Simulation Practice and Theory最新文献

In a few short years, Web-Based Simulation has exhibited explosive growth in the simulation research community. This paper which grew out of a panel discussion at the 2000 WEBSIM Conference, briefly reviews the development of this research area and considers future opportunities, both on the research and commercial sides. On the research side, the area is maturing, but still quite active. Efforts to expanded Web-Based Simulation to include new capabilities beyond those found in conventional simulation technology or provide interoperation with other information processing technology are particularly promising. On the commercial side, a critical mass of research knowledge is now available. However, some catalyst is needed to produce any substantial movement of simulation vendors toward Web-Based Simulation. This could happen quickly under a couple of scenarios: A small simulation vendor focused on Web-Based Simulation could begin to claim significant market share. Alternatively, the development of a “killer-app” to demonstrate a clear advantage to Web-Based Simulation could make this shift happen very quickly.

The web has grown tremendously over the past decade – with applications in education, marketing, financial services, and supply chain management. Web technology also has a significant impact on computer simulation. Most of the effort in web-based simulation is aimed at modeling, particularly at building simulation languages and at creating model libraries that can be assembled and executed over the web. This paper focuses on efficiency of simulation experimentation for optimization. We introduce a framework for combining the statistical efficiency of simulation optimization techniques with the effectiveness of parallel execution algorithms. In particular, a novel simulation sampling procedure, the Optimal Computing Budget Allocation (OCBA) algorithm, is implemented in a web-based environment for low-cost parallel and distributed simulation experimentation. A prototype implementation with some experimental results is presented to show the viability of web-enabled simulation environments.

A new runtime simulation-model compiler quickly reads, compiles, and immediately solves vector differential equations and difference equations as well as scalar equations for dynamic-system models. Vector assignments compactly model nonlinear as well as linear matrix/vector relations for many problems in physics, control systems, neural networks, and fuzzy logic. The key feature is that the new vector differential-equation solver can replicate a dynamic-system model many times and then simulates hundreds of such models in a single simulation run, e.g. for Monte-Carlo studies. Also, partial differential equations (e.g. for a heat exchanger) can be solved together with ordinary differential equations. Portable C code runs on UNIX or LINUX workstations. A fast machine-language version for personal computers (Windows 98 and NT) directly utilizes the Pentium floating-point hardware stack, which is automatically continued into memory.

The performance of parallel discrete event models is highly dependent on lookahead, particularly when a conservative algorithm is employed. Unfortunately lookahead is known to be problem-dependent, which restricts the implementations of conservative algorithms. This paper uses a simple queuing network to show how this lookahead affects performance and discusses various techniques for automatic generation of lookahead using control flow graphs (CFGs). These methods are tested on the queuing network simulation running on a CRAY T3E 1200E. Results indicate that the automatic lookahead techniques, though requiring some time to compute, perform as well as the best manually extracted lookahead injected into the parallel program.

The development of efficient parallel discrete event simulators is hampered by the large number of interrelated factors affecting performance. This problem is made more difficult by the lack of scalable representative models that can be used to analyze optimizations and isolate bottlenecks. This paper proposes a performance and scalability analysis framework (PSAF) for parallel discrete event simulators. PSAF is built on a platform-independent Workload Specification Language (WSL). WSL is a language that represents simulation models using a set of fundamental performance-critical parameters. For each simulator under study, a WSL translator generates synthetic platform-specific simulation models that conform to the performance and scalability characteristics specified by the WSL description. Moreover, sets of portable simulation models that explore the effects of the different parameters, individually or collectively, on the execution performance can easily be constructed using the Synthetic Workload Generator (SWG). The SWG automatically generates simulation workloads with different performance properties. In addition, PSAF supports the seamless integration of real simulation models into the workload specification. Thus, a benchmark with both real and synthetically generated models can be built allowing for realistic and thorough exploration of the performance space. The utility of PSAF in determining the boundaries of performance and scalability of simulation environments and models is demonstrated.

Present simulation languages provide the modeler with powerful tools that facilitate the building of discrete-event simulation models. These models can largely be built by using high-level modules containing a lot of built-in functionality. Although such languages greatly reduce the amount of work to build an implementation model, the modeler often has the feeling that he is reinventing the wheel again and again. Perhaps the model he is about to design and implement already exists, or perhaps some model exists that sufficiently resembles the model about to be designed. All this would make it worthwhile to store existing models in a database for later use. In this respect, two aspects are of major interest. Firstly, how can implementation models be stored in a database and how can a modeler retrieve a specific model from such a database? A second theme is closely related to this. If the specified model is not present in the database – and this is expected to be true in most cases – would it then be possible to select a model that, in some sense, is similar to the model that the modeler had specified? In this paper, the feasibility and usefulness of the proposed approach is investigated with a focus on Arena models.

We present a method for translating the synchronisation behaviour of a process oriented discrete event simulation language into a process algebra. Such translations serve two purposes. The first exploits the formal structure of the target process algebraic representations to enable proofs of such properties of the source system as deadlock freedom, safety, fairness and liveness which can be very difficult to establish by simulation experiment. The second exploits the denotational semantics to better understand the language constructs as abstract entities and to facilitate reasoning about simulation models. Here we give the intuition and the basic translation mechanisms using a variety of the Demos simulation language and the CCS and SCCS process algebras. The translations have been automated as SML programs and produce CWB compatible input allowing the automated checking of formal system properties.

This paper describes the development of natural climatic conditions in a closed loop full-scale automotive wind tunnel. The tunnel simulates wind, different rainfalls, a range of air temperature as well as several road conditions. It generates, under controlled heat loading, wind speeds of up to 50 km h with different approach boundary conditions, rainfalls from drizzle to cloudburst, controlled air temperature over the range of 30–20°C below zero and road inclines up to 15° in any direction. The design and optimization process of the tunnel functions is outlined and examples of its use in vehicle development are given. The need to comply with the standardised recommended practice requirements and a compact design are important features of the tunnel. The tunnel provides an important test bed for close scrutiny of the relationship between rainwater ingress, vehicle speed, road condition, heat loading and vehicle geometry. The tunnel can also be used to study vehicle thermal management, vehicle thermal comfort, engine cold starting, and wipers efficiency in severe cold weather. Computational fluid dynamic (CFD) simulation is used to optimize and assess the performance of a number of key tunnel components. To validate the CFD developed model, the resulting flow field around a bluff body placed on the tunnel is closely scrutinized and verified against well-established and published data. Moreover, the numerical prediction is experimentally validated using laser sheet visualisation (LSV). The resulting tunnel is approximately 9.5 m long, 9.5 m high and 3 m wide.