Simulation

Simulation is the imitation of some real thing, state of affairs, or process. The act of simulating something generally entails representing certain key characteristics or behaviours of a selected physical or abstract system.

Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning.^[1] Other contexts include simulation of technology for performance optimization, safety engineering, testing, training and education. Simulation can be used to show the eventual real effects of alternative conditions and courses of action. Simulation is also used when the real system cannot be engaged. The real system may not be engaged because it may not be accessible, it may be dangerous or unacceptable to engage, or it may simply not exist ^[2].

Key issues in simulation include acquisition of valid source information about the relevant selection of key characteristics and behaviours, the use of simplifying approximations and assumptions within the simulation, and fidelity and validity of the simulation outcomes.

Contents 1 Classification and terminology 2 Computer simulation 2.1 Computer science 3 Simulation in education and training 4 Clinical healthcare simulators 4.1 Improving Patient Safety through New Innovations 4.2 History of simulation in healthcare 4.3 Type of models 5 Simulation in entertainment 5.1 History 5.1.1 Early History (1940’s and 50’s) 5.1.2 Modern Simulation (1980’s-present) 5.2 Examples of entertainment simulation 5.2.1 Computer and video games 5.2.2 Film 5.2.3 Theme park rides 6 Simulation and Manufacturing 7 More examples in different areas 7.1 City and urban simulation 7.2 Classroom of the future 7.3 Digital Lifecycle Simulation 7.4 Disaster Preparedness and Simulation Training 7.5 Engineering, technology or process simulation 7.6 Space Shuttle Countdown Simulation 7.7 Satellite Navigation Simulators 7.8 Communication Satellite Simulation 7.9 Finance simulation 7.10 Flight simulation 7.11 Automobile simulator 7.12 Marine simulators 7.13 Military simulations 7.14 Robotics simulators 7.15 Biomechanics simulators 7.16 Sales process simulators 8 Simulation and games 9 Historical usage 10 See also 11 References 12 Further reading 13 External links

Classification and terminology

Historically, simulations used in different fields developed largely independently, but 20th century studies of Systems theory and Cybernetics combined with spreading use of computers across all those fields have led to some unification and a more systematic view of the concept.

Physical simulation refers to simulation in which physical objects are substituted for the real thing (some circles^[3] use the term for computer simulations modelling selected laws of physics, but this article doesn't). These physical objects are often chosen because they are smaller or cheaper than the actual object or system.

Interactive simulation is a special kind of physical simulation, often referred to as a human in the loop simulation, in which physical simulations include human operators, such as in a flight simulator or a driving simulator.

Human in the loop simulations can include a computer simulation as a so-called synthetic environment.^[4]

Computer simulation

A computer simulation (or "sim") is an attempt to model a real-life or hypothetical situation on a computer so that it can be studied to see how the system works. By changing variables, predictions may be made about the behaviour of the system.^[1]

Computer simulation has become a useful part of modeling many natural systems in physics, chemistry and biology^[5], and human systems in economics and social science (the computational sociology) as well as in engineering to gain insight into the operation of those systems. A good example of the usefulness of using computers to simulate can be found in the field of network traffic simulation. In such simulations, the model behaviour will change each simulation according to the set of initial parameters assumed for the environment.

Traditionally, the formal modeling of systems has been via a mathematical model, which attempts to find analytical solutions enabling the prediction of the behaviour of the system from a set of parameters and initial conditions. Computer simulation is often used as an adjunct to, or substitution for, modeling systems for which simple closed form analytic solutions are not possible. There are many different types of computer simulation, the common feature they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states would be prohibitive or impossible.

Several software packages exist for running computer-based simulation modeling (e.g. Monte Carlo simulation, stochastic modeling, multimethod modeling) that makes the modeling almost effortless.

Modern usage of the term "computer simulation" may encompass virtually any computer-based representation.

Computer science

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 (in modern terminology, a computer runs a program) that describes the state transitions, inputs and outputs of a subject discrete-state machine. The computer simulates the subject machine. Accordingly, in theoretical computer science the term simulation is a relation between state transition systems, useful in the study of operational semantics.

Less theoretically, an interesting application of computer simulation is to simulate computers using computers. In computer architecture, a type of simulator, typically called an emulator, is often used to execute a program that has to run on some inconvenient type of computer (for example, a newly designed computer that has not yet been built or an obsolete computer that is no longer available), or in a tightly controlled testing environment (see Computer architecture simulator and Platform virtualization). For example, simulators have been used to debug a microprogram or sometimes commercial application programs, before the program is downloaded to the target machine. Since the operation of the computer is simulated, all of the information about the computer's operation is directly available to the programmer, and the speed and execution of the simulation can be varied at will.

