仿真模型設(shè)計(jì)英文翻譯.doc

SIMULATION MODEL DESIGN仿真模型設(shè)計(jì)ABSTRACT摘要In this state of the art talk, we will present a structure for defining and categorizing simulation model designs. In the past, simulation researchers have created categories for discrete event simulation: event, process and activity; however, there are problems with this breakdown. First, the major problem is that the taxonomy based on these three sub-types deals with only discrete event methods. Discrete time methods including a spatial decomposition of a physical system(cellular automata, L-Systems) or a continuous model are not included. Second, the terms “event,” process” and “activity” create a division among classes of simulation languages, rather than a division based on model design. The term “process,” for example, is really a level of abstraction higher than “event” and is not orthogonal to “event.” The structure that we present in this talk is more comprehensive and provides simulations with a unified framework that is independent of the terms discrete and continuous.我們將提出一份結(jié)構(gòu)界定及分類(lèi)模型設(shè)計(jì).在過(guò)去, 模擬研究者創(chuàng)建類(lèi)別離散事件模擬:事件過(guò)程和活動(dòng); 不過(guò),有問(wèn)題這一細(xì)分. 第一,主要的問(wèn)題是,分類(lèi)的基礎(chǔ)上,這三個(gè)子類(lèi)處理,只有離散事件的方法. 離散時(shí)間的方法,包括空間分解一個(gè)物理系統(tǒng)(元胞自動(dòng)機(jī),L-系統(tǒng))或連續(xù)模型,則不包括在內(nèi). 第二,從事件過(guò)程和活動(dòng),營(yíng)造一個(gè)分工各階層仿真語(yǔ)言 而非部基于模型設(shè)計(jì). 所謂過(guò)程中,例如, 真是一個(gè)較高的抽象層次比活動(dòng),而不是正交的盛會(huì) 這個(gè)架構(gòu)之下,我們目前 在這次演講是比較全面,并提供一個(gè)統(tǒng)一模擬的框架,是獨(dú)立的職權(quán)離散連續(xù)1 OVERVIEW1概況Simulation is a tightly coupled and iterative three component process composed of 1) model design, 2) model execution and 3) execution analysis as shown in Fig. 1 along with the relevant sub-areas and book chapter numbers in a book which has just been published in the Fall of 1994 (Fish wick 1995). The bold lines in Fig. 1 are to show our emphasis in the text: model design and model execution. The third area of execution analysis already has broad coverage in simulation and is not covered in the book or this state of the art talk. Also, in this talk, we will cover model design and not algorithms for model execution. Perhaps the hardest general problem in simulation is determining the exact method that one should use to create a model. After all, where does one begin? Just as the discipline of software engineering has emerged to address this question for software, in general, modelers also have a need to explore similar issues: how dower engineer models? While there are many modeling techniques for simulation, we are often in a quandary as to which model technique to use, and under what conditions we should use it. Our approach is depicted in Fig. 2 along with the associated chapter references where each modeling method is defined. For the talk, we will proceed to briefly discuss the model types. A more complete written treatment is provided in Fish wick (1995).仿真是一緊耦合迭代三個(gè)部分組成的過(guò)程:1)模型設(shè)計(jì) 2)模型執(zhí)行和3)執(zhí)行情況分析如圖. 1連同相關(guān)小區(qū)及書(shū)章數(shù)在一本剛剛出版的 1994年秋季(Fishwick1995). 大膽的線(xiàn)路圖. 第一是要展示我們的重點(diǎn),在文字:模具設(shè)計(jì)和模范執(zhí)行. 第三方面的執(zhí)行分析已經(jīng)復(fù)蓋面寬的模擬,而不是蓋在書(shū)或 這個(gè)國(guó)家的藝術(shù)講座. 另外,在這次會(huì)談中,我們將涵蓋模式設(shè)計(jì),而不是算法的執(zhí)行模式. 也許是最難的一般問(wèn)題,在模擬確定準(zhǔn)確的方法,一要利用創(chuàng)造一種模式. 畢竟,從何處著手呢? 正如紀(jì)律的軟件工程出現(xiàn)了解決這一問(wèn)題的軟件,一般 模具設(shè)計(jì)者也有必要探討類(lèi)似的問(wèn)題:如何進(jìn)行工程師模式? 