of the field of computer graphics (or, more • Pre-reading questions specifically, ) to special effects in films, television programs, commercials and simulation – How can we solve problems in cases where – differential physical models are too complex or expensive to • a mathematical equation for an unknown function of one or build? several variables that relates the values of the function itself and of its derivatives – Name some problems which can be solved using – Gamut computer simulation? • a complete range or extent – • a computational algorithm which relies on repeated random sampling to compute its results

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1 Computer Simulation Computer Simulation

• A computer simulation • Computer vary from computer programs • also referred to as a computer model or a computational model that run a few minutes, to network-based groups of – is a computer program, or network of , that computers running for hours or ongoing simulations attempts to simulate an abstract model of a particular that run for days. system. • The scale of events being simulated by computer simulations has far exceeded anything possible (or • Computer simulations have become a useful part of the perhaps even imaginable) using the traditional paper- mathematical modelling of many natural systems in and-pencil mathematical modelling: over 10 years ago. (), and ; • A desert-battle simulation, of one force invading human systems in , , and social another, involved the modelling of 66,239 tanks, trucks science, and in the process of new and other on simulated terrain around Kuwait, , so as to gain insight into the operation of using multiple supercomputers in the DoD High those systems or to observe their behaviour. Performance Computer Modernization Program.

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Computer Simulation Simulation versus modelling

• A desert-battle simulation, of one force invading • Traditionally, the formal modelling of systems has another, involved the modelling of 66,239 tanks, trucks and other vehicles on simulated terrain around Kuwait, been via a mathematical model, using multiple supercomputers in the DoD High – which attempts to find analytical solutions to problems, Performance Computer Modernization Program. • which enables the of the behaviour of the system from a • Another simulation ran a 1-billion-atom model, where set of parameters and initial conditions. previously, a 2.64-million-atom model of a ribosome, in • While computer simulations might use some 2005, had been considered a massive computer simulation. algorithms from purely mathematical models, • The Blue Brain project at EPFL (École Polytechnique computers can combine simulations with the reality of Fédérale de Lausanne, Switzerland) began in May 2005 actual events, such as generating input responses to to create the first computer simulation of the entire simulate test subjects that are no longer present. human brain, right down to the molecular level.

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Simulation versus modelling Simulation versus modelling

• Although the missing test subjects (i.e. the • However, computer simulation also includes users of equipment or systems) are being generating inputs from simulated users to run modelled/simulated, actual computer software or equipment, – the whole process can be conducted with the actual – with only part of the system being modelled: equipment or system they use, • an example would be flight simulators which can run • revealing performance limits or defects in long-term use by the simulated users. machines as well as actual flight software. • Note that the term computer simulation is • Computer simulations are used in many fields, broader than computer modelling, including – which implies that all aspects are being modelled in – science, technology, entertainment, and business the computer representation. planning and scheduling.

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2 History History

• Computer simulation was developed hand-in-hand • There are many different types of computer with the rapid growth of the computer, simulation; – following its first large-scale deployment during the – the common feature they all share is the attempt to Manhattan Project in World War II to model the generate a sample of representative scenarios for a process of nuclear detonation. model in which a complete enumeration of all possible • It was a simulation of 12 hard spheres using a Monte Carlo states of the model would be prohibitive or impossible. algorithm. • Computer models were initially used as a • Computer simulation is often used as an adjunct supplement for other arguments, but their use later to, or substitution for, modelling systems for became rather widespread. which simple closed form analytic solutions are • The data input/output for the simulation can be not possible. either through formatted text files or a pre- and – [adjunct:something joined or added to another thing post processor. but not essentially a part of it]

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Types of computer simulation Types of computer simulation

• Computer models can be classified according – For example, steady-state models use to several criteria including: defining the relationships between elements of the modelled system and attempt to find a state in – stochastic or deterministic which the system is in equilibrium. • and as a special case of deterministic, chaotic – steady-state or dynamic • Such models are often used in simulating – continuous or discrete physical systems as a simpler modelling case • and as an important special case of discrete, discrete before dynamic simulation is attempted. event or DE models • Dynamic simulations model changes in a – local or distributed. system in response to (usually changing) input signals.

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Types of computer simulation Types of computer simulation

• Stochastic models use random number generators to • A continuous dynamic simulation performs model chance or random events; numerical solutions of differential-algebraic – they are also called Monte Carlo simulations. equations or differential equations (either partial • A discrete event simulation (DES) manages events in or ordinary). . – Periodically, the simulation program solves all the – Most computer, logic-test and fault-tree simulations are of equations, and uses the numbers to change the state and this type. output of the simulation. • In this type of simulation, the simulator maintains a queue of events sorted by the simulated time in which they should occur. • Applications include • The simulator reads the queue and triggers new events as each event – flight simulators, is processed. – It is not important to execute the simulation in real time. – simulation games, – It’s often more important to be able to access the data – chemical process modelling, produced by the simulation, – simulations of electrical circuits. • to discover logic defects in the design or the sequence of events.