Simulators may also be used to interpret fault trees, or test VLSI logic designs before they are constructed. Symbolic simulation uses variables to stand for unknown values.

In the field of optimization, simulations of physical processes are often used in conjunction with evolutionary computation to optimize control strategies.

Simulation in education and training

Simulation is often used in the training of civilian and military personnel.^[6] This usually occurs when it is prohibitively expensive or simply too dangerous to allow trainees to use the real equipment in the real world. In such situations they will spend time learning valuable lessons in a "safe" virtual environment. Often the convenience is to permit mistakes during training for a safety-critical system. For example, in simSchool teachers practice classroom management and teaching techniques on simulated students, which avoids "learning on the job" that can damage real students. There is a distinction, though, between simulations used for training and Instructional simulation.

Training simulations typically come in one of three categories:^[7]

• "live" simulation (where real people use simulated (or "dummy") equipment in the real world);
• "virtual" simulation (where real people use simulated equipment in a simulated world, or virtual environment^[4]), or
• "constructive" simulation (where simulated people use simulated equipment in a simulated environment). Constructive simulation is often referred to as "wargaming" since it bears some resemblance to table-top war games in which players command armies of soldiers and equipment that move around a board.

In standardized tests, "live" simulations are sometimes called "high-fidelity", producing "samples of likely performance", as opposed to "low-fidelity", "pencil-and-paper" simulations producing only "signs of possible performance"^[8], but the distinction between high, moderate and low fidelity remains relative, depending on the context of a particular comparison.

Simulations in education are somewhat like training simulations. They focus on specific tasks. The term 'microworld' is used to refer to educational simulations which model some abstract concept rather than simulating a realistic object or environment, or in some cases model a real world environment in a simplistic way so as to help a learner develop an understanding of the key concepts. Normally, a user can create some sort of construction within the microworld that will behave in a way consistent with the concepts being modeled. Seymour Papert was one of the first to advocate the value of microworlds, and the Logo (programming language) programming environment developed by Papert is one of the most famous microworlds. As another example, the Global Challenge Award online STEM learning web site uses microworld simulations to teach science concepts related to global warming and the future of energy. Other projects for simulations in educations are Open Source Physics and its EJS environment.

Management games (or business simulations) have been finding favour in business education in recent years.^[9] Business simulations that incorporate a dynamic model enable experimentation with business strategies in a risk free environment and provide a useful extension to case study discussions.

Social simulations may be used in social science classrooms to illustrate social and political processes in anthropology, economics, history, political science, or sociology courses, typically at the high school or university level. These may, for example, take the form of civics simulations, in which participants assume roles in a simulated society, or international relations simulations in which participants engage in negotiations, alliance formation, trade, diplomacy, and the use of force. Such simulations might be based on fictitious political systems, or be based on current or historical events. An example of the latter would be Barnard College's "Reacting to the Past" series of educational simulations.^[10] The "Reacting to the Past" series also includes simulation games that address science education.

In recent years, there has been increasing use of social simulations for staff training in aid and development agencies. The Carana simulation, for example, was first developed by the United Nations Development Programme, and is now used in a very revised form by the World Bank for training staff to deal with fragile and conflict-affected countries.^[11]

Clinical healthcare simulators

Medical simulators are increasingly being developed and deployed to teach therapeutic and diagnostic procedures as well as medical concepts and decision making to personnel in the health professions. Simulators have been developed for training procedures ranging from the basics such as blood draw, to laparoscopic surgery ^[12] and trauma care. They are also important to help on prototyping new devices for biomedical engineering problems. Currently, simulators are applied to research and development of tools for new therapies, treatments and early diagnosis in medicine.

Many medical simulators involve a computer connected to a plastic simulation of the relevant anatomy. Sophisticated simulators of this type employ a life size mannequin that responds to injected drugs and can be programmed to create simulations of life-threatening emergencies. In other simulations, visual components of the procedure are reproduced by computer graphics techniques, while touch-based components are reproduced by haptic feedback devices combined with physical simulation routines computed in response to the user's actions. Medical simulations of this sort will often use 3D CT or MRI scans of patient data to enhance realism. Some medical simulations are developed to be widely distributed (such as web-enabled simulations that can be viewed via standard web browsers) and can be interacted with using standard computer interfaces, such as the keyboard and mouse.