雖然有許多建模技術(shù)用于模擬, 我們常常處于兩難局面,因?yàn)樵撃Ｐ图夹g(shù)的運(yùn)用, 以及在什么條件下,我們應(yīng)該利用它. 我們的方針是描圖. 2連同相關(guān)章節(jié)參考資料每個(gè)建模方法的定義. 在會(huì)談中,我們將開(kāi)始討論一下模型類(lèi)型.Fishwick(1995年)的一個(gè)較完整的書(shū)面治療提供. 2 MODEL TYPES2模型類(lèi)型There are five basic model types, and one complex ”kJ type which includes abstraction levels, each composed of one of the basic types. All model types are now discussed.有五個(gè)基本模式類(lèi)型,和一個(gè)復(fù)雜的焦式,其中包括抽象層次 各由一國(guó)的基本類(lèi)型. 所有型號(hào)類(lèi)型現(xiàn)討論. (1) Conceptual Models(1) 概念模型Conceptual models represent the first phase in any modeling endeavor. All static and dynamic knowledge about the physical system must be encoded in some form which allows specification of interaction without necessarily specifying the dynamics in quantitative terms. Semantic networks (Woods 1975) present one way of encoding conceptual semantics; however, we have chosen object-oriented design networks (Booch1991; Rumbaugh, Blaha, Premerlani, Frederick, and Lorenson 1991) which have more formal treatment. The ultimate conceptual model is one based on database technology, such as an object-oriented database, capturing all facets of the physical system.概念模型所代表的第一階段,在任何建模工作. 所有靜態(tài)和動(dòng)態(tài)的了解物理系統(tǒng)必須打上某種形式允許規(guī)格互動(dòng) 不一定要指明的動(dòng)態(tài)和18.22%. 語(yǔ)義網(wǎng)絡(luò)恢復(fù)(Woods1975)本辦法之一編碼概念語(yǔ)義學(xué); 但是,我們選擇了面向?qū)ο笤O(shè)計(jì)網(wǎng)(Booch1991; Bumbaugh,Blaha,Bremerlani, Frederick 和lorenson1991)有較正式修正.終極概念模型是基于數(shù)據(jù)庫(kù)技術(shù), 例如一個(gè)面向?qū)ο蟮臄?shù)據(jù)庫(kù), 所有捕捉層面的物理系統(tǒng). (2) Declarative Models(2) Declarative型號(hào) These models permit dynamics to be encoded as statetostate or event-to-event transitions. The idea behind declarative modeling is to focus on the structure of state (or event) from one time period to the next, while de-emphasizing functions or constraints which define the transition. Models such as finite state automata (Hopcroft and Ullman 1979), Markov models, event graphs (Schruben 1983) and temporal logic models (Moszkowski 1986) fall into the declarative category. Declarative models are state-based(FSAs), event-based (event graphs) or a hybrid (Petrinets (Peterson 1981).這些模型允許動(dòng)態(tài)進(jìn)行編碼,作為國(guó)家增生或事件-事件躍遷. 念頭宣示建模是著眼于結(jié)構(gòu)的國(guó)家(或活動(dòng))由一個(gè)時(shí)期來(lái) 未來(lái),而不再?gòu)?qiáng)調(diào)職能或制約,其中確定了過(guò)渡. 模型,例如有限狀態(tài)自動(dòng)(Hopcroft和ullman1979),馬爾可夫模型 事件圖(schruben1983年)和時(shí)序邏輯模型(科夫斯基1986年)落入declarative類(lèi). declarative模式是基于狀態(tài)(大使),基于事件(事件圖)或混合(Petrinets(peterson1981). (3) Functional Models(3)功能模式 Functional models represent a directional flow of a signal (discrete or continuous) among transfer functions(boxes). When the system is seen as a set of boxes communicating with messages or signals, the functional paradigm takes hold. The use of functional models is found in control engineering (Ogata1970; Dorf 1986) (with continuous signals) as well as queuing networks for computer system model design (MacDougall 1987). Some functional systems focus not so much on the functions, but more on the variables. Such models include signal flow graphs, compartmental models (Jacquez 1985), and Systems Dynamics (Roberts, Andersen, Deal, Garet, and Shaffer1983).功能模塊,代表了定向流動(dòng)的一個(gè)信號(hào)(離散或連續(xù))之間的傳遞函數(shù)(箱). 當(dāng)系統(tǒng)被看作是一套箱子溝通訊息或信號(hào),功能范式掌握. 使用功能模塊,發(fā)現(xiàn)在控制工程(Ogata1970; Dorf1986)(連續(xù)信號(hào))以及排隊(duì)網(wǎng)絡(luò)計(jì)算機(jī)系統(tǒng)模型設(shè)計(jì)(麥德1987). 有些功能制度的重點(diǎn)是不是這么多的功能,但更多的變數(shù). 