Product Code Database
A simulation is an imitative representation of a process or system that could exist in the real world. (2025). 9780130887023, Prentice Hall. ISBN 9780130887023 In this broad sense, simulation can often be used interchangeably with model. Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Another way to distinguish between the terms is to define simulation as with the help of a model. (2015). 9781467397438 ISBN 9781467397438 This definition includes time-independent simulations. Often, computers are used to execute the simulation.
Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games. Simulation is also used with scientific modelling of natural systems or human systems to gain insight into their functioning,In the words of the Simulation article in Encyclopedia of Computer Science, "designing a model of a real or imagined system and conducting experiments with that model". as in economics. 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, because it may not be accessible, or it may be dangerous or unacceptable to engage, or it is being designed but not yet built, or it may simply not exist.
Key issues in modeling and simulation include the acquisition of valid sources of information about the relevant selection of key characteristics and behaviors used to build the model, the use of simplifying approximations and assumptions within the model, and fidelity and validity of the simulation outcomes. Procedures and protocols for model verification and validation are an ongoing field of academic study, refinement, research and development in simulations technology or practice, particularly in the work of computer simulation.
Physical simulation refers to simulation in which physical objects are substituted for the real thing. These physical objects are often chosen because they are smaller or cheaper than the actual object or system. () Alternatively, physical simulation may refer to computer simulations considering selected laws of physics, as in multiphysics simulation.For example in computer graphics SIGGRAPH 2007 | For Attendees | Papers Doc:Tutorials/Physics/BSoD – BlenderWiki . ()
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, sailing simulator, or driving simulator.
Continuous simulation is a simulation based on continuous-time rather than discrete-time steps, using numerical integration of differential equations.McLeod, J. (1968) "Simulation: the Dynamic Modeling of Ideas And Systems with Computers", McGraw-Hill, NYC.
Discrete-event simulation studies systems whose states change their values only at discrete times.Zeigler, B. P., Praehofer, H., & Kim, T. G. (2000) "Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems", Elsevier, Amsterdam. For example, a simulation of an epidemic could change the number of infected people at time instants when susceptible individuals get infected or when infected individuals recover.
Stochastic simulation is a simulation where some variable or process is subject to random variations and is projected using Monte Carlo techniques using pseudo-random numbers. Thus replicated runs with the same boundary conditions will each produce different results within a specific confidence band.
Deterministic simulation is a simulation which is not stochastic: thus the variables are regulated by deterministic algorithms. So replicated runs from the same boundary conditions always produce identical results.
Hybrid simulation (or combined simulation) corresponds to a mix between continuous and discrete event simulation and results in integrating numerically the differential equations between two sequential events to reduce the number of discontinuities.Giambiasi, N., Escude, B., & Ghosh, S. (2001). GDEVS: A generalized discrete event specification for accurate modeling of dynamic systems. In Autonomous Decentralized Systems, 2001. Proceedings. 5th International Symposium on (pp. 464–469). IEEE.
A stand-alone simulation is a simulation running on a single workstation by itself.
A is one which uses more than one computer simultaneously, to guarantee access from/to different resources (e.g. multi-users operating different systems, or distributed data sets); a classical example is Distributed Interactive Simulation (DIS).Petty, M. D. (April 1995). Computer-generated forces in a distributed interactive simulation. In Distributed Interactive Simulation Systems for Simulation and Training in the Aerospace Environment: A Critical Review (Vol. 10280, p. 102800I). International Society for Optics and Photonics.
Parallel simulation speeds up a simulation's execution by concurrently distributing its workload over multiple processors, as in high-performance computing.Fujimoto, R. M. (1990). Parallel discrete event simulation. Communications of the ACM, 33(10), 30–53.
Interoperable simulation is where multiple models, simulators (often defined as federates) interoperate locally, distributed over a network; a classical example is High-Level Architecture.Kuhl, F., Weatherly, R., & Dahmann, J. (1999). Creating computer simulation systems: an introduction to the high-level architecture. Prentice Hall PTR.Bruzzone A.G., Massei M., Simulation-Based Military Training, in Guide to Simulation-Based Disciplines, Vol.1. 315–361.