Another important medical application of a simulator — although, perhaps, denoting a slightly different meaning of simulator — is the use of a placebo drug, a formulation that simulates the active drug in trials of drug efficacy (see Placebo (origins of technical term)).

Improving Patient Safety through New Innovations

Patient safety is a concern in the medical industry. Patients have been known to suffer injuries and even death due to management error, and lack of using best standards of care and training. According to Building a National Agenda for Simulation-Based Medical Education (Eder-Van Hook, Jackie, 2004) , “A health care provider’s ability to react prudently in an unexpected situation is one of the most critical factors in creating a positive outcome in medical emergency, regardless of whether it occurs on the battlefield, freeway, or hospital emergency room.” simulation. Eder-Van Hook (2004) also noted that medical errors kill up to 98,000 with an estimated cost between $37 and $50 million and $17 to $29 billion for preventable adverse events dollars per year. “Deaths due to preventable adverse events exceed deaths attributable to motor vehicle accidents, breast cancer, or AIDS” Eder-Van Hook (2004). With these types of statistics it is no wonder that improving patient safety is a prevalent concern in the industry.

New innovative simulation training solutions are now being used to train medical professionals in an attempt to reduce the number of safety concerns that have adverse effects on the patients. However, according to the article Does Simulation Improve Patient Safety? Self-efficacy, Competence, Operational Performance, and Patient Safety (Nishisaki A., Keren R., and Nadkarni, V., 2007), the jury is still out. Nishisaki states that “There is good evidence that simulation training improves provider and team self-efficacy and competence on manikins. There is also good evidence that procedural simulation improves actual operational performance in clinical settings. However, no evidence yet shows that crew resource management training through simulation, despite its promise, improves team operational performance at the bedside. Also, no evidence to date proves that simulation training actually improves patient outcome. Even so, confidence is growing in the validity of medical simulation as the training tool of the future.” This could be because there are not enough research studies yet conducted to effectively determine the success of simulation initiatives to improve patient safety. Examples of [recently implemented] research simulations used to improve patient care [and its funding] can be found at Improving Patient Safety through Simulation Research (US Department of Human Health Services) http://www.ahrq.gov/qual/simulproj.htm.

One such attempt to improve patient safety through the use of simulations training is pediatric care to deliver just-in-time service or/and just-in-place. This training consists of 20 minutes of simulated training just before workers report to shift. It is hoped that the recentness of the training will increase the positive and reduce the negative results that have generally been associated with the procedure. The purpose of this study is to determine if just-in-time training improves patient safety and operational performance of orotracheal intubation and decrease occurrences of undesired associated events and “to test the hypothesis that high fidelity simulation may enhance the training efficacy and patient safety in simulation settings.” The conclusion as reported in Abstract P38: Just-In-Time Simulation Training Improves ICU Physician Trainee Airway Resuscitation Participation without Compromising Procedural Success or Safety (Nishisaki A., 2008), were that simulation training improved resident participation in real cases; but did not sacrifice the quality of service. It could be therefore hypothesized that by increasing the number of highly trained residents through the use of simulation training, that the simulation training does in fact increase patient safety. This hypothesis would have to be researched for validation and the results may or may not generalize to other situations.

History of simulation in healthcare

The first medical simulators were simple models of human patients.^[13]

Since antiquity, these representations in clay and stone were used to demonstrate clinical features of disease states and their effects on humans. Models have been found from many cultures and continents. These models have been used in some cultures (e.g., Chinese culture) as a "diagnostic" instrument, allowing women to consult male physicians while maintaining social laws of modesty. Models are used today to help students learn the anatomy of the musculoskeletal system and organ systems.^[13]

Type of models

Active models

Active models that attempt to reproduce living anatomy or physiology are recent developments. The famous “Harvey” mannikin was developed at the University of Miami and is able to recreate many of the physical findings of the cardiology examination, including palpation, auscultation, and electrocardiography.

Interactive models

More recently, interactive models have been developed that respond to actions taken by a student or physician. Until recently, these simulations were two dimensional computer programs that acted more like a textbook than a patient. Computer simulations have the advantage of allowing a student to make judgements, and also to make errors. The process of iterative learning through assessment, evaluation, decision making, and error correction creates a much stronger learning environment than passive instruction.

Computer simulators

Simulators have been proposed as an ideal tool for assessment of students for clinical skills.^[14]

Programmed patients and simulated clinical situations, including mock disaster drills, have been used extensively for education and evaluation. These “lifelike” simulations are expensive, and lack reproducibility. A fully functional "3Di" simulator would be the most specific tool available for teaching and measurement of clinical skills.

