Implicit Partitioned Fluid-Structure Interaction Coupling

Schäfer, Michael; Yigit, Saim; Heck, Marcus

doi:10.1115/pvp2006-icpvt-11-93184

Cited by 7 publications

(2 citation statements)

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“…Co‐simulation has advantageously been applied in the field of vehicle dynamics, see for instance Refs. [] or in context with fluid/structure interaction problems . For the coupled simulation of multibody and finite‐element systems, co‐simulation has also been successfully applied, see Refs.…”

Section: Introductionmentioning

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

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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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Section: Introductionmentioning

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

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show abstract

“…As can be seen in Figure 2, to better describe the burr, a new term called ''burr value'' was defined by Scha¨fer. 3 It contains the burr root thickness (b r ), burr height (b h ), burr thickness (b t ) and burr root radius (r f ). However, measuring and/or estimating all these parameters to calculate the burr value is very difficult and time-consuming.…”

Section: Burr Definitions and Classificationmentioning

confidence: 99%

Milling burr formation, modeling and control: A review

Niknam

Songmené

2014

Proceedings of the Institution of Mechanical Engineers, Part B:

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Because of global competition, manufacturing industries today must provide high-quality products on time to remain competitive. High-quality mechanical parts include those with better surface finish and texture, dimension and form accuracies, reduced residual stress and burr-free. Burr formation is one of the most common and undesirable phenomenon occurring in machining operations, which reduces assembly and machined part quality. To remove burrs, a secondary operation known as deburring is required for post-processing and edge finishing operations. Since deburring is costly and considered a non-value-added process, the goal is desired to eliminate burrs or reduce the effort required to remove them. Because of non-uniform chip thickness, tool runout and complex interactive effects between cutting process parameters, milling burr formation is a very complex mechanism. Therefore, research and close attention are still needed in order to minimize and control milling burr formation. In this article, a review of burr formation and characterization is presented, along with burr formation modeling and control. An overview of factors governing milling burr formation is also presented.

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Explicit Co-simulation Approach with Improved Numerical Stability

Schmoll

et al. 2019

IUTAM Symposium on Solver-Coupling and Co-Simulation

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Implicit Partitioned Fluid-Structure Interaction Coupling

Cited by 7 publications

References 0 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

Milling burr formation, modeling and control: A review

Explicit Co-simulation Approach with Improved Numerical Stability

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