Parallel simulation for aviation applications

Wieland, Frederick

doi:10.1109/wsc.1998.745978

Cited by 28 publications

(16 citation statements)

References 3 publications

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“…Furthermore, current data can be exploited to be fed into the simulation during runtime. Although this is not a new idea, particularly in the context of supporting decisions, for example, in (Krusche and Tolk, 2000;Wieland, 1998) the idea of "symbiotic" simulation stresses the benefit that both simulation and physical system receive by their close interaction (DAGSTUHL, 2002;Ayed et al, 2008). The simulation benefits from the data, as its predictions will be more accurate, and the simulation results can be validated, and the physical system benefits from the simulation as its operation will run in an optimized manner based on the online analysis of the simulation results.…”

Section: Simulation As Support For Decision Making In Systems Engineementioning

confidence: 99%

Agents: Agenthood, Agent Architectures, and Agent Taxonomies

Tolk

Uhrmacher

2009

Agent‐Directed Simulation and Systems Engineering

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Section: Simulation As Support For Decision Making In Systems Engineementioning

confidence: 99%

Agents: Agenthood, Agent Architectures, and Agent Taxonomies

Tolk

Uhrmacher

2009

Agent‐Directed Simulation and Systems Engineering

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“…In some, state is explicitly expressed as discrete variables changing in response to events (e.g. the DPAT model described by Wieland [21])1 in others, state is explicitly expressed as continuously-valued variables evolving smoothly through time1 and still others, such as agentbased simulations, are more focused on capturing emergent behaviors and component interactions than maintaining a definition of the system state. The different simulations may be advanced by real time, time steps, or events.…”

Section: Conceptual Questions Facing Modeling and Simulation In Air Tmentioning

confidence: 99%

Looking into the Future of Air Transportation Modeling and Simulation: A Grand Challenge

Wieland¹,

Pritchett

2007

SIMULATION

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The future of air transportation modeling and simulation represents a grand challenge for both the air transportation and the modeling and simulation communities. In addition to its size and scope, air transportation has many technical, operational, organizational, policy, security and legal aspects contributing to its complexity, yet must ensure an un-rivaled level of safety throughout any transition to next generation systems. Thus, modeling and simulation must address not only technical challenges in representing a system of this complexity, but also institutional realities that prevent full data and model sharing between the many entities involved in air transportation. We outline the attributes of a shared repository of data, models and computational tools required to meet this challenge, including the coordination and administrative processes required to manage it, and provide an example of its potential application.

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“…Asia and Taiwan, as well as the continental US (CONUS). For more detail on DPAT please see [Wieland 1998]. …”

Section: Air Traffic Control Simulationmentioning

confidence: 99%

Cloning parallel simulations

Hybinette

Fujimoto

2001

ACM Trans. Model. Comput. Simul.

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We present a cloning mechanism that enables the evaluation of multiple simulated futures. Performance of the mechanism is analyzed and evaluated experimentally on a shared memory multiprocessor. A running parallel discrete event simulation is dynamically cloned at decision points to explore different execution paths concurrently. In this way what-if and alternative scenario analysis can be performed in applications such as gaming or tactical and strategic battle management. A construct called virtual logical processes avoids repeating common computations among clones and improves efficiency. The advantages of cloning are preserved regardless of the number of clones (or execution paths). Our performance results with a commercial air traffic control simulation demonstrate that cloning can significantly reduce the time required to compute multiple alternate futures.

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Parallel simulation for aviation applications

Cited by 28 publications

References 3 publications

Agents: Agenthood, Agent Architectures, and Agent Taxonomies

Agents: Agenthood, Agent Architectures, and Agent Taxonomies

Looking into the Future of Air Transportation Modeling and Simulation: A Grand Challenge

Cloning parallel simulations

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