Immersive disease state simulations allow a doctor or HCP to experience what a disease actually feels like. Using sensors and transducers symptomatic effects can be delivered to a participant allowing them to experience the patients disease state.

Such a simulator meets the goals of an objective and standardized examination for clinical competence.^[15] This system is superior to examinations that use "standard patients" because it permits the quantitative measurement of competence, as well as reproducing the same objective findings.^[16]

Simulation in entertainment

Entertainment simulation is a term that encompasses many large and popular industries such as film, television, video games (including serious games) and rides in theme parks. Although modern simulation is thought to have its roots in training and the military, in the 20th century it also became a conduit for enterprises which were more hedonistic in nature. Advances in technology in the 1980’s and 1990’s caused simulation to become more widely used and it began to appear in movies such as Jurassic Park (1993) and in computer-based games such as Atari’s Battlezone.

History

Early History (1940’s and 50’s)

The first simulation game may have been created as early as 1947 by Thomas T. Goldsmith Jr. and Estle Ray Mann. This was a straightforward game that simulated a missile being fired at a target. The curve of the missile and its speed could be adjusted using several knobs. In 1958 a computer game called “Tennis for Two” was created by Willy Higginbotham which simulated a tennis game between two players who could both play at the same time using hand controls and was displayed on an oscilloscope ^[17]. This was one of the first electronic video games to use a graphical display.

Modern Simulation (1980’s-present)

Advances in technology in the 1980’s made the computer more affordable and more capable than they were in previous decades ^[18] which facilitated the rise of computer gaming. The first video game consoles released in the 1970’s and early 80’s fell prey to the industry crash in 1983, but in 1985 Nintendo released the Nintendo Entertainment System (NES) which became the best selling console in video game history ^[19]. In the 1990’s computer games became widely popular with the release of such game as The Sims and Command and Conquer and the still increasing power of desktop computers. Today, computer simulation games such as World of Warcraft are played by millions of people around the world.
Computer-generated imagery was used in film to simulate objects as early as 1976, though in 1982 the movie Tron was the first film to use computer-generated imagery for more than a couple of minutes. However, the commercial failure of the movie may have caused the industry to step away from the technology ^[20]. In 1993, the movie Jurassic Park became the first popular film to use computer-generated graphics extensively, integrating the simulated dinosaurs almost seamlessly into live action scenes. This event transformed the film industry; in 1995 the movie Toy Story was the first film to use only computer-generated images and by the new millennium computer generated graphics were the leading choice for special effects in movies ^[21].
Simulators have been used for entertainment since the Link Trainer in the 1930’s ^[22]. The first modern simulator ride to open at a theme park was Disney’s Star Tours in 1987 soon followed by Universal’s The Funtastic World of Hanna-Barbera in 1990 which was the first ride to be done entirely with computer graphics ^[23].

Examples of entertainment simulation

Computer and video games

Simulation games, as opposed to other genres of video and computer games, represent or simulate an environment accurately. Moreover, they represent the interactions between the playable characters and the environment realistically. These kinds of games are usually more complex in terms of game play.^[24] Simulation games have become incredibly popular among people of all ages and the industry has proven to be one of the few resistant to recession conditions ^[25]. Popular simulation games include SimCity, Tiger Woods PGA Tour and Virtonomics.

Film

Computer-generated imagery is “the application of the field of 3D computer graphics to special effects”. This technology is used for visual effects because they are high in quality, controllable, and can create effects that would not be feasible using any other technology either because of cost, resources or safety ^[26]. Computer-generated graphics can be seen in many live action movies today, especially those of the action genre. Further, computer generated imagery has almost completely supplanted hand-drawn animation in children's movies which are increasingly computer-generated only. Examples of movies that use computer-generated imagery include Finding Nemo, 300 and Iron Man.

Theme park rides

Simulator rides are the progeny of military training simulators and commercial simulators, but they are different in a fundamental way. While military training simulators react realistically to the input of the trainee in real time, ride simulators only feel like they move realistically and move according to prerecorded motion scripts.^[23] One of the first simulator rides, Star Tours, which cost $32 million, used a hydraulic motion based cabin. The movement was programmed by a joystick. Today’s simulator rides, such as The Amazing Adventures of Spider-man include elements to increase the amount of immersion experienced by the riders such as: 3D imagery, physical effects (spraying water or producing scents), and movement through an environment.^[27] Examples of simulation rides include Mission Space and The Simpsons Ride.