Modeling and simulation as a service is where simulation is accessed as a service over the web.Cayirci, E. (December 2013). Modeling and simulation as a cloud service: a survey. In Simulation Conference (WSC), 2013 Winter (pp. 389–400). IEEE.
Modeling, interoperable simulation and serious games is where serious game approaches (e.g. game engines and engagement methods) are integrated with interoperable simulation.Bruzzone, A. G., Massei, M., Tremori, A., Longo, F., Nicoletti, L., Poggi, S., ... & Poggio, G. (2014). MS2G: simulation as a service for data mining and crowdsourcing in vulnerability Reduction. Proceedings of WAMS, Istanbul, September.
Simulation fidelity is used to describe the accuracy of a simulation and how closely it imitates the real-life counterpart. Fidelity is broadly classified as one of three categories: low, medium, and high. Specific descriptions of fidelity levels are subject to interpretation, but the following generalizations can be made:
A synthetic environment is a computer simulation that can be included in human-in-the-loop simulations.
Simulation in failure analysis refers to simulation in which we create environment/conditions to identify the cause of equipment failure. This can be the best and fastest method to identify the failure cause.
Computer simulation has become a useful part of modeling many natural systems in physics, chemistry and biology,For a popular research project in the field of biochemistry where "computer simulation is particularly well suited to address these questions" Folding@home – Main , see Folding@Home. and human systems in economics and social science (e.g., 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 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 all the modeling almost effortless.
Modern usage of the term "computer simulation" may encompass virtually any computer-based representation.
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 , 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.
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 environment developed by Papert is one of the most well-known microworlds.
Project management simulation is increasingly used to train students and professionals in the art and science of project management. Using simulation for project management training improves learning retention and enhances the learning process.
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 historical educational games. "Reacting to the Past Home Page" . The National Science Foundation has also supported the creation of reacting games that address science and math education. "Reacting to the Past: STEM Games" . In social media simulations, participants train communication with critics and other stakeholders in a private environment.
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. "Carana," at 'PaxSims' blog, 27 January 2009 .
Military uses for simulation often involve aircraft or armoured fighting vehicles, but can also target small arms and other weapon systems training. Specifically, virtual firearms ranges have become the norm in most military training processes and there is a significant amount of data to suggest this is a useful tool for armed professionals. (pages missing)
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 and procedural simulations that can be viewed via standard web browsers) and can be interacted with using standard computer interfaces, such as the keyboard and computer mouse.
Simulation is being used to study patient safety, as well as train medical professionals. Studying patient safety and safety interventions in healthcare is challenging, because there is a lack of experimental control (i.e., patient complexity, system/process variances) to see if an intervention made a meaningful difference (Groves & Manges, 2017). An example of innovative simulation to study patient safety is from nursing research. Groves et al. (2016) used a high-fidelity simulation to examine nursing safety-oriented behaviors during times such as change-of-shift report.
However, the value of simulation interventions to translating to clinical practice are is still debatable. As Nishisaki states, "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, there is a need to have improved evidence to show that crew resource management training through simulation. One of the largest challenges is showing that team simulation improves team operational performance at the bedside. Although evidence that simulation-based training actually improves patient outcome has been slow to accrue, today the ability of simulation to provide hands-on experience that translates to the operating room is no longer in doubt.
One of the largest factors that might impact the ability to have training impact the work of practitioners at the bedside is the ability to empower frontline staff (Stewart, Manges, Ward, 2015). Another example of an attempt to improve patient safety through the use of simulations training is patient 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. One study found that just in time training improved the transition to the bedside. The conclusion as reported in Nishisaki (2008) work, was that the 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.
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 in 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.
In 2002, the Society for Simulation in Healthcare (SSH) was formed to become a leader in international interprofessional advances the application of medical simulation in healthcare
The need for a "uniform mechanism to educate, evaluate, and certify simulation instructors for the health care profession" was recognized by McGaghie et al. in their critical review of simulation-based medical education research. In 2012 the SSH piloted two new certifications to provide recognition to educators in an effort to meet this need.
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. Game engine have been applied to create these virtual medical environments to create an interactive method for learning and application of information in a clinical context.
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. 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.
