Publication

Fluid-structure interaction in straight pipelines: Friction coupling mechanisms

Anton Schleiss, Pedro Filipe De Almeida Manso, David Ferràs Segura
2016
Journal Articles

Abstract

The present paper approaches fluid-structure interaction by means of a 4-equation model. Experimental data collected from a straight copper pipe-rig lying directly on the lab floor is used for the model validation in terms of wave shape, timing and damping. The main focus lies on the friction coupling modelling considering skin and dry friction. For skin friction three approaches are analysed: quasi-steady, Brunone’s and Trikha’s unsteady friction. For dry friction Coulomb’s model is added in the beam momentum conservation equation. Results present a good fitting between experimental and numerical data, showing the dissipative effect of dry friction phenomenon which complement that of skin friction, specially in the short term simulation.

Official source

https://infoscience.epfl.ch/entities/publication/1abdd7f2-a872-43a9-bbc3-39760c515a05

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Anton Schleiss, Pedro Filipe De Almeida Manso, David Ferràs Segura
2016
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/1abdd7f2-a872-43a9-bbc3-39760c515a05

About this result

Related concepts (16)

Friction

Friction is the force resisting the relative motion of solid surfaces, fluid layers, and material elements sliding against each other. There are several types of friction: Dry friction is a force that opposes the relative lateral motion of two solid surfaces in contact. Dry friction is subdivided into static friction ("stiction") between non-moving surfaces, and kinetic friction between moving surfaces. With the exception of atomic or molecular friction, dry friction generally arises from the interaction of surface features, known as asperities (see Figure 1).

Statistical model validation

In statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model. To combat this, model validation is used to test whether a statistical model can hold up to permutations in the data.

Cross-validation (statistics)

Cross-validation, sometimes called rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis will generalize to an independent data set. Cross-validation is a resampling method that uses different portions of the data to test and train a model on different iterations. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice.

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