Simulation and Manufacturing

Manufacturing represents one of the most important applications of Simulation. This technique represents a valuable tool used by engineers when evaluating the effect of capital investment in equipments and physical facilities like factory plants, warehouses, and distribution centers.Simulation can be used to predict the performance of an existing or planned system and to compare alternative solutions for a particular design problem.^[28]

Another important goal of manufacturing-simulations is to quantify system performance.Common measures of system performance include the following:^[29]

• Throughput under average and peak loads;
• System cycle time (how long it take to produce one part);
• Utilization of resource, labor, and machines;
• Bottlenecks and choke points;
• Queuing at work locations;
• Queuing and delays caused by material-handling devices and systems;
• WIP storage needs;
• Staffing requirements;
• Effectiveness of scheduling systems;
• Effectiveness of control systems.

More examples in different areas

City and urban simulation

A city simulator can be a city-building game but can also be a tool used by urban planners to understand how cities are likely to evolve in response to various policy decisions. AnyLogic is an example of modern, large-scale urban simulators designed for use by urban planners. City simulators are generally agent-based simulations with explicit representations for land use and transportation. UrbanSim is an example of a large-scale urban simulation model system being used widely by metropolitan planning agencies for land use and transportation planning.

Classroom of the future

The "classroom of the future" will probably contain several kinds of simulators, in addition to textual and visual learning tools. This will allow students to enter the clinical years better prepared, and with a higher skill level. The advanced student or postgraduate will have a more concise and comprehensive method of retraining — or of incorporating new clinical procedures into their skill set — and regulatory bodies and medical institutions will find it easier to assess the proficiency and competency of individuals.

The classroom of the future will also form the basis of a clinical skills unit for continuing education of medical personnel; and in the same way that the use of periodic flight training assists airline pilots, this technology will assist practitioners throughout their career.

The simulator will be more than a "living" textbook, it will become an integral a part of the practice of medicine. The simulator environment will also provide a standard platform for curriculum development in institutions of medical education.

Digital Lifecycle Simulation

Simulation solutions are being increasingly integrated with CAx (CAD, CAM, CAE....) solutions and processes. The use of simulation throughout the product lifecycle, especially at the earlier concept and design stages, has the potential of providing substantial benefits. These benefits range from direct cost issues such as reduced prototyping and shorter time-to-market, to better performing products and higher margins. However, for some companies, simulation has not provided the expected benefits.

The research firm Aberdeen Group has found that nearly all best-in-class manufacturers use simulation early in the design process as compared to 3 or 4 laggards who do not.

The successful use of Simulation, early in the lifecycle, has been largely driven by increased integration of simulation tools with the entire CAD, CAM and PLM solution-set. Simulation solutions can now function across the extended enterprise in a multi-CAD environment, and include solutions for managing simulation data and processes and ensuring that simulation results are made part of the product lifecycle history. The ability to use simulation across the entire lifecycle has been enhanced through improved user interfaces such as tailorable user interfaces and "wizards" which allow all appropriate PLM participants to take part in the simulation process.

Disaster Preparedness and Simulation Training

Simulation training has become a method for preparing people for disasters. Simulations can replicate emergency situations and track how learners respond. Disaster preparedness simulations can involve training on how to handle terrorism attacks, natural disasters, pandemic outbreaks, or other life-threatening emergencies.

One organization that has used simulation training for disaster preparedness is CADE (Center for Advancement of Distance Education). CADE^[30] has used a video game to prepare emergency workers for multiple types of attacks. As reported by News-Medical.Net, ”The video game is the first in a series of simulations to address bioterrorism, pandemic flu, smallpox and other disasters that emergency personnel must prepare for.^[31]” Developed by a team from the University of Illinois at Chicago (UIC), the game allows learners to practice their emergency skills in a safe, controlled environment.

The Emergency Simulation Program (ESP) at the British Columbia Institute of Technology (BCIT), Vancouver, British Columbia, Canada is another example of an organization that uses simulation to train for emergency situations. ESP uses simulation to train on the following situations: forest fire fighting, oil or chemical spill response, earthquake response, law enforcement, municipal fire fighting, hazardous material handling, military training, and response to terrorist attack ^[32] One feature of the simulation system is the implementation of “Dynamic Run-Time Clock,” which allows simulations to run a 'simulated' time frame, 'speeding up' or 'slowing down' time as desired”^[32] Additionally, the system allows session recordings, picture-icon based navigation, file storage of individual simulations, multimedia components, and launch external applications.

At the University of Québec in Chicoutimi, a research team at the outdoor research and expertise laboratory (Laboratoire d'Expertise et de Recherche en Plein Air - LERPA) specializes in using wilderness backcountry accident simulations to verify emergency response coordination.