The film Tron (1982) was the first film to use computer-generated imagery for more than a couple of minutes.
Advances in technology in the 1980s caused 3D simulation to become more widely used and it began to appear in movies and in computer-based games such as Atari's Battlezone (1980) and Acornsoft's Elite (1984), one of the first Wire-frame model for .
In 1993, the film 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 film 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 films.
The terminal in the Pan Am (TV series) no longer existed during the filming of this 2011–2012 aired series, which was no problem as they created it in virtual cinematography using automation camera angle finding and matching in conjunction with compositing real and simulated footage, which has been the bread and butter of the movie artist in and around since the early 2000s.
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. 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.
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. 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.
Another important goal of simulation in manufacturing systems is to quantify system performance. Common measures of system performance include the following:
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.
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.
A neuromechanical simulator that combines biomechanical and biologically realistic neural network simulation. It allows the user to test hypotheses on the neural basis of behavior in a physically accurate 3-D virtual environment.
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.
The successful use of simulation, early in the lifecycle, has been largely driven by increased integration of simulation tools with the entire set of CAD, CAM and product-lifecycle management solutions. 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.
One organization that has used simulation training for disaster preparedness is CADE (Center for Advancement of Distance Education). CADE 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.News-Medical.: "Net article-." " 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 firefighting, hazardous material handling, military training, and response to terrorist attack 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" 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 allow 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.
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. Simulators are also used for plant operator training. It is called Operator Training Simulator (OTS) and has been widely adopted by many industries from chemical to oil&gas and to the power industry. This created a safe and realistic virtual environment to train board operators and engineers. Mimic is capable of providing high fidelity dynamic models of nearly all chemical plants for operator training and control system testing.
Software tools typically calculate biomechanical properties including individual muscle forces, joint forces and moments. Most of these tools employ standard ergonomic evaluation methods such as the NIOSH lifting equation and Rapid Upper Limb Assessment (RULA). Some simulations also analyze physiological measures including metabolism, energy expenditure, and fatigue limits Cycle time studies, design and process validation, user comfort, reachability, and line of sight are other human-factors that may be examined in ergonomic simulation packages.
Modeling and simulation of a task can be performed by manually manipulating the virtual human in the simulated environment. Some ergonomics simulation software permits interactive, real-time simulation and evaluation through actual human input via motion capture technologies. However, motion capture for ergonomics requires expensive equipment and the creation of props to represent the environment or product.
Some applications of ergonomic simulation in include analysis of solid waste collection, disaster management tasks, interactive gaming,Bush, P. M., Gaines, S., Gammoh, F., & Wooden, S. A Comparison of Software Tools for Occupational Biomechanics and Ergonomic Research. automotive assembly line,Niu, J. W., Zhang, X. W., Zhang, X., & Ran, L. H. (December 2010). Investigation of ergonomics in automotive assembly line using Jack. industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on (pp. 1381–1385). IEEE. virtual prototyping of rehabilitation aids,Beitler, Matthew T., Harwin, William S., & Mahoney, Richard M. (1996) In Proceedings of the virtual prototyping of rehabilitation aids, RESNA 96, pp. 360–363. and aerospace product design.G.R. Bennett. The application of virtual prototyping in the development of complex aerospace products. Virtual Prototyping Journal, 1 (1) (1996), pp. 13–20 Ford engineers use ergonomics simulation software to perform virtual product design reviews. Using engineering data, the simulations assist evaluation of assembly ergonomics. The company uses Siemen's Jack and Jill ergonomics simulation software in improving worker safety and efficiency, without the need to build expensive prototypes.
Simulations are frequently used in financial training to engage participants in experiencing various historical as well as fictional situations. There are stock market simulations, portfolio simulations, risk management simulations or models and forex simulations. Such simulations are typically based on stochastic asset models. Using these simulations in a training program allows for the application of theory into a something akin to real life. As with other industries, the use of simulations can be technology or case-study driven.
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 reposition the simulated aircraft to a location from which the next approach can be begun.
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. Another advantage is reduced environmental impact, as simulators don't contribute directly to carbon or noise emissions.
