“Modeling and simulation”的意思、由来-开放百科全书

Modeling and simulation (M&S) at simple terms is a substitute for physical experimentation, in which computers are used to calculate the results of some physical phenomenon. As it is apparent from its name "Modeling and simulation" firstly a computer is used to build a mathematical model which contains all the parameters of physical model and represent physical model in virtual form then conditions are applied which we want to experiment on physical model, then simulation starts i.e, we leave on computer to calculate the results of those conditions on mathematical model. In this way, actual experimentation can be avoided which is costly and time-consuming instead of using mathematical knowledge and computer's computation power to solve real-world problems cheaply and in a time efficient manner. As such, M&S can facilitate understanding a system's behavior without actually testing the system in the real world. For instance, to determine which type of spoiler would improve traction the most while designing a race car, a computer simulation of the car could be used to estimate the effect of different spoiler shapes on the coefficient of friction in a turn. Useful insights about different decisions in the design could be gleaned without actually building the car. In addition, simulation can support experimentation that occurs totally in software, or in human-in-the-loop environments where simulation represents systems or generates data needed to meet experiment objectives. Furthermore, simulation can be used to train persons using a virtual environment that would otherwise be difficult or expensive to produce.

The use of M&S within engineering is well recognized. Simulation technology belongs to the tool set of engineers of all application domains and has been included in the body of knowledge of engineering management. M&S helps to reduce costs, increase the quality of products and systems, and document and archive lessons learned.

M&S is a discipline on its own. Its many application domains often lead to the assumption that M&S is a pure application. This is not the case and needs to be recognized by engineering management experts who want to use M&S. To ensure that the results of the simulation are applicable to the real world, the engineering manager must understand the assumptions, conceptualizations, and implementation constraints of this emerging field. Results of actual experiments must be considered to make models better.

Interest in simulations

Technically, simulation is well accepted. The 2006 National Science Foundation (NSF) Report on "Simulation-based Engineering Science"^[1] showed the potential of using simulation technology and methods to revolutionize the engineering science. Among the reasons for the steadily increasing interest in simulation applications are the following:

The military and defense domain, in particular within the United States, has been the main M&S champion, in form of funding as well as application of M&S. E.g., M&S in modern military organizations is part of the acquisition/procurement strategy. Specifically, M&S is used to conduct Events and Experiments that influence requirements and training for military systems. As such, M&S is considered an integral part of systems engineering of military systems. Other application domains, however, are currently catching up. M&S in the fields of medicine, transportation, and other industries is poised to rapidly outstrip DoD's use of M&S in the years ahead, if it hasn't already happened.^[6]

Simulation in science

Modeling and simulation are important in research. Representing the real systems either via physical reproductions at smaller scale, or via mathematical models that allow representing the dynamics of the system via simulation, allows exploring system behavior in an articulated way which is often either not possible, or too risky in the real world.

As an emerging discipline

"The emerging discipline of M&S is based on developments in diverse computer science areas as well as influenced by developments in Systems Theory, Systems Engineering, Software Engineering, Artificial Intelligence, and more. This foundation is as diverse as that of engineering management and brings elements of art, engineering, and science together in a complex and unique way that requires domain experts to enable appropriate decisions when it comes to application or development of M&S technology in the context of this paper. The diversity and application-oriented nature of this new discipline sometimes result in the challenge, that the supported application domains themselves already have vocabularies in place that are not necessarily aligned between disjunctive domains. A comprehensive and concise representation of concepts, terms, and activities is needed that make up a professional Body of Knowledge for the M&S discipline. Due to the broad variety of contributors, this process is still ongoing."^[7]

Padilla et al. recommend in "Do we Need M&S Science" to distinguish between M&S Science, Engineering, and Applications.^[8]

Models can be composed of different units (models at finer granularity) linked to achieving a specific goal; for this reason they can be also called modeling solutions.

