Interface Jacobian‐based Co‐Simulation

Here, we study the flow of energy between coupled simulators in a co-simulation environment using the concept of power bonds. We introduce energy residuals which are a direct expression of the coupling errors and hence the accuracy of co-simulation results. We propose a novel EnergyConservation-based Co-Simulation method (ECCO) for adaptive macro step size control to improve accuracy and efficiency. In contrast to most other co-simulation algorithms, this method is noniterative and only requires knowledge of the current coupling data. Consequently, it allows for significant speed ups and the protection of sensitive information contained within simulator models. A quarter car model with linear and nonlinear damping serves as a co-simulation benchmark and verifies the capabilities of the energy residual concept: Reductions in the errors of up to 93 % are achieved at no additional computational cost.

show abstract

“…(13). This is true for any macro or micro step size, and irrespective of the simulator implementations.…”

Section: Predictor/corrector Error Estimatormentioning

confidence: 85%

“…Note that Eqs. (13) are exact, irrespective of macro or micro step sizes, and irrespective of the simulator implementations. The suitability of energy residuals as energy-conservation-based error estimators is exemplified in Fig.…”

Section: B Error Estimation Based On Energy Conservationmentioning

confidence: 98%

Energy conservation and power bonds in co-simulations: non-iterative adaptive step size control and error estimation

Sadjina

Kyllingstad

Skjong

et al. 2016

Engineering with Computers

View full text Add to dashboard Cite

show abstract

“…Co-simulation is a prominent method to solve multi-physic problems. Such simulations combine well-established and specialized simulation tools for different fields [23]. In the context of the GEWISS project a cosimulation is distinguished by a distributed simulation as well as a distributed modeling (defined by the usage of different modeling tools).…”

Section: B Simulation Requirementsmentioning

confidence: 99%

Simulation as a Service: A Design Approach for large-scale Energy Network Simulations

Preisler

Dethlefs

Renz

2015

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

Abstract-In the ongoing GEWISS project it is planned to implement a geographical heat information and simulation system. It shall provide a planning and simulation tool for the interlinking of urban development and district heating network development to support the political decision making process in the City of Hamburg. The system shall combine macroscopic and microscopic simulations to a co-simulation system. The simulation as a service approach is presented as a looselycoupled scalable solution to realize large-scale energy network simulations. It is based on cloud computing technologies for the optimal utilization of computing resources in heterogeneous simulation-infrastructures. This approach can be used to realize simulation systems integrating Multi-Agent System (MAS) based simulations and other simulation technologies. For practical evaluation, two implementation approaches based on a MAS platform as a service-oriented solution will be presented and compared to an approach involving standard web-service technologies.

show abstract

“…Co-simulation is a technology which can solve the multi-physics simulation integration [11]. It means a particular case of simulation scenario which there are at least two simulators solve coupled-algebraic equations and exchange the data with each other during simulation [12].…”

Section: Co-simulationmentioning

confidence: 99%

An Investigation of Model-Based Design Framework for Aero-Engine Control Systems

Chen

Wang

et al. 2015

Proceedings of the 2015 Chinese Intelligent Systems Conference

View full text Add to dashboard Cite

Abstract:In the whole aero-engine design phase, modeling and simulation technologies have been widely used for supporting the conceptual design and performance design. Due to the increasing complexity of aero-engine systems, there are however new challenges in the areas of quality management and process optimization. In particular, the integrations of various domain physical models for early system quality assessment are becoming a challenging area for the reason of quality management and engineering efficiency. In this paper, we present the initial concepts of a framework based on formal system models for allowing automated management of simulation services in the development of aero-engine systems. We exploit in particular EAST-ADL as the framework for system modeling, which captures the design and implementation of target systems, including the related requirements, constraints, verification and validation cases, etc. With the specification of verification and validation cases as inputs, an additional co-simulation service will provide the support for an automated configuration and execution of simulation tools. Currently, the co-simulation service is specified and managed based on SysML.

show abstract

Interface Jacobian‐based Co‐Simulation

Cited by 72 publications

References 12 publications

Energy conservation and power bonds in co-simulations: non-iterative adaptive step size control and error estimation

Energy conservation and power bonds in co-simulations: non-iterative adaptive step size control and error estimation

Simulation as a Service: A Design Approach for large-scale Energy Network Simulations

An Investigation of Model-Based Design Framework for Aero-Engine Control Systems

Contact Info

Product

Resources

About