這種模式包括的信號(hào)流圖,并求出模型(Jacquez1985),及系統(tǒng)動(dòng)力學(xué)(羅伯茨,安德森, Deal,Garet,Shaffer1983). (4) Constraint Models(4)約束模式There are two types of constraint models:equational and graph-based. Constraint models are models where a balance (or constraint)is at the heart of the model design. In such a case, an equation is often the best characterization of the model since a directional approach such as functional modeling is insufficient. Equational systems include difference models, ODEs and delay differential equations. Graphical models such as bond graphs (Breedveld 1986;karnopp, Margolis, and Rosenberg 1990) and electrical network graphs (Raghuram 1989)are also constraint based.有兩種類(lèi)型的約束模式:等式和圖型. 約束模式模式下的平衡(或約束),是在心臟的模型設(shè)計(jì). 在這種情況下, 方程式往往是最好的表征的模式,因?yàn)橐粋€(gè)方向性的做法,諸如功能建模是不夠的. 等式系統(tǒng)包括不同的模式,賦與時(shí)滯微分方程. 圖形模式,如債券圖(Breedveld1986年; Karnopp,Margolis, 和羅森堡1990年)和電力網(wǎng)絡(luò)圖(1989年幣值)也是基于約束. (5) Spatial Models(5)空間模式If a system is spatially decomposed as for cellular automata (Wolfram 1986; Toffoli and Margolus 1987),Ising systems, PDE-based solutions or finite element models, then the system is being modeled using a spatial modeling technique. Spatial models are used to model systems in great detail, where individual pieces of physical phenomena are modeled by discretizing the geometry of the system. Spatial models are “entity-based” or “space-based.” Entity-based spatial models focus on a fixed space where the entity dynamics are given whereas space-based focus on how the space changes by convolving a template over the space at each time step. PDEs are space-based where the template defines the integration method. L-Systems (Prusinkiewicz and Lindenmeyer 1990) are entity-based since the dynamics are based on how the organism grows over a fixed space. 如果一個(gè)系統(tǒng)在空間上分解為蜂窩自動(dòng)(Wolfram1986年; Toffoli和margolus1987),伊辛系統(tǒng) 基于PDE解或有限元模型,隨后該系統(tǒng)正在modeled利用空間建模技術(shù). 空間模型是用來(lái)模擬系統(tǒng)非常詳盡, 凡單項(xiàng)物理現(xiàn)象,是仿照離散幾何體系. 空間模型是實(shí)體型或航天為本 實(shí)體的空間數(shù)據(jù)模型,重點(diǎn)放在了固定場(chǎng)所的實(shí)體動(dòng)力學(xué)刊載 而空間的焦點(diǎn)放在如何空間變化convolving模板以上的空間,在每個(gè)時(shí)間步.PDEs空間的那里的模板定義集成方法. L-系統(tǒng)(Pprusinkiewicz和Lindenmeyer1990)是實(shí)體型自動(dòng)力學(xué)是基于如何生物體成長(zhǎng)超過(guò)定額 太空. (6) Multi Models(6) 多種型號(hào)Large scale models are built from one or more abstraction levels, each level being designed using one of the aforementioned more primitive model types. The lowest level of abstraction for a system will probablyuse a spatial model whereas the highest level may use a declarative finite state machine. Intermediate levels will often use functional and constraint techniques. Models which are composed of other models are termed multimodal (Fishwick and Zeigler 1992; Fishwick 1992; Fishwick 1993). By utilizing abstraction levels, we can switch levels during the simulationand use the abstraction most appropriate at that given time. This approach gives us multiple levels of explanation and is computationally more efficient than simulating the system at one level.大型模型是建立一個(gè)或多個(gè)抽象層次 每個(gè)級(jí)別的設(shè)計(jì),使用上述任何一種更為原始模型類(lèi)型. 最低程度的抽象的體制,可能會(huì)使用一種空間發(fā)展模式,而最高級(jí)別的可使用 宣示有限狀態(tài)機(jī). 中級(jí)班將經(jīng)常使用功能和約束技巧. 這些模式是由其他模型被稱(chēng)為多式聯(lián)運(yùn)(Fishwick和Zeigler1992年; Fishwick1992年; Fishwick1993). 用抽象層次 我們可以切換水平在模擬和運(yùn)用抽象最適合在這個(gè)時(shí)候. 