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3 Types of computer simulation

• Polish analog computer AKAT-1, 1959. • Originally, these kinds of simulations were • Any of a class of devices in which actually implemented on analogue computers, continuously variable physical quantities such as electrical potential, – where the differential equations could be fluid pressure, or mechanical motion are represented in a way analogous to represented directly by various electrical the corresponding quantities in the components such as op-amps. problem to be solved. • The analog system is set up according • By the late 1980s, however, most “analogue” to initial conditions and then allowed to change freely. simulations were run on conventional digital • Answers to the problem are obtained by measuring the variables in the computers that emulate the behaviour of an analog model. analogue computer.

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Types of computer simulation Types of computer simulation

• A special type of discrete simulation which does • Distributed models run on a network of not rely on a model with an underlying equation, interconnected computers, possibly through the but can nonetheless be represented formally, is . agent-based simulation. – Simulations dispersed across multiple host computers like this are often referred to as “distributed • In agent-based simulation, the individual entities simulations”. (such as molecules, cells, trees or consumers) in • There are several standards for distributed the model are represented directly (rather than by simulation, including their density or concentration) and possess an – Aggregate Level Simulation Protocol (ALSP), internal state and set of behaviours or rules which – Distributed Interactive Simulation (DIS), determine how the agent’s state is updated from – the (HLA), one time-step to the next. – the Test and Training Enabling Architecture (TENA).

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CGI computer simulation CGI computer simulation

• Formerly, the output data from a computer • Although observers couldn’t necessarily read out simulation was sometimes presented in a table, or numbers, or spout maths formulas, from observing a matrix, a moving weather chart, they might be able to – showing how data was affected by numerous changes predict events (and “see that rain was headed their in the simulation parameters. way”), much faster than scanning tables of rain- • The use of the matrix format was related to the traditional use of the matrix concept in cloud coordinates. mathematical models; • Such intense graphical displays, which – however, psychologists and others noted that humans transcended the world of numbers and formulae, could quickly perceive trends by looking at graphs or sometimes also led to output that lacked a even moving-images or motion-pictures generated from the data, as displayed by computer -generated- coordinate grid or omitted timestamps, as if imagery (CGI) animation. straying too far from numeric data displays.

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4 CGI computer simulation Computer simulation in science

• Today, models tend to balance the view • The following are generic examples of types of of moving rain/snow clouds against a map that uses numeric coordinates and numeric timestamps of events. computer simulations in science, • Similarly, CGI computer simulations of CAT scans can – which are derived from an underlying mathematical simulate how a tumour might shrink or change, during an description: extended period of medical treatment, presenting the passage of time as a spinning view of the visible human • A numerical simulation of differential equations head, as the tumour changes. which cannot be solved analytically. – [CAT scan: an X-ray image made using computerized axial – Falling into this category are: tomography] • Other applications of CGI computer simulations are being • theories which involve continuous systems such as developed to graphically display large amounts of data in phenomena in motion, as changes occur during a simulation run. • (e.g. climate models, models, roadway air dispersion models) • and

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Computer simulation in science Computer simulation in science

• A , typically used for • Specific examples of computer simulations follow: discrete systems where events occur • statistical simulations based upon an probabilistically, and which cannot be agglomeration of a large number of input profiles, described directly with differential equations such as the forecasting of equilibrium (this is a discrete simulation in the above of receiving waters, allowing the gamut of meteorological data to be input for a specific sense). locale. – Phenomena in this category include: • [gamut: the complete range or scope of something] • [agglomeration : a mass or collection of things; an • assemblage] • biochemical or gene regulatory networks with small – This technique was developed for numbers of molecules (See also: Monte Carlo method). forecasting.

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Computer simulation in science Computer simulation in science

• agent based simulation has been used effectively in • computer simulations have also been used to formally , model theories of human cognition and performance, – where it is often called individual based modelling and has e.g. ACT-R been used in situations for which individual variability in • ACT-R is a cognitive architecture: the agents cannot be neglected, – a theory about how human • such as population dynamics of salmon and trout (most purely mathematical models assume all trout behave identically) cognition works. • On the exterior, ACT-R • time stepped dynamic model; in hydrology there are looks like a programming several such hydrology transport models such as the language; SWMM and DSSAM developed by the U.S. • however, its constructs reflect assumptions about Environmental Protection Agency for river water human cognition. quality forecasting • These assumptions are • [SWMM: Storm Water Management Model] based on numerous facts • [DSSAM: Dynamic Stream Simulation and Assessment Model] derived from psychology experiments.

