仿真模型设计英文翻译.doc

SIMULATION MODEL DESIGN仿真模型设计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.我们将提出一份结构界定及分类模型设计.在过去, 模拟研究者创建类别离散事件模拟:事件过程和活动; 不过,有问题这一细分. 第一,主要的问题是,分类的基础上,这三个子类处理,只有离散事件的方法. 离散时间的方法,包括空间分解一个物理系统(元胞自动机,L-系统)或连续模型,则不包括在内. 第二,从事件过程和活动,营造一个分工各阶层仿真语言 而非部基于模型设计. 所谓过程中,例如, 真是一个较高的抽象层次比活动,而不是正交的盛会 这个架构之下,我们目前 在这次演讲是比较全面,并提供一个统一模拟的框架,是独立的职权离散连续1 OVERVIEW1概况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).仿真是一紧耦合迭代三个部分组成的过程:1)模型设计 2)模型执行和3)执行情况分析如图. 1连同相关小区及书章数在一本刚刚出版的 1994年秋季(Fishwick1995). 大胆的线路图. 第一是要展示我们的重点,在文字:模具设计和模范执行. 第三方面的执行分析已经复盖面宽的模拟,而不是盖在书或 这个国家的艺术讲座. 另外,在这次会谈中,我们将涵盖模式设计,而不是算法的执行模式. 也许是最难的一般问题,在模拟确定准确的方法,一要利用创造一种模式. 毕竟,从何处着手呢? 正如纪律的软件工程出现了解决这一问题的软件,一般 模具设计者也有必要探讨类似的问题:如何进行工程师模式? 虽然有许多建模技术用于模拟, 我们常常处于两难局面,因为该模型技术的运用, 以及在什么条件下,我们应该利用它. 我们的方针是描图. 2连同相关章节参考资料每个建模方法的定义. 在会谈中,我们将开始讨论一下模型类型.Fishwick(1995年)的一个较完整的书面治疗提供. 2 MODEL TYPES2模型类型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.有五个基本模式类型,和一个复杂的焦式,其中包括抽象层次 各由一国的基本类型. 所有型号类型现讨论. (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阶段,在任何建模工作. 所有静态和动态的了解物理系统必须打上某种形式允许规格互动 不一定要指明的动态和18.22%. 语义网络恢复(Woods1975)本办法之一编码概念语义学; 但是,我们选择了面向对象设计网(Booch1991; Bumbaugh,Blaha,Bremerlani, Frederick 和lorenson1991)有较正式修正.终极概念模型是基于数据库技术, 例如一个面向对象的数据库, 所有捕捉层面的物理系统. (2) Declarative Models(2) Declarative型号 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).这些模型允许动态进行编码,作为国家增生或事件-事件跃迁. 念头宣示建模是着眼于结构的国家(或活动)由一个时期来 未来,而不再强调职能或制约,其中确定了过渡. 模型,例如有限状态自动(Hopcroft和ullman1979),马尔可夫模型 事件图(schruben1983年)和时序逻辑模型(科夫斯基1986年)落入declarative类. declarative模式是基于状态(大使),基于事件(事件图)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).功能模块,代表了定向流动的一个信号(离散或连续)之间的传递函数(箱). 当系统被看作是一套箱子沟通讯息或信号,功能范式掌握. 使用功能模块,发现在控制工程(Ogata1970; Dorf1986)(连续信号)以及排队网络计算机系统模型设计(麦德1987). 有些功能制度的重点是不是这么多的功能,但更多的变数. 这种模式包括的信号流图,并求出模型(Jacquez1985),及系统动力学(罗伯茨,安德森, Deal,Garet,Shaffer1983). (4) Constraint Models(4)约束模式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.有两种类型的约束模式:等式和图型. 约束模式模式下的平衡(或约束),是在心脏的模型设计. 在这种情况下, 方程式往往是最好的表征的模式,因为一个方向性的做法,诸如功能建模是不够的. 等式系统包括不同的模式,赋与时滞微分方程. 图形模式,如债券图(Breedveld1986年; Karnopp,Margolis, 和罗森堡1990年)和电力网络图(1989年币值)也是基于约束. (5) Spatial Models(5)空间模式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. 