Distributed Mechanical System Simulation Based on a General “Gluing Algorithm”

2003 ◽  
Author(s):  
Jinzhong Wang ◽  
Zheng-Dong Ma ◽  
Gregory M. Hulbert
Keyword(s):  
Distributed Simulation ◽  
Model Description ◽  
Design Problems ◽  
New Techniques ◽  
Model And Simulation ◽  
Engineering Design Problems ◽  
Simulation Based ◽  
Distributed Simulations ◽  
Gluing Algorithm ◽  
Model Database

Three key concepts are presented in this paper, which comprise the foundation of a distributed simulation platform for design and virtual prototyping of general mechanical systems that have their subsystems distributed amongst dispersed development units in multi-layered supply chains. First, a new gluing algorithm, denoted as the T-T method, is developed, which enables distributed simulations (both the component model and simulation of the component) to be coupled while maintaining the independence of the separate component simulations. Second, a general and efficient model description for simulation is defined using XML. Each model is described with an XML file and stored in model database. A complete model then can be assembled based on these model descriptions. Simulation of a model is started simply by sending the model description to a simulation server. Third, a logical distributed architecture is laid out that can be implemented with one of the existing technologies for distributed computing. Interfaces between different network components have been standardized to enable extensibility of the architecture. These concepts have been incorporated into a prototype distributed simulation system that demonstrates the potential of the new techniques for solving real engineering design problems.

A Distributed Mechanical System Simulation Platform Based on a “Gluing Algorithm”

2005 ◽  
Vol 5 (1) ◽  
pp. 71-76 ◽  
Author(s):  
Jinzhong Wang ◽  
Zheng-Dong Ma ◽  
Gregory M. Hulbert
Keyword(s):  
Distributed Simulation ◽  
Model Description ◽  
Simulation Platform ◽  
Design Problems ◽  
Web Based ◽  
Engineering Design Problems ◽  
Distributed Simulations ◽  
Gluing Algorithm ◽  
Model Database ◽  
Component Models

Three key concepts are presented in this paper, which comprise the foundation of a distributed simulation platform for design and virtual prototyping of general mechanical systems that have their subsystems distributed amongst dispersed development units in multilayered supply chains. First, a general and efficient model description for simulation is defined using XML. Each model is described with an XML file and stored in model database. A complete model can then be assembled based on these model descriptions. Simulation of a model is started simply by sending the model description to a simulation server and running it through a web-based graphics user interface. Second, a new gluing algorithm, denoted as the T-T method, is developed, which enables distributed simulations (both the component models and simulation of the components) to be coupled while maintaining the independence of the separate component simulations. Third, a logical distributed simulation architecture is laid out that can be implemented with one of the existing technologies for distributed computing. Interfaces between different network components have been standardized to enable extensibility of the architecture. These concepts have been incorporated into a prototype web-based distributed simulation system that demonstrates the potential of the new techniques for solving real engineering design problems.

Standards, Codes of Practice and Expert Systems

1988 ◽  
Vol 21 (1) ◽  
pp. 5-9 ◽  
Author(s):  
E G McCluskey ◽  
S Thompson ◽  
D M G McSherry
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Engineering Design ◽  
Performance Criteria ◽  
Design Problems ◽  
Codes Of Practice ◽  
Engineering Design Problems ◽  
And Performance

Many engineering design problems require reference to standards or codes of practice to ensure that acceptable safety and performance criteria are met. Extracting relevant data from such documents can, however, be a problem for the unfamiliar user. The use of expert systems to guide the retrieval of information from standards and codes of practice is proposed as a means of alleviating this problem. Following a brief introduction to expert system techniques, a tool developed by the authors for building expert system guides to standards and codes of practice is described. The steps involved in encoding the knowledge contained in an arbitrarily chosen standard are illustrated. Finally, a typical consultation illustrates the use of the expert system guide to the standard.

scholarly journals A Multimodal Smart Quantum Particle Swarm Optimization for Electromagnetic Design Optimization Problems

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4613
Author(s):  
Shah Fahad ◽  
Shiyou Yang ◽  
Rehan Ali Khan ◽  
Shafiullah Khan ◽  
Shoaib Ahmed Khan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Continuous Variables ◽  
Design Problems ◽  
Swarm Optimization ◽  
Electromagnetic Design ◽  
Quantum Particle Swarm Optimization ◽  
Engineering Design Problems