More generally, modeling and simulation is a key enabler for systems engineering activities as the system representation in a computer readable (and possibly executable) model enables engineers to reproduce the system (or Systems of System) behavior. A collection of applicative modeling and simulation method to support systems engineering activities in provided in.^[9]

In pharmacy education

The shortage of pharmacists in the United States has prompted increases in class sizes and the number of satellite and distance-learning programs at colleges and schools of pharmacy. This rapid expansion has created a burden on existing clinical experimental sites.^[10] The Accreditation Council on Pharmacy Education (ACPE) requires at least 1440 hours of advanced pharmacy practice experience (APPE); included among the 1440 hours of APPE, the ACPE requires colleges and schools of pharmacy to provide a minimum of 300 hours of introductory pharmacy practice experience (IPPE) interspersed throughout the first three years of the pharmacy curriculum.^[11] Simulation training may be one such model to provide students with the opportunity to apply didactic knowledge and reduce the burden on experiential sites. The inclusion of simulation in IPPEs has gained acceptance and is encouraged by ACPE as described in the Policies and Procedures for ACPE Accreditation of Professional Degree Programs – January 2010. Addendum 1.3, Simulations for Introductory Pharmacy Practices Experiences – Approved June 2010, states:

Several pharmacy colleges and schools have incorporated simulation as part of their core curricula. At the University of Pittsburgh School of Pharmacy, high-fidelity patient simulators are used to reinforce therapeutics. While the University of Rhode Island College of Pharmacy integrated their simulation program into their pharmacology and medicinal chemistry coursework; and was the first college of pharmacy to purchase a high-fidelity patient simulator. Some pharmacy colleges and schools host virtual reality and full environment simulation programs. For example, Purdue University School of Pharmacy and the university's Envision Center for Data Perceptualization collaborated with the United States Pharmacopeia (USP) to create a virtual clean room that is USP 797 standards compliant.^[12]

Application domains

There are many categorizations possible, but the following taxonomy has been very successfully used in the defense domain, and is currently applied to medical simulation and transportation simulation as well.

A special use of Analyses Support is applied to ongoing business operations. Traditionally, decision support systems provide this functionality. Simulation systems improve their functionality by adding the dynamic element and allow to compute estimates and predictions, including optimization and what-if analyses.

Individual concepts

Although the terms "modeling" and "simulation" are often used as synonyms within disciplines applying M&S exclusively as a tool, within the discipline of M&S both are treated as individual and equally important concepts. Modeling is understood as the purposeful abstraction of reality, resulting in the formal specification of a conceptualization and underlying assumptions and constraints. M&S is in particular interested in models that are used to support the implementation of an executable version on a computer. The execution of a model over time is understood as the simulation. While modeling targets the conceptualization, simulation challenges mainly focus on implementation, in other words, modeling resides on the abstraction level, whereas simulation resides on the implementation level.

Conceptualization and implementation – modeling and simulation – are two activities that are mutually dependent, but can nonetheless be conducted by separate individuals. Management and engineering knowledge and guidelines are needed to ensure that they are well connected. Like an engineering management professional in systems engineering needs to make sure that the systems design captured in a systems architecture is aligned with the systems development, this task needs to be conducted with the same level of professionalism for the model that has to be implemented as well. As the role of big data and analytics continues to grow, the role of combined simulation of analysis is the realm of yet another professional called a simplest – in order to blend algorithmic and analytic techniques through visualizations available directly to decision makers. A study designed for the Bureau of Labor and Statistics^[13] by Lee et al. provides an interesting look at how bootstrap techniques (statistical analysis) were used with simulation to generate population data where there existed none.

Academic programs

Modeling and simulation have only recently become an academic discipline of its own. Formerly, those working in the field usually had a background in engineering.