Instructionally, the benefits of emergency training through simulations are that learner performance can be tracked through the system. This allows the developer to make adjustments as necessary or alert the educator on topics that may require additional attention. Other advantages are that the learner can be guided or trained on how to respond appropriately before continuing to the next emergency segment—this is an aspect that may not be available in the live-environment. Some emergency training simulators also allows for immediate feedback, while other simulations may provide a summary and instruct the learner to engage in the learning topic again.

In a live-emergency situation, emergency responders do not have time to waste. Simulation-training in this environment provides an opportunity for learners to gather as much information as they can and practice their knowledge in a safe environment. They can make mistakes without risk of endangering lives and be given the opportunity to correct their errors to prepare for the real-life emergency.

Engineering, technology or process simulation

Simulation is an important feature in engineering systems or any system that involves many processes. For example in electrical engineering, delay lines may be used to simulate propagation delay and phase shift caused by an actual transmission line. Similarly, dummy loads may be used to simulate impedance without simulating propagation, and is used in situations where propagation is unwanted. A simulator may imitate only a few of the operations and functions of the unit it simulates. Contrast with: emulate.^[33]

Most engineering simulations entail mathematical modeling and computer assisted investigation. There are many cases, however, where mathematical modeling is not reliable. Simulation of fluid dynamics problems often require both mathematical and physical simulations. In these cases the physical models require dynamic similitude. Physical and chemical simulations have also direct realistic uses, rather than research uses; in chemical engineering, for example, process simulations are used to give the process parameters immediately used for operating chemical plants, such as oil refineries.

Space Shuttle Countdown Simulation

Simulation is used at Kennedy Space Center (KSC) to train and certify Space Shuttle engineers during simulated launch countdown operations. The Space Shuttle engineering community participates in a launch countdown integrated simulation before each shuttle flight. This simulation is a virtual simulation where real people interact with simulated Space Shuttle vehicle and Ground Support Equipment (GSE) hardware. The Shuttle Final Countdown Phase Simulation, also known as S0044, involves countdown processes that integrate many of the Space Shuttle vehicle and GSE systems. Some of the Shuttle systems integrated in the simulation are the Main Propulsion System, Main Engines, Solid Rocket Boosters, ground Liquid Hydrogen and Liquid Oxygen, External Tank, Flight Controls, Navigation, and Avionics ^[34]. The high-level objectives of the Shuttle Final Countdown Phase Simulation are:

• To demonstrate Firing Room final countdown phase operations.
• To provide training for system engineers in recognizing, reporting and evaluating system problems in a time critical environment.
• To exercise the launch teams ability to evaluate, prioritize and respond to problems in an integrated manner within a time critical environment.
• To provide procedures to be used in performing failure/recovery testing of the operations performed in the final countdown phase ^[35].

The Shuttle Final Countdown Phase Simulation takes place at the Kennedy Space Center Launch Control Center Firing Rooms. The firing room used during the simulation is the same control room where real launch countdown operations are executed. As a result, equipment used for real launch countdown operations is engaged. Command and control computers, application software, engineering plotting and trending tools, launch countdown procedure documents, launch commit criteria documents, hardware requirement documents, and any other items used by the engineering launch countdown teams during real launch countdown operations are used during the simulation. The Space Shuttle vehicle hardware and related GSE hardware is simulated by mathematical models (written in Shuttle Ground Operations Simulator (SGOS) modeling language ^[36]) that behave and react like real hardware. During the Shuttle Final Countdown Phase Simulation, engineers command and control hardware via real application software executing in the control consoles – just as if they were commanding real vehicle hardware. However, these real software applications do not interface with real Shuttle hardware during simulations. Instead, the applications interface with mathematical model representations of the vehicle and GSE hardware. Consequently, the simulations bypass sensitive and even dangerous mechanisms while providing engineering measurements detailing how the hardware would have reacted. Since these math models interact with the command and control application software, models and simulations are also used to debug and verify the functionality of application software ^[37].

Satellite Navigation Simulators

The only true way to test GNSS receivers (commonly known as Sat-Nav's in the commercial world)is by using an RF Constellation Simulator. A receiver that may for example be used on an aircraft, can be tested under dynamic conditions without the need to take it on a real flight. The test conditions can be repeated exactly, and there is full control over all the test parameters. this is not possible in the 'real-world' using the actual signals. For testing receivers that will use the new Galileo (satellite navigation) there is no alternative, as the real signals do not yet exist.

