The paper discusses verification, validation, and accreditation of simulation models. The different approaches to deciding model validity are presented; how model verification and validation relate to the model develo...
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The paper discusses verification, validation, and accreditation of simulation models. The different approaches to deciding model validity are presented; how model verification and validation relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; a recommended procedure is presented; and accreditation is briefly discussed.
Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.
Provides an abstract of the keynote presentation and a brief professional biography of the presenter. The complete presentation was not made available for publication as part of the conference proceedings.
The nature of the emerging field of web-based simulation is examined in terms of its relationship to the fundamental aspects of simulation research and practice. The presentation, assuming a form of debate, is based o...
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The nature of the emerging field of web-based simulation is examined in terms of its relationship to the fundamental aspects of simulation research and practice. The presentation, assuming a form of debate, is based on a panel session held at the first International Conference on Web-Based Modeling and simulation, which was sponsored by the Society for computersimulation during 11-14 January 1998 in San Diego, California. While no clear "winner" is evident in this debate, the issues raised here certainly merit ongoing attention and contemplation.
We briefly review the theory of modeling and simulation and its support for constructing distributed simulations. Formal representation of simulation models can contribute to a number of aspects in the modeling and si...
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We briefly review the theory of modeling and simulation and its support for constructing distributed simulations. Formal representation of simulation models can contribute to a number of aspects in the modeling and simulation enterprise. Separation of models from simulation execution engines is a prerequisite transferring models among phases of a project as well as from project to project. The Discrete Event System Specification (DEVS) formalism, drawing on its system theoretical basis, provides a number of important properties such as hierarchical, modular composition, universality and uniqueness that can support development of simulation models and environments. A layered architecture for supporting comprehensive M&S environments is discussed that unifies the theoretical framework with implementation in distributed computational environments.
The concept of strong groups is introduced to describe the structure of simulation models. It is shown that logical processes within strong groups process at approximately the same rate and that different strong group...
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The concept of strong groups is introduced to describe the structure of simulation models. It is shown that logical processes within strong groups process at approximately the same rate and that different strong groups can progress at different rates. An algorithm based on the rates of the strong groups is presented to balance the load among the physical processors and for flow control.
The Power System Blockset (PSB) simulation tool uses the MATLAB/Simulink environment to represent common components and devices found in electrical power networks. The PSB is well suited to the simulation of medium si...
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The Power System Blockset (PSB) simulation tool uses the MATLAB/Simulink environment to represent common components and devices found in electrical power networks. The PSB is well suited to the simulation of medium size power systems and power electronics using variable or fixed step algorithms from Simulink. The PSB libraries contain basic elements as well as many ready-built sub-systems. Control systems using Simulink blocks can be naturally integrated into the power system model. The computation capabilities of MATLAB/Simulink can be advantageously exploited in post-processing of the simulation results. SPICE (simulation Program with Integrated Circuit Emphasis) can perform nonlinear DC, nonlinear transient, and linear AC analyses. In addition to the standard R,L and C elements, models for transmission lines and several semiconductor devices types are also available. In the study of power systems, PSpice is well suited for device-level modeling of small size systems: study of voltages and currents in power converters, snubber circuit design, study of transformer transients, etc. Also, PSpice performs well for system-level modeling of small size power systems (less than 30 states and 6 switches) using ideal switch models instead of detailed semiconductor models.
The Power System Blockset (PSB) is a graphic tool that allows schematics and simulation of power systems to be built in the Simulink environment. The blockset uses the MATLAB/Simulink environment to represent common c...
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The Power System Blockset (PSB) is a graphic tool that allows schematics and simulation of power systems to be built in the Simulink environment. The blockset uses the MATLAB/Simulink environment to represent common components and devices found in electrical power networks. Simulink's variable-step event-sensitive integration algorithms allow increased accuracy in zero-crossing detection of currents as compared with fixed step algorithms. One important feature of the Power System Blockset which has been introduced with version 2.0 is its ability to simulate either with continuous variable time-step integration algorithms or with a discretized system. For small and medium size systems, variable time steps algorithms are usually faster because the number of steps will be less than with a fixed-time step method. However, for large systems which contain many states or many nonlinear blocks such as power electronic switches, it is advantageous to discretize the electrical system. Both the continuous integration and fixed-time step methods are illustrated. The graphic interface of Simulink provides a user-friendly environment where the power circuit and control system are represented in the same diagram. The results are displayed while the simulation is running. The processing power of MATLAB allows the designer to perform complex post-processing on simulation results. This special technical session presents the features of the Power System Blockset and its applications in the simulation of power systems and power electronics systems.
The project investigated various aspects of parallel FDTD implementation on a workstation cluster. The computation grid was divided among nodes. For a fixed size problem, as the number of processor increases, the spee...
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The project investigated various aspects of parallel FDTD implementation on a workstation cluster. The computation grid was divided among nodes. For a fixed size problem, as the number of processor increases, the speedup saturates. This happens because each processor spends less time computing but essentially the same time communicating with its neighbors. To take advantage of the parallel algorithm, the problem size must be sufficiently large compared with the number of processors. For very large problems, we can efficiently employ a large number of processors to obtain a linear speedup. In this work, the message passing interface (MPI) parallel implementation was integrated with POSIX threads using the pthreads library. This was required because each node in the cluster was equipped with two processors. On each node, each process contained two threads that executed in parallel. As expected, for sufficiently large problems the speedup was increased by almost a factor of two when using threads.
An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource size or balance may b...
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An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource size or balance may be different across servers. One approach to resource management for this grid is to layer a global load distribution system on top of the local job management systems at each site. Unfortunately, classical load distribution policies fail on two aspects when applied to a multi-resource server grid First, simple load indices may not recognize that a resource imbalance exists at a server. Second, classical job selection policies do not actively correct such a resource-imbalanced state. We show through simulation that new policies based on resource balancing perform consistently better than the classical load distribution strategies.
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