Electromagnetic design problems are generally formulated as nonlinear programming problems with multimodal objective functions and continuous variables. These can be solved by either a deterministic or a stochastic optimization algorithm. Recently, many intelligent optimization algorithms, such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC), have been proposed and applied to electromagnetic design problems with promising results. However, there is no universal algorithm which can be used to solve engineering design problems. In this paper, a stochastic smart quantum particle swarm optimization (SQPSO) algorithm is introduced. In the proposed SQPSO, to tackle the premature convergence problem in order to improve the global search ability, a smart particle and a memory archive are adopted instead of mutation operations. Moreover, to enhance the exploration searching ability, a new set of random numbers and control parameters are introduced. Experimental results validate that the adopted control policy in this work can achieve a good balance between exploration and exploitation. Finally, the SQPSO has been tested on well-known optimization benchmark functions and implemented on the electromagnetic TEAM workshop problem 22. The simulation result shows an outstanding capability of the proposed algorithm in speeding convergence compared to other algorithms.

A Robust Error-Pursuing Sequential Sampling Approach for Global Metamodeling Based on Voronoi Diagram and Cross Validation

2014 ◽  
Vol 136 (7) ◽  
Author(s):  
Shengli Xu ◽  
Haitao Liu ◽  
Xiaofang Wang ◽  
Xiaomo Jiang
Keyword(s):  
Engineering Design ◽  
Voronoi Diagram ◽  
Cross Validation ◽  
Sequential Sampling ◽  
Voronoi Cell ◽  
Sensitive Region ◽  
Engineering Design Problems ◽  
Simulation Based ◽  
Global Metamodeling ◽  
Sampling Approach

Surrogate models are widely used in simulation-based engineering design and optimization to save the computing cost. The choice of sampling approach has a great impact on the metamodel accuracy. This article presents a robust error-pursuing sequential sampling approach called cross-validation (CV)-Voronoi for global metamodeling. During the sampling process, CV-Voronoi uses Voronoi diagram to partition the design space into a set of Voronoi cells according to existing points. The error behavior of each cell is estimated by leave-one-out (LOO) cross-validation approach. Large prediction error indicates that the constructed metamodel in this Voronoi cell has not been fitted well and, thus, new points should be sampled in this cell. In order to rapidly improve the metamodel accuracy, the proposed approach samples a Voronoi cell with the largest error value, which is marked as a sensitive region. The sampling approach exploits locally by the identification of sensitive region and explores globally with the shift of sensitive region. Comparative results with several sequential sampling approaches have demonstrated that the proposed approach is simple, robust, and achieves the desired metamodel accuracy with fewer samples, that is needed in simulation-based engineering design problems.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

scholarly journals Lévy-Flight Moth-Flame Algorithm for Function Optimization and Engineering Design Problems

2016 ◽  
Vol 2016 ◽  
pp. 1-22 ◽  
Author(s):  
Zhiming Li ◽  
Yongquan Zhou ◽  
Sen Zhang ◽  
Junmin Song
Keyword(s):  
Engineering Design ◽  
Function Optimization ◽  
Superior Performance ◽  
Local Optimum ◽  
Lévy Flight ◽  
Design Problems ◽  
Levy Flight ◽  
Spiral Path ◽  
Straight Line ◽  
Engineering Design Problems

The moth-flame optimization (MFO) algorithm is a novel nature-inspired heuristic paradigm. The main inspiration of this algorithm is the navigation method of moths in nature called transverse orientation. Moths fly in night by maintaining a fixed angle with respect to the moon, a very effective mechanism for travelling in a straight line for long distances. However, these fancy insects are trapped in a spiral path around artificial lights. Aiming at the phenomenon that MFO algorithm has slow convergence and low precision, an improved version of MFO algorithm based on Lévy-flight strategy, which is named as LMFO, is proposed. Lévy-flight can increase the diversity of the population against premature convergence and make the algorithm jump out of local optimum more effectively. This approach is helpful to obtain a better trade-off between exploration and exploitation ability of MFO, thus, which can make LMFO faster and more robust than MFO. And a comparison with ABC, BA, GGSA, DA, PSOGSA, and MFO on 19 unconstrained benchmark functions and 2 constrained engineering design problems is tested. These results demonstrate the superior performance of LMFO.

scholarly journals Distributed Simulation as a modelling tool for the development of a simulation-based training programme for cardiovascular specialties

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Tanika Kelay ◽  
Kah Leong Chan ◽  
Emmanuel Ako ◽  
Mohammad Yasin ◽  
Charis Costopoulos ◽  
...  
Keyword(s):  
Distributed Simulation ◽  
Training Programme ◽  
Simulation Based
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