如果一个系统在空间上分解为蜂窝自动(Wolfram1986年; Toffoli和margolus1987),伊辛系统 基于PDE解或有限元模型,随后该系统正在modeled利用空间建模技术. 空间模型是用来模拟系统非常详尽, 凡单项物理现象,是仿照离散几何体系. 空间模型是实体型或航天为本 实体的空间数据模型,重点放在了固定场所的实体动力学刊载 而空间的焦点放在如何空间变化convolving模板以上的空间,在每个时间步.PDEs空间的那里的模板定义集成方法. L-系统(Pprusinkiewicz和Lindenmeyer1990)是实体型自动力学是基于如何生物体成长超过定额 太空. (6) Multi Models(6) 多种型号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.大型模型是建立一个或多个抽象层次 每个级别的设计,使用上述任何一种更为原始模型类型. 最低程度的抽象的体制,可能会使用一种空间发展模式,而最高级别的可使用 宣示有限状态机. 中级班将经常使用功能和约束技巧. 这些模式是由其他模型被称为多式联运(Fishwick和Zeigler1992年; Fishwick1992年; Fishwick1993). 用抽象层次 我们可以切换水平在模拟和运用抽象最适合在这个时候. 这种做法给人多层次的解释,是计算效率高于模拟系统在一个层面. 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 “learning 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.)计算机仿真设计模型的一个实际或理论物理体系, 执行模型在计算机上,并分析执行输出. 仿真体现了学做,了解他们的制度,我们必须先建立一个模型,有些 那样的话,那么经营模式. 孩子们了解他们周围世界的模拟(玩具及快递)大部分的互动与其他人, 动物及物体. 计算机仿真是相等的电子这一类的角色扮演. 它有助于推动综合环境和虚拟世界. 在整个任务的仿真,有三个主要的分支领域:模型设计 模型执行和模型分析(见图. 1). 来模拟一些物理,你首先要建立一个数学模型,其中,代表实物. 模型可以采取多种形式,包括宣示,功能有限,空间或多式联运. 一多式联运含有多重整合模式各自代表一个层面的粒度的物理系统. 下一个任务,一旦模型已经制定,是执行示范一台电脑. 即 你必须建立一个计算机程序的步骤,通过的时间,同时更新状态和事件的变数在您 数学模型. 有很多方法的步骤,通过时间的认识. 你可以,比如 跨越时间使用事件调度或者你可以用小的时间增量利用时间切片. 你也可以执行(即模拟)的计划,大规模并行计算机. 这就是所谓的并行与分布仿真. 对于许多大型模型,这是唯一可行的方式得到的答案早在一个合理的时间. 仿真系统可在13多个不同层次的忠诚度. 一位读者会认为物理模型和输出. 另一个则可能认为较抽象的模型,其中产量上级,不太详细输出作为一个排队网络. 型号的设计提供了答案,在一个特定的抽象层次的更详细的模型,更详细的输出. 什么样的输出,你需要将建议采用哪种模式,你会聘用. 为例图形输出从一个物理模型产生器程序aero显示为37,239美元一双 刚性机构无花果. 2. 你可以把这个立体无需使用外部看艾滋病,不同的眼睛. (分歧,可以通过各种方式. 尽量集中于一个对象三或四英尺从贵 眼睛. 然后把这些数字与你的眼睛与物体. 你会看到三个帧, 随着帧被合并左侧的立体框架). 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 “let 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.技术,如模拟与虚拟现实技术将主导娱乐和科学前沿,并进入下一世纪. 如今的电脑价格,个人电脑的负担. 手持电脑, 你可以着手建立模型的现实,让他们松散来看看,并学习更多 对现实的模型. 虽然我们可能做今天可能是原始的标准的科幻表演等星舰 (Holodeck)和剪草机的男子,目前的计算机仿真学科将率先开展对这些最终目标. 关键的一句话是:数字化正如许多诸如走下神坛的尼葛洛庞帝的麻省理工学院媒体实验室 他最近的文字:数字化 我们要创造数字复制品一切你看你看周围 在阅读这篇文章. 当你想臆造数字世界,你会选择数字对象,采用三维, 沉浸施工工具把它们放在一起. 数字对象可能位于任何地方上网. 你会使用帮助工具(或自治区代理商)寻找建筑砌块对象为您的数码世界. 有些工作正在做分布式交互仿真是推力最先由国防部. 影响这些类型的模拟,由于深刻的思想分布仿真技术的巨大潜力,同时, 在工业和娱乐等领域. REFERENCES参考资料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