Communication Satellite Simulation

Modern satellite communications systems (SatCom) are often large and complex with many interacting parts and elements. In addition, the need for broadband connectivity on a moving vehicle has increased dramatically in the past few years for both commercial and military applications. To accurately predict and deliver high quality of service, satcom system designers have to factor in terrain as well as atmospheric and meteorological conditions in their planning. To deal with such complexity, system designers and operators increasingly turn towards computer models of their systems to simulate real world operational conditions and gain insights in to usability and requirements prior to final product sign-off. Modeling improves the understanding of the system by enabling the SatCom system designer or planner to simulate real world performance by injecting the models with multiple hypothetical atmospheric and environmental conditions.

Finance simulation

In finance, computer simulations are often used for scenario planning. Risk-adjusted net present value, for example, is computed from well-defined but not always known (or fixed) inputs. By imitating the performance of the project under evaluation, simulation can provide a distribution of NPV over a range of discount rates and other variables.

Flight simulation

Flight Simulation Training Devices (FSTD) are used to train pilots on the ground. In comparison to training in an actual aircraft, simulation based training allows for the training of maneuvers or situations that may be impractical (or even dangerous) to perform in the aircraft, while keeping the pilot and instructor in a relatively low-risk environment on the ground. For example, electrical system failures, instrument failures, hydraulic system failures, and even flight control failures can be simulated without risk to the pilots or an aircraft.

Instructors can also provide students with a higher concentration of training tasks in a given period of time than is usually possible in the aircraft. For example, conducting multiple instrument approaches in the actual aircraft may require significant time spent repositioning the aircraft, while in a simulation, as soon as one approach has been completed, the instructor can immediately preposition the simulated aircraft to an ideal (or less than ideal) location from which to begin the next approach.

Flight simulation also provides an economic advantage over training in an actual aircraft. Once fuel, maintenance, and insurance costs are taken into account, the operating costs of an FSTD are usually substantially lower than the operating costs of the simulated aircraft. For some large transport category airplanes, the operating costs may be several times lower for the FSTD than the actual aircraft.

Some people who use simulator software, especially flight simulator software, build their own simulator at home. Some people — in order to further the realism of their homemade simulator — buy used cards and racks that run the same software used by the original machine. While this involves solving the problem of matching hardware and software — and the problem that hundreds of cards plug into many different racks — many still find that solving these problems is well worthwhile. Some are so serious about realistic simulation that they will buy real aircraft parts, like complete nose sections of written-off aircraft, at aircraft boneyards. This permits people to simulate a hobby that they are unable to pursue in real life.

Automobile simulator

An automobile simulator provides an opportunity to reproduce the characteristics of real vehicles in a virtual environment. It replicates the external factors and conditions with which a vehicle interacts enabling a driver to feel as if they are sitting in the cab of their own vehicle. Scenarios and events are replicated with sufficient reality to ensure that drivers become fully immersed in the experience rather than simply viewing it as an educational experience.

The simulator provides a constructive experience for the novice driver and enables more complex exercises to be undertaken by the more mature driver. For novice drivers, truck simulators provide an opportunity to begin their career by applying best practice. For mature drivers, simulation provides the ability to enhance good driving or to detect poor practice and to suggest the necessary steps for remedial action. For companies, it provides an opportunity to educate staff in the driving skills that achieve reduced maintenance costs, improved productivity and, most importantly, to ensure the safety of their actions in all possible situations.

Marine simulators

Bearing resemblance to flight simulators, marine simulators train ships' personnel. The most common marine simulators include:

• Ship's bridge simulators
• Engine room simulators
• Cargo handling simulators
• Communication / GMDSS simulators
• ROV simulators

Simulators like these are mostly used within maritime colleges, training institutions and navies. They often consist of a replication of a ships' bridge, with operating desk(s), and a number of screens on which the virtual surroundings are projected.

Military simulations

Military simulations, also known informally as war games, are models in which theories of warfare can be tested and refined without the need for actual hostilities. They exist in many different forms, with varying degrees of realism. In recent times, their scope has widened to include not only military but also political and social factors (for example, the NationLab series of strategic exercises in Latin America.^[38] Whilst many governments make use of simulation, both individually and collaboratively, little is known about the model's specifics outside professional circles.

Robotics simulators

A robotics simulator is used to create embedded applications for a specific (or not) robot without being dependent on the 'real' robot. In some cases, these applications can be transferred to the real robot (or rebuilt) without modifications. Robotics simulators allow reproducing situations that cannot be 'created' in the real world because of cost, time, or the 'uniqueness' of a resource. A simulator also allows fast robot prototyping. Many robot simulators feature physics engines to simulate a robot's dynamics.