這種做法給人多層次的解釋,是計(jì)算效率高于模擬系統(tǒng)在一個(gè)層面. Computer simulation is designing a model of an actual or theoretical physical system, executing the model on a digital computer, and analyzing the execution output. Simulation embodiesthe principle of “l(fā)earning by doing”-to learn about the system we must first build a model of some sort and then operate the model. Children understand the world around them by simulating (with toys and figurines) most of their interactions with other people, animals and objects. Computer simulation is the electronic equivalent of this type of role playing. It serves to drive synthetic environments and virtual worlds. Within the overall task of simulation, there are three primary sub-fields: model design, model execution and model analysis (see Fig. 1). To simulate something physical, you will first need to create a mathematical model which represents that physical object. Models can take many forms including declarative, functional, constraint, spatial or multimodal. A multimode1 contains multiple integrated models each of which represents a level of granularity for the physical system. The next task, once a model has been developed, is to execute the model on a computer. That is, you need to create a computer program which steps through time while updating the state and event variables in your mathematical model. There are many ways to “step through time.” You can, for instance, leap through time using event scheduling or you can employ small time increments using time slicing. You can also execute (i.e., simulate) the program on a massively parallel computer. This is called parallel and distributed simulation. For many large-scale models, this is the only feasible way of getting answers back in a reasonable amount of time. System simulation can be done at many different levels of fidelity. One reader will think of physics-based models and output. Another may think of more abstract models which yield higherlevel, less detailed output as in a queuing network. Models are designed to provide answers at a given abstraction level-the more detailed the model, the more detailed the output. The kind of output you need will suggest the type of model you will employ. An example of graphical output from a physically-based model generated using the program AERO is shown as a stereo pair of “rigid bodies” in Fig. 2. You can view this stereo pair without the use of external viewing aids, by diverging the eyes. (Divergence can be achieved in a variety of ways. Try focusing on an object three or four feet from your eyes. Then place these figures between your eyes and the object. You will see three frames, with the middle frame being the combined left right stereo frame.)計(jì)算機(jī)仿真設(shè)計(jì)模型的一個(gè)實(shí)際或理論物理體系, 執(zhí)行模型在計(jì)算機(jī)上,并分析執(zhí)行輸出. 仿真體現(xiàn)了學(xué)做,了解他們的制度,我們必須先建立一個(gè)模型,有些 那樣的話(huà),那么經(jīng)營(yíng)模式. 孩子們了解他們周?chē)澜绲哪M(玩具及快遞)大部分的互動(dòng)與其他人, 動(dòng)物及物體. 計(jì)算機(jī)仿真是相等的電子這一類(lèi)的角色扮演. 它有助于推動(dòng)綜合環(huán)境和虛擬世界. 在整個(gè)任務(wù)的仿真,有三個(gè)主要的分支領(lǐng)域:模型設(shè)計(jì) 模型執(zhí)行和模型分析(見(jiàn)圖. 1). 來(lái)模擬一些物理,你首先要建立一個(gè)數(shù)學(xué)模型,其中,代表實(shí)物. 模型可以采取多種形式,包括宣示,功能有限,空間或多式聯(lián)運(yùn). 一多式聯(lián)運(yùn)含有多重整合模式各自代表一個(gè)層面的粒度的物理系統(tǒng). 下一個(gè)任務(wù),一旦模型已經(jīng)制定,是執(zhí)行示范一臺(tái)電腦. 即 你必須建立一個(gè)計(jì)算機(jī)程序的步驟,通過(guò)的時(shí)間,同時(shí)更新?tīng)顟B(tài)和事件的變數(shù)在您 數(shù)學(xué)模型. 有很多方法的步驟,通過(guò)時(shí)間的認(rèn)識(shí). 你可以,比如 跨越時(shí)間使用事件調(diào)度或者你可以用小的時(shí)間增量利用時(shí)間切片. 你也可以執(zhí)行(即模擬)的計(jì)劃,大規(guī)模并行計(jì)算機(jī). 