Modeling Fluid Structure Interaction

By H. Benaroya, T. Wei. 2000

189 citations recorded by the source corpus.

Subfields: Mechanical Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/8cf104b13fd944a7de791a2572ba2bd8d5fdde05

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In Mechanical Engineering

In Ocean Engineering

Citations in the corpus

Topology Optimization (2009, unknown): “Althought FSI was introduced for the aircraft industry, it is applicable in a large range of fields, for example airfoils [35] [37], engines [71], compressors [91], moving containers [56], the human blood flow system [42] [41], and the human lung system [82].”
A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems (2015, unknown): “Early applications of POD include unsteady flows and turbulence modeling [73, 105, 205], and unsteady fluid-structure interaction [75].”
Using Automatic Differentiation to Create a Nonlinear Reduced-Order-Model Aerodynamic Solver (2010, background): “Vol. 48, No. 1, January 2010 19 In the present case, we are using a nonlinear frequency-domain harmonic balance (HB) CFD solution method created at Duke University (Hall et al. [10] and Thomas et al. [11]).”
Reduced Basis Approximation and A Posteriori Error Estimation for Parametrized Partial Differential Equations (2007, background): “The Proper Orthogonal Decomposition (POD) or Karhunen-Loève (KL) [72, 80] approach to sampling [75, 77, 97, 142] is immensely popular in a variety of contexts — turbulent flows [85], fluid-structure interaction [46], non-linear structural mechanics [73], turbo-machinery flows [156] — most notably in”
Aeroelastic and Aerothermoelastic Analysis in Hypersonic Flow: Past, Present, and Future (2011, methodology): “Typical approaches for constructing aerodynamic ROMs are proper orthogonal decomposition (POD) [81–84], Volterra series [82,85], and surrogates [71,86–92].”
Numerical Methods for Fluid-Structure Interaction — A Review (2012, background): “FSI problems play prominent roles in many scientific and engineering fields, yet a comprehensive study of such problems remains a challenge due to their strong nonlinearity and multidisciplinary nature (Chakrabarti 2005, Dowell and Hall 2001, Morand and Ohayon 1995).”
Balanced Model Reduction via the Proper Orthogonal Decomposition (2002, background): “( 20 ) and (21) when the systems are large, by the use of approximate subspace iteration, 2 least-squares approximation,3 and Krylovsubspacemethods(seeRefs.4and5),toobtainlow-rank approximationsofthegrammians.However,allofthesetechniquesare expensive for very high-order systems and have only been de”