There also exist "engineering flight simulators" which are a key element of the aircraft design process. Many benefits that come from a lower number of test flights like cost and safety improvements are described above, but there are some unique advantages. Having a simulator available allows for faster design iteration cycle or using more test equipment than could be fit into a real aircraft.
Simulators like these are mostly used within maritime colleges, training institutions, and navies. They often consist of a replication of a ships' bridge, with the operating console(s), and a number of screens on which the virtual surroundings are projected.
Central banks have been using payment system simulations to evaluate things such as the adequacy or sufficiency of liquidity available ( in the form of account balances and intraday credit limits) to participants (mainly banks) to allow efficient settlement of payments.Leinonen (ed.): Simulation studies of liquidity needs, risks and efficiency in payment networks (Bank of Finland Studies E:39/2007) Simulation publications Neville Arjani: Examining the Trade-Off between Settlement Delay and Intraday Liquidity in Canada's LVTS: A Simulation Approach (Working Paper 2006–20, Bank of Canada) Simulation publications The need for liquidity is also dependent on the availability and the type of netting procedures in the systems, thus some of the studies have a focus on system comparisons.Johnson, K.; McAndrews, J.; Soramäki, K. 'Economizing on Liquidity with Deferred Settlement Mechanisms' (Reserve Bank of New York Economic Policy Review, December 2004)
Another application is to evaluate risks related to events such as communication network breakdowns or the inability of participants to send payments (e.g. in case of possible bank failure).H. Leinonen (ed.): Simulation analyses and stress testing of payment networks (Bank of Finland Studies E:42/2009) Simulation publications This kind of analysis falls under the concepts of stress testing or scenario analysis.
A common way to conduct these simulations is to replicate the settlement logics of the real payment or securities settlement systems under analysis and then use real observed payment data. In case of system comparison or system development, naturally, also the other settlement logics need to be implemented.
To perform stress testing and scenario analysis, the observed data needs to be altered, e.g. some payments delayed or removed. To analyze the levels of liquidity, initial liquidity levels are varied. System comparisons (benchmarking) or evaluations of new netting algorithms or rules are performed by running simulations with a fixed set of data and varying only the system setups.
An inference is usually done by comparing the benchmark simulation results to the results of altered simulation setups by comparing indicators such as unsettled transactions or settlement delays.
With the increased interest in fantasy sports simulation models that predict individual player performance have gained popularity. Companies like What If Sports and StatFox specialize in not only using their simulations for predicting game results but how well individual players will do as well. Many people use models to determine whom to start in their fantasy leagues.
Another way simulations are helping the sports field is in the use of biomechanics. Models are derived and simulations are run from data received from sensors attached to athletes and video equipment. Sports biomechanics aided by simulation models answer questions regarding training techniques such as the effect of fatigue on throwing performance (height of throw) and biomechanical factors of the upper limbs (reactive strength index; hand contact time).
Computer simulations allow their users to take models which before were too complex to run, and give them answers. Simulations have proven to be some of the best insights into both play performance and team predictability.
The Shuttle Final Countdown Phase Simulation took 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 languageShuttle Ground Operations Simulator (SGOS) Summary Description Manual. National Aeronautics and Space Administration KSC Document # KSC-LPS-SGOS-1000, Revision 3 CHG-A, 1995.) 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.Math Model Main Propulsion System (MPS) Requirements Document, National Aeronautics and Space Administration KSC Document # KSCL-1100-0522, Revision 9, June 2009.
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).
However, the connection between simulation and dissembling later faded out and is now only of linguistic interest.South, in the passage quoted, was speaking of the differences between a falsehood and an honestly mistaken statement; the difference being that for the statement to be a lie the truth must be known, and the opposite of the truth must have been knowingly uttered. And, from this, to the extent to which a lie involves deceptive words, a simulation involves deceptive actions, deceptive gestures, or deceptive behavior. Thus, it would seem, if a simulation is false, then the truth must be known (for something other than the truth to be presented in its stead); and, for the simulation to simulate. Because, otherwise, one would not know what to offer up in a simulation. Bacon's essay expresses somewhat similar views. Samuel Johnson thought so highly of South's definition, that he used it in the entry for simulation in his Dictionary of the English Language.
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