這就是所謂的并行與分布仿真. 對(duì)于許多大型模型,這是唯一可行的方式得到的答案早在一個(gè)合理的時(shí)間. 仿真系統(tǒng)可在13多個(gè)不同層次的忠誠(chéng)度. 一位讀者會(huì)認(rèn)為物理模型和輸出. 另一個(gè)則可能認(rèn)為較抽象的模型,其中產(chǎn)量上級(jí),不太詳細(xì)輸出作為一個(gè)排隊(duì)網(wǎng)絡(luò). 型號(hào)的設(shè)計(jì)提供了答案,在一個(gè)特定的抽象層次的更詳細(xì)的模型,更詳細(xì)的輸出. 什么樣的輸出,你需要將建議采用哪種模式,你會(huì)聘用. 為例圖形輸出從一個(gè)物理模型產(chǎn)生器程序aero顯示為37,239美元一雙 剛性機(jī)構(gòu)無(wú)花果. 2. 你可以把這個(gè)立體無(wú)需使用外部看艾滋病,不同的眼睛. (分歧,可以通過(guò)各種方式. 盡量集中于一個(gè)對(duì)象三或四英尺從貴 眼睛. 然后把這些數(shù)字與你的眼睛與物體. 你會(huì)看到三個(gè)幀, 隨著幀被合并左側(cè)的立體框架). Technologies such as Simulation and Virtual Reality will dominate the entertainment and science forefronts well into the next century. With todays computer prices, personal computers are highly affordable. Armed with your computer, you can proceed to build models of reality and “l(fā)et them loose” to see what happens and to learn more about reality by modeling it. While what we may do today may be primitive by standards set in science fiction shows such as Star Trek (The Holodeck) and Lawnmower Man, the present computer simulation discipline will lead the way to these eventual goals. The key word is “digital” as pointed out by many such as Nicholas Negroponte at the MIT Media Lab in his recent text “Being Digital.” We want to create digital replicas of everything you see as you look around you while reading this article. When you want to concoct a digital world, you will pick digital objects, using a 3D, immersive construction tool to put them together. The digital objects may be located anywhere on the Internet. You will use help tools (or autonomous agents) to locate the building block objects for your digital world. Some work is being done in Distributed Interactive Simulation which is a thrust pioneered by the Department ofDefense. The implications of these types of simulations are profound since the idea of distributed simulation has enormous potential, also, in industrial and entertainment fields.技術(shù),如模擬與虛擬現(xiàn)實(shí)技術(shù)將主導(dǎo)娛樂(lè)和科學(xué)前沿,并進(jìn)入下一世紀(jì). 如今的電腦價(jià)格,個(gè)人電腦的負(fù)擔(dān). 手持電腦, 你可以著手建立模型的現(xiàn)實(shí),讓他們松散來(lái)看看,并學(xué)習(xí)更多 對(duì)現(xiàn)實(shí)的模型. 雖然我們可能做今天可能是原始的標(biāo)準(zhǔn)的科幻表演等星艦 (Holodeck)和剪草機(jī)的男子,目前的計(jì)算機(jī)仿真學(xué)科將率先開(kāi)展對(duì)這些最終目標(biāo). 關(guān)鍵的一句話(huà)是:數(shù)字化正如許多諸如走下神壇的尼葛洛龐帝的麻省理工學(xué)院媒體實(shí)驗(yàn)室 他最近的文字:數(shù)字化 我們要?jiǎng)?chuàng)造數(shù)字復(fù)制品一切你看你看周?chē)?在閱讀這篇文章. 當(dāng)你想臆造數(shù)字世界,你會(huì)選擇數(shù)字對(duì)象,采用三維, 沉浸施工工具把它們放在一起. 數(shù)字對(duì)象可能位于任何地方上網(wǎng). 你會(huì)使用幫助工具(或自治區(qū)代理商)尋找建筑砌塊對(duì)象為您的數(shù)碼世界. 有些工作正在做分布式交互仿真是推力最先由國(guó)防部. 影響這些類(lèi)型的模擬,由于深刻的思想分布仿真技術(shù)的巨大潛力,同時(shí), 在工業(yè)和娛樂(lè)等領(lǐng)域. REFERENCES參考資料Booch, G. 1991. Object Oriented Design. BenjaminCummings.Breedveld, P. C. 1986. A Systematic Method to DeriveBond Graph Models. In Second EuropeanSimulation Congress, Antwerp, Belgium.Dorf, R. C. 1986. Modern Control Systems. AddisonWesley.Fishwick, P. A. 1992. An Integrated Approach toSystem Modelling using a Synthesis of ArtificialIntelligence, Software Engineering and SimulationMethodologies. A CM Transactions on Modelingand Computer Simulation. (submitted forreview).Fishwick, P. A. 1993. A simulation environment formultimodeling. Discrete Event Dynamic Systems:Theory and Applications 9, 151-171.Fishwick, P. A. 1995. Simulation Model Design andExecution: Building Digital Worlds. PrenticeHall.Fishwick, P. A. and B. P. Zeigler. 1992. A Multimode1Methodology for Qual