Biomechanics simulators

A biomechanics simulator is used to analyze walking dynamics, study sports performance, simulate surgical procedures, analyze joint loads, design medical devices, and animate human and animal movement.

Sales process simulators

Simulations are useful in modeling the flow of transactions through business processes, such as in the field of sales process engineering, to study and improve the flow of customer orders through various stages of completion (say, from an initial proposal for providing goods/services through order acceptance and installation). Such simulations can help predict the impact of how improvements in methods might impact variability, cost, labor time, and the quantity of transactions at various stages in the process. A full-featured computerized process simulator can be used to depict such models, as can simpler educational demonstrations using spreadsheet software, pennies being transferred between cups based on the roll of a die, or dipping into a tub of colored beads with a scoop^[39].

Simulation and games

Strategy games — both traditional and modern — may be viewed as simulations of abstracted decision-making for the purpose of training military and political leaders (see History of Go for an example of such a tradition, or Kriegsspiel for a more recent example).

Many other video games are simulators of some kind. Such games can simulate various aspects of reality, from business, to government, to construction, to piloting vehicles (see above).

Historical usage

Historically, the word had negative connotations:

…for Distinction Sake, a Deceiving by Words, is commonly called a Lye, and a Deceiving by Actions, Gestures, or Behavior, is called Simulation…

—Robert South, South, 1697, p.525

However, the connection between simulation and dissembling later faded out and is now only of linguistic interest.^[40]

See also

References

Further reading

• C. Aldrich (2003). Learning by Doing : A Comprehensive Guide to Simulations, Computer Games, and Pedagogy in e-Learning and Other Educational Experiences. San Francisco: Pfeifer — John Wiley & Sons.
• C. Aldrich (2004). Simulations and the future of learning: an innovative (and perhaps revolutionary) approach to e-learning. San Francisco: Pfeifer — John Wiley & Sons.
• Steve Cohen (2006). Virtual Decisions. Mahwah, New Jersey: Lawrence Erlbaum Associates.
• R. Frigg and S. Hartmann (2007). Models in Science. Entry in the Stanford Encyclopedia of Philosophy.
• S. Hartmann (1996). The World as a Process: Simulations in the Natural and Social Sciences, in: R. Hegselmann et al. (eds.), Modelling and Simulation in the Social Sciences from the Philosophy of Science Point of View, Theory and Decision Library. Dordrecht: Kluwer 1996, 77–100.
• J.P. Hertel (2002). Using Simulations to Promote Learning in Higher Education. Sterling, Virginia: Stylus.
• P. Humphreys, Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford: Oxford University Press, 2004.
• F. Percival, S. Lodge & D. Saunders (1993). The Simulation and Gaming Yearbook: Developing Transferable Skills in Education and Training. London: Kogan Page.
• D. Saunders (Ed.). (2000). The International Simulation and Gaming Research Yearbook, volume 8. London: Kogan Page Limited.
• Roger D. Smith: Simulation Article, Encyclopedia of Computer Science, Nature Publishing Group, ISBN 0-333-77879-0.
• Roger D. Smith: "Simulation: The Engine Behind the Virtual World", eMatter, December, 1999.
• R. South (1688). "A Sermon Delivered at Christ-Church, Oxon., Before the University, Octob. 14. 1688: Prov. XII.22 Lying Lips are abomination to the Lord", pp. 519–657 in South, R., Twelve Sermons Preached Upon Several Occasions (Second Edition), Volume I, Printed by S.D. for Thomas Bennet, (London), 1697.
• Eric Winsberg (1999) Sanctioning Models: The epistemology of simulation, in Sismondo, Sergio and Snait Gissis (eds.) (1999), Modeling and Simulation. Special Issue of Science in Context 12.
• Eric Winsberg (2001), “Simulations, Models and Theories: Complex Physical Systems and their Representations”, Philosophy of Science 68 (Proceedings): 442-454.
• Eric Winsberg (2003), Simulated Experiments: Methodology for a Virtual World, Philosophy of Science 70: 105–125.
• Joseph Wolfe & David Crookall (1998). Developing a scientific knowledge of simulation/gaming . Simulation & Gaming: An International Journal of Theory, Design and Research, 29(1), 7–19.
• Ellen K. Levy (2004) Synthetic Lighting: Complex Simulations of Nature, Photography Quarterly (#88) pp. 5–9

External links

• Bibliographies containing more references to be found on the website of the journal Simulation & Gaming.