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5 Computer simulation in science Computer simulation in science

• computer simulation using • Understanding of statistical thermodynamic molecular for drug discovery theory is fundamental to the appreciation of molecular • computational fluid dynamics simulations are solutions. used to simulate the behaviour of flowing air, • Development of the Potential Distribution Theorem water and other fluids. (PDT) allows one to simplify this complex subject to – There are one-, two- and three- dimensional models down-to-earth presentations of molecular theory. used. • Notable, and sometimes controversial, computer • A one dimensional model might simulate the effects of water hammer in a pipe. simulations used in science include: • A two-dimensional model might be used to simulate the drag – Donella Meadows’ World3 used in forces on the cross-section of an aeroplane wing. – ’s • A three-dimensional simulation might estimate the heating and cooling requirements of a large building. – Thomas Ray’s Tierra.

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Simulation environments for physics and engineering Pitfalls in computer simulation

• Graphical environments to design simulations • It is very important to perform have been developed. to ensure that the accuracy of the results is • Special care was taken to handle “events” properly understood. – situations in which the simulation equations are not – For example, the probabilistic risk analysis of factors valid and have to be changed. determining the success of an oilfield exploration program involves combining samples from a variety of • The open project Open Source Physics was started statistical distributions using the Monte Carlo method. in order to develop reusable libraries for • If, for instance, one of the key parameters (i.e. the net ratio of simulations in Java, together with Easy Java oil-bearing strata) is known to only one significant figure, Simulations, then the result of the simulation might not be more precise than one significant figure, – a complete graphical environment that generates code – although it might (misleadingly) be presented as having four based on these libraries. significant figures.

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Computer simulation in practical contexts Computer simulation in practical contexts

• Computer simulations are used in a wide – behaviour of structures (such as buildings and variety of practical contexts, such as: industrial parts) under stress and other conditions – analysis of air pollutant dispersion using – design of industrial processes, such as chemical atmospheric dispersion modelling processing plants – design of complex systems such as aircraft and – and organizational studies systems – reservoir simulation for the petroleum engineering – design of noise barriers to effect roadway noise to model the subsurface reservoir mitigation – Process Engineering Simulation tools – flight simulators to train pilots – robot simulators for the design of robots and robot – weather forecasting control algorithms

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6 Computer simulation in practical contexts Computer simulation in practical contexts

• The reliability and the trust people put in • Although this might seem obvious, this is a computer simulations depends on the validity special point of attention in stochastic of the simulation model, simulations, – therefore verification and validation are of crucial – where random numbers should actually be semi- importance in the development of computer random numbers. simulations. • An exception to reproducibility are “human-in- • Another important aspect of computer the-loop” simulations, simulations is that of reproducibility of the – such as flight simulations and computer games. results, • Here a human is part of the simulation and thus – meaning that a simulation model should not influences the outcome in a way that is hard if not provide a different answer for each execution. impossible to reproduce exactly.

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Computer simulation in practical contexts Computer simulation in practical contexts

• Computer graphics can be used to display the results of • In debugging, simulating a program execution a computer simulation. under test (rather than executing natively) can • Animations can be used to experience a simulation in detect far more errors than the hardware itself real-time e.g. in training simulations. can detect and, • In some cases animations may also be useful in faster than real-time or even slower than real-time modes. – at the same time, log useful debugging information such as instruction trace, memory alterations and – For example, faster than real-time animations can be useful in visualizing the build-up of queues in the simulation of instruction counts. humans evacuating a building. • This technique can also detect buffer overflow • Furthermore, simulation results are often aggregated and similar “hard to detect” errors as well as into static images using various ways of scientific produce performance information and tuning visualization. data.

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Grammar revision Grammar revision

• Verbs+object+infinitive; Verbs+object+to-infinitive • For example: – New developments in computing are often designed to – {A GUI lets you point to icons and click a mouse make something easier. button to execute a task.} – The following verbs are often used to describe such – {A GUI allows you to use a computer without developments: knowing any operating system commands.} • allow – {The X Window System enables Unix-based • let computers to have a graphical look and feel.} • enable • permit – {Voice recognition software helps disabled users • help (to) access computers.}

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7 Grammar revision

• Allow, enable and permit are used with the following structure: – verb + object + to-infinitive • Let is used with the following structure: – verb + object + infinitive • Help can be used with either structure.

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