scholarly journals A Framework for Early and Approximate Uncertainty Quantification of Large System Simulation Models

2015 ◽  
Author(s):  
Magnus Eek ◽  
Johan Karlén ◽  
Johan Ölvander
Keyword(s):  
Uncertainty Quantification ◽  
System Simulation ◽  
Simulation Models ◽  
Large System

Construction of Multi-Domain System Simulation Model for Trade Studies in System Design Considering Multiple Scenes

2019 ◽  
Author(s):  
Kazuya Oizumi ◽  
Keita Ishida ◽  
Yoshihiro Uchibori ◽  
Kazuhiro Aoyama
Keyword(s):  
Simulation Model ◽  
System Design ◽  
Systems Engineering ◽  
System Simulation ◽  
Cognitive Model ◽  
Simulation Models ◽  
Modelling Method ◽  
Variable Transmission ◽  
Physical Phenomena ◽  
Model Based Systems Engineering

Abstract As a product is sold globally, usages of the product have much wider variety. Thus, a product needs to be designed considering multiple scenes. To certify that the product performs properly in any scene, industries started to apply Model Based Systems Engineering (MBSE). Whereas multi-domain system simulations are regarded as a prominent approach for the system design of a product, construction of model depends on knowledge and sense modelers. This paper proposes a modelling method to construct appropriate multi-domain system simulation models while reducing dependencies to senses of modelers. The proposed method comprises two parts. First, significant tradeoffs to be studied by the simulation are specified. Second, features of simulation models are deliberated for specified tradeoffs. To specify significant tradeoffs, product and scenes where the product is used are integrated into a model. Further, to deliberate features of simulation model, cognitive model of physical phenomena in a product is employed as well. The proposed method was applied to the development of continuously variable transmission to verify its validity.

scholarly journals Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling

2013 ◽  
Vol 28 (4) ◽  
pp. 616-640 ◽  
Author(s):  
Roman Schefzik ◽  
Thordis L. Thorarinsdottir ◽  
Tilmann Gneiting
Keyword(s):  
Uncertainty Quantification ◽  
Simulation Models ◽  
Complex Simulation

Production and representation of computer system simulation models

1976 ◽  
Vol 7 (4) ◽  
pp. 205-212
Author(s):  
Giuseppe G. Iazeolla ◽  
Enrico Martinelli ◽  
Orazio Tedone
Keyword(s):  
Computer System ◽  
System Simulation ◽  
Simulation Models

scholarly journals Service-Oriented Model Encapsulation and Selection Method for Complex System Simulation Based on Cloud Architecture

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 891
Author(s):  
Xiong ◽  
Zhu ◽  
Yao ◽  
Tang ◽  
Xiao
Keyword(s):  
Complex System ◽  
System Simulation ◽  
Simulation Models ◽  
Selection Method ◽  
Semantic Search ◽  
Distributed Scheduling ◽  
Parallel Operation ◽  
Optimal Service ◽  
Service Oriented ◽  
Search And Selection

With the rise in cloud computing architecture, the development of service-oriented simulation models has gradually become a prominent topic in the field of complex system simulation. In order to support the distributed sharing of the simulation models with large computational requirements and to select the optimal service model to construct complex system simulation applications, this paper proposes a service-oriented model encapsulation and selection method. This method encapsulates models into shared simulation services, supports the distributed scheduling of model services in the network, and designs a semantic search framework which can support users in searching models according to model correlation. An optimization selection algorithm based on quality of service (QoS) is proposed to support users in customizing the weights of QoS indices and obtaining the ordered candidate model set by weighted comparison. The experimental results showed that the parallel operation of service models can effectively improve the execution efficiency of complex system simulation applications, and the performance was increased by 19.76% compared with that of scatter distribution strategy. The QoS weighted model selection method based on semantic search can support the effective search and selection of simulation models in the cloud environment according to the user’s preferences.

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