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

RTCONTACT: An Efficient Wheel-Rail Contact Algorithm for Real-Time Dynamic Simulations

2012 ◽  
Author(s):  
N. Bosso ◽  
A. Gugliotta ◽  
N. Zampieri
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Simulation Models ◽  
Experimental Tests ◽  
Contact Forces ◽  
Dynamic Simulations ◽  
Time Dynamic ◽  
Contact Algorithm ◽  
Complex Simulation ◽  
Precise Representation

Determination of contact forces exchanged between wheel and rail is one of the most important topics in railway dynamics. Recent studies are oriented to improve the existing contact methods in terms of computational efficiency on one side and on the other side to develop more complex and precise representation of the contact problem. This work shows some new results of the contact code developed at Politecnico di Torino identified as RTCONTACT; this code, which is an improvement of the CONPOL algorithm, is the result of long term activities, early versions were used in conjunction with MBS codes or in Matlab® environment to simulate vehicle behaviour. The code has been improved also using experimental tests performed on a scaled roller-rig. More recently the contact model was improved in order to obtain a higher computational efficiency that is a required for the use inside of a Real Time process. Benefit of a Real Time contact algorithm is the possibility to use complex simulation models in diagnostic or control systems in order to improve their performances. This work shows several comparisons of the RTCONTACT contact code respect commercial codes, standards and benchmark results.

Hider: A Methodology for Early-Stage Exploration of Design Space

1996 ◽  
Author(s):  
Sudhakar Y. Reddy
Keyword(s):  
Design Space ◽  
Optimization Problems ◽  
Early Stage ◽  
Simulation Models ◽  
Design Tool ◽  
System Level ◽  
Complex Simulation ◽  
Machine Learning Approach ◽  
Detailed Simulation ◽  
And Performance

Abstract This paper describes HIDER, a methodology that enables detailed simulation models to be used during the early stages of system design. HIDER uses a machine learning approach to form abstract models from the detailed models. The abstract models are used for multiple-objective optimization to obtain sets of non-dominated designs. The tradeoffs between design and performance attributes in the non-dominated sets are used to interactively refine the design space. A prototype design tool has been developed to assist the designer in easily forming abstract models, flexibly defining optimization problems, and interactively exploring and refining the design space. To demonstrate the practical applicability of this approach, the paper presents results from the application of HIDER to the system-level design of a wheel loader. In this demonstration, complex simulation models for cycle time evaluation and stability analysis are used together for early-stage exploration of design space.

Communicating Insights from Complex Simulation Models

1987 ◽  
Vol 18 (3) ◽  
pp. 321-343 ◽  
Author(s):  
A.M. Vennix ◽  
L.A. Geurts
Keyword(s):  
Simulation Models ◽  
Complex Simulation

The perils of tweaking: how to use macrodata to set parameters in complex simulation models

Synthese ◽  
2012 ◽  
Vol 190 (2) ◽  
pp. 203-218 ◽  
Author(s):  
Brian Epstein ◽  
Patrick Forber
Keyword(s):  
Simulation Models ◽  
Complex Simulation

scholarly journals Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

2021 ◽  
Author(s):  
Max-Arno Meyer ◽  
Lina Sauter ◽  
Christian Granrath ◽  
Hassen Hadj-Amor ◽  
Jakob Andert
Keyword(s):  
Data Exchange ◽  
Time Synchronization ◽  
Simulation Models ◽  
Simulation Platform ◽  
Automated Driving ◽  
Complex Simulation ◽  
Simulation Protocol ◽  
Environment Simulation ◽  
Cross Platform ◽  
And Performance

AbstractTo meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

scholarly journals INTEGRATES ASSESSMENT MODELS (IAMS) APPLIED TO CLIMATRE CHANGE AND ENERGY TRANSITION

10.6036/9922 ◽  
2021 ◽  
Vol 96 (3) ◽  
pp. 316-321
Author(s):  
IGNACIO DE BLAS ◽  
LUIS JAVIER MIGUEL GONZALEZ ◽  
CARLOS DE CASTRO CARRANZA
Keyword(s):  
Climate Change ◽  
Ghg Emissions ◽  
Energy Transition ◽  
Simulation Models ◽  
Intergovernmental Panel ◽  
Number Of Factors ◽  
Complex Simulation ◽  
Energy Economy ◽  
Mitigate Climate Change ◽  
Complex Relationships

The climate change that is currently occurring is due to the increase in the concentration of greenhouse gases (GHG) in the atmosphere as a result of human activity. The large number of factors and variables that directly or indirectly affect GHG emissions, as well as the multiple and complex relationships between them, makes it difficult to make decisions on the best measures to be adopted to slow down or mitigate climate change and to analyze the consequences that each decision entails. This has led to the development of complex simulation models called Integrated Assessment Models (IAMs) or Energy-Economy-Environment Models (E3 models), with a particular focus on climate change. The development and use of these models to guide policy decisions on climate change has grown very significantly in recent years, as evidenced by the reports of the Intergovernmental Panel on Climate Change (IPCC). This paper is a panoramic review of the main existing IAMs and analyzes their main characteristics. The paper focuses especially on the analysis of the limitations of the current IAMs, which should mark the future developments of these tools.

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