Co-simulation method for solver coupling with algebraic constraints incorporating relaxation techniques

Schweizer, Bernhard; Lu, Daixing; Li, Pu

doi:10.1007/s11044-015-9464-9

Cited by 31 publications

(23 citation statements)

References 29 publications

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“…by rigid joints). In this case, reaction forces/torques are used to describe the interaction between the subsystems . Secondly, the subsystems may be coupled by constitutive laws (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Implicit co‐simulation methods: Stability and convergence analysis for solver coupling approaches with algebraic constraints

Schweizer¹,

Li²,

Lu³

2015

Z Angew Math Mech

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The analysis of the numerical stability of co‐simulation methods with algebraic constraints is subject of this manuscript. Three different implicit coupling schemes are investigated. The first method is based on the well‐known Baumgarte stabilization technique. Basis of the second coupling method is a weighted multiplier approach. Within the third method, a classical projection technique is applied. The three methods are discussed for different approximation orders. Concerning the decomposition of the overall system into subsystems, we consider all three possible approaches, i.e. force/force‐, force/displacement‐ and displacement/displacement‐decomposition. The stability analysis of co‐simulation methods with algebraic constraints is inherently related to the definition of a test model. Bearing in mind the stability definition for numerical time integration schemes, i.e. Dahlquist's stability theory based on the linear single‐mass oscillator, a linear two‐mass oscillator is used here for analyzing the stability of co‐simulation methods. The two‐mass co‐simulation test model may be regarded as two Dahlquist equations, coupled by an algebraic constraint equation. By discretizing the co‐simulation test model with a linear co‐simulation approach, a linear system of recurrence equations is obtained. The stability of the recurrence system, which reflects the stability of the underlying coupling method, can simply be determined by an eigenvalue analysis.

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“…by rigid joints). In this case, reaction forces/torques are used to describe the interaction between the subsystems . Secondly, the subsystems may be coupled by constitutive laws (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…N+1 ) T collects the predicted coupling variables at the macro-time pointT N+1 . r Corrected coupling variables, which fulfill the coupling conditions at the macro-time pointT N+1 , can be derived by calculating the roots of the Eqs (41). and(42) …”

mentioning

confidence: 99%

Implicit co‐simulation methods: Stability and convergence analysis for solver coupling approaches with algebraic constraints

Schweizer¹,

Li²,

Lu³

2015

Z Angew Math Mech

Self Cite

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“…This is performance consuming and can only ensure stability in the observed working points. More sophisticated solutions include adaptive communication step-size or relaxation techniques (Schweizer et al, 2016). Such methods typically rely on rollback mechanisms, which are often not available (state serialization in FMUs is optional).…”

Section: Numerically Stable Co-simulationmentioning

confidence: 99%

OMSimulator - Integrated FMI and TLM-based Co-simulation with Composite Model Editing and SSP

Ochel

Braun

Thiele

et al. 2019

Linköping Electronic Conference Proceedings

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OMSimulator is an FMI-based co-simulation tool and recent addition to the OpenModelica tool suite. It supports large-scale simulation and virtual prototyping using models from multiple sources utilizing the FMI standard. It is integrated into OpenModelica but also available stand-alone, i.e., without dependencies to Modelicaspecific models or technology. OMSimulator provides an industrial-strength open-source FMI-based modelling and simulation tool. Input/output ports of FMUs can be connected, ports can be grouped to buses, FMUs can be parameterized and composed, and composite models can be exported according to the (preliminary) SSP (System Structure and Parameterization) standard. Efficient FMIbased simulation is provided for both model-exchange and co-simulation. TLM-based tool connection is provided for a range of applications, e.g., Adams, Simulink, Beast, Dymola, and OpenModelica. Moreover, optional TLM (Transmission Line Modelling) domain-specific connectors are also supported, providing additional numerical stability to co-simulation. An external API is available for use from other tools and scripting languages such as Python and Lua. The paper gives an overview of the tool functionality, compares with related work, and presents experience from industrial usage.

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“…This means that the coupling will involve a force (computed or not in each subsystem) applied on both subsystems. Other co-simulation schemes exists such as the constraints coupling [12,13,14] but they involve algebraic equations that require specific time-integration schemes. Similar applied-force studies have been undertaken by Antunes et al [15].…”

Section: Split Locationsmentioning

confidence: 99%

A Vehicle/Track Co-Simulation Model Using Easydyn

Olivier¹,

Verlinden²,

Kouroussis³

2019

Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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In the railway domain, studies have been undertaken on the attenuation of vibrations transmitted to the vehicle in order to improve the comfort of the passengers. However, a slight variation in the stiffness and damping characteristics of the train constitutive parts can considerably change the amount of energy transmitted to the soil in terms of vibrations. To predict those ground-borne vibrations generated by the vehicle moving along the track that could affect or disturb the surrounding environment, a relevant option would be to build a numerical model that simulates the passage of a vehicle on a track by coupling a multibody modeling of the train with a finite element modeling of the soil using co-simulation techniques. However the location where the model has to be split remains uncertain and then the border between the multibody and the finite element parts must be determined. The aim of this paper is to emphasize the possibility to perform co-simulation between two or more subsystems using an in-house C++ library package called EasyDyn. Using its co-simulation capabilities, the recoupling of a vehicle, that can be modeled using the minimal coordinates approach in multibody systems and a track modeled using a finite element representation of the rail and sleepers, will be discussed. 4128 COMPDYN 2019 7 th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering M. Papadrakakis, M. Fragiadakis (eds.

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Co-simulation method for solver coupling with algebraic constraints incorporating relaxation techniques

Cited by 31 publications

References 29 publications

Implicit co‐simulation methods: Stability and convergence analysis for solver coupling approaches with algebraic constraints

Implicit co‐simulation methods: Stability and convergence analysis for solver coupling approaches with algebraic constraints

OMSimulator - Integrated FMI and TLM-based Co-simulation with Composite Model Editing and SSP

A Vehicle/Track Co-Simulation Model Using Easydyn

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