Modeling and Simulation Body of Knowledge

The Modeling and Simulation Body of Knowledge (M&S BoK) is the domain of knowledge (information) and capability (competency) that identifies the modeling and simulation community of practice and the M&S profession, industry, and market.^[14]

The M&S BoK Index is a set of pointers providing handles so that subject information content can be denoted, identified, accessed, and manipulated.^[14]

Summary

See also

References

1. ^{{cite web|publisher=National Science Foundation (NSF) Blue Ribbon Panel|title=Report on Simulation-Based Engineering Science|date=2006-05-01|url=https://www.nsf.gov/pubs/reports/sbes_final_report.pdf}}
2. ^{{cite web|url=http://io9.gizmodo.com/5916320/supercomputer-simulates-nuclear-explosion-down-to-the-molecular-level|title=Supercomputer simulates nuclear explosion down to the molecular level|author=George Dvorsky|publisher=Gawker Media|work=io9}}
3. ^{{cite web|url=http://www.hpcwire.com/2013/11/14/behind-blue-waters-hurricane-sandy-simulation/|title=Hurricane Force Supercomputing: Petascale Simulations of Sandy|work=HPCwire}}
4. ^{{cite web|url=http://scijinks.jpl.nasa.gov/hurricane-simulation/|title=NOAA's SciJinks :: Simulate a Hurricane|publisher=}}
5. ^{{cite web|url=http://www.livescience.com/6392-9-super-cool-supercomputers.html|title=9 Super-Cool Uses for Supercomputers|work=LiveScience.com}}
6. ^{{cite journal|last=Collins|first=A.J. |author2=S.R. Shefrey |author3=J. Sokolowski |author4=C.D. Turnitsa |author5=E. Weisel|title=Modeling and Simulation Standards Study: Healthcare Workshop report|journal=VMASC Report, Suffolk VA|date=January 2011}}
7. ^{{cite journal|last=Tolk|first=Andreas|title=Engineering Management Challenges for Applying Simulation as a Green Technology|url=http://ww2.odu.edu/~atolk/research/ASEM.045.pdf}}
8. ^{{cite journal|last=Padilla|first=Jose |author2=S.Y. Diallo |author3=A. Tolk|title=Do We Need M&S Science?|journal=SCS M&S Magazine|date=October 2011|issue=4|pages=161–166|url=http://www.scs.org/magazines/2011-10/index_file/Files/Padilla-Diallo-Tolk.pdf|accessdate=July 1, 2012}}
9. ^{{cite book|editor1-last=Gianni|editor1-first=Daniele|editor2-last=D'Ambrogio|editor2-first=Andrea|editor3-last=Tolk|editor3-first=Andreas|title=Modeling and Simulation-Based Systems Engineering Handbook|date=December 2, 2014|publisher=CRC Press|isbn=9781466571457|pages=513|edition=1st|url=http://www.crcpress.com/product/isbn/9781466571457}}
10. ^, Vyas, D., Wombwell, E., Russell, E., & Caligiuri, F. (2010). High-fidelity patient simulationseries to supplement introductory pharmacy practice experiences. Am J Pharm Educ, 74(9), 169.
11. ^{{cite web|title=Accreditation Council forPharmacy Education: Policies and Procedures for ACPE Accreditation forProfessional Degree Programs|year=2011|accessdate=July 13, 2013|url=https://www.acpe-accredit.org/pdf/FinalS2007Guidelines2.0.pdf}}
12. ^Lin, K., Travlos, D. V., Wadelin, J. W., & Vlasses, P. H. (2011). Simulation and IntroductoryPharmacy Practice Experiences. American journal of Pharmaceutical Education, 75(10), 209. doi: 10.5688/ajpe7510209
13. ^{{cite web|url=http://www.bls.gov/osmr/pdf/st130210.pdf|format=PDF|title=Simulation Study to Validate Sample Allocation for the National Compensation Survey|publisher=Bureau of Labor Statistics|work=JSM 2013 - Survey Research Methods Section|year=2013|author=Lee, Hyunshik J.|displayauthors=etal}}
14. ^¹[https://www.scs.org/confernc/foundations/finalprogram.doc Waite, W. (2004) "Foundations '04: A Workshop for VV&A in the 21st Century, Session 10: V&V Education Initiatives]