Detecting behaviours within HLA distributed simulations with added analysis components

2012 ◽  
Author(s):  
Patrice Carle ◽  
C. Choppy ◽  
R. Kervarc
Keyword(s):  
Distributed Simulations

Colored Ants for Distributed Simulations

2004 ◽  
pp. 326-333 ◽  
Author(s):  
Cyrille Bertelle ◽  
Antoine Dutot ◽  
Frédéric Guinand ◽  
Damien Olivier
Keyword(s):  
Distributed Simulations

A Statistical Approach to Causality Analysis in a Distributed Design Framework

2004 ◽  
Author(s):  
Jaehyun Kim ◽  
David Wallace
Keyword(s):  
Collaborative Design ◽  
Linear Regression Analysis ◽  
Simulation Models ◽  
Design Parameters ◽  
Causality Analysis ◽  
Web Based ◽  
Distributed Object ◽  
Distributed Simulations ◽  
Variable Sensitivity ◽  
Definition Of

Numerous collaborative design tools have been developed to accelerate the product development, and recently environments for building distributed simulations have been proposed. For example, a simulation framework called DOME (Distributed Object-oriented Modeling and Evaluation) has been developed in MIT CADLAB. DOME is unique in its decentralized structure that allows heterogeneous simulations to be stitched together while allowing proprietary information an simulation models to remain secure with each participant. While such an approach offers many advantages, it also hides causality and sensitivity information, making it difficult for designers to understand problem structure and verify solutions. The purpose of this research is to analyze the relationships between design parameters (causality) and the strength of the relationships (sensitivity) in decentralized web-based design simulation. Algorithms and implementations for the causality and sensitivity analysis are introduced. Causality is determined using Granger’s definition of causality, which is to distinguish causation from association using conditional variance of the suspected output variable. Sensitivity is estimated by linear regression analysis and a perturbation method, which transfers the problem into a frequency domain by generating periodic perturbations. Varying Internet latency and disturbances are problematic issues with these methods. Thus, new algorithms are developed and tested to overcome these problems.

Computational Steering of Interactive Material Flow Simulations

2008 ◽  
Author(s):  
Stefan Lietsch ◽  
Christoph Laroque ◽  
Henning Zabel
Keyword(s):  
Fluid Dynamics ◽  
Molecular Dynamics ◽  
Material Flow ◽  
High Performance ◽  
Flow Simulation ◽  
Computational Steering ◽  
Flow Simulations ◽  
Distributed Simulations ◽  
Computational Fluid Dynamics Cfd ◽  
Performance Computing

In this paper we present the integration of computational steering techniques into the interactive material flow simulation d3FACT insight. This kind of simulation differs from traditional, long running High Performance Computing (HPC) simulations such as Computational Fluid Dynamics (CFD) or Molecular Dynamics in many aspects. One very important aspect is that these simulations run in (soft) real-time, thus the corresponding visualization needs to be updated after every step of the simulation. In turn, this allows to let changes, made through the visualization, impact the actual simulation and again, to see the effects in visualization. To allow this kind of control over the simulation and to further provide a flexible basis to integrate several instances of simulation, visualization and steering components, we used and enhanced a self-developed computational steering platform, which fits best for the needs of highly interactive and distributed simulations. Thereby we are able to realize multi-user and comparative scenarios which were not possible in this field of simulations before.

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