Publication

An anisotropic adaptive finite element algorithm for transonic viscous flows around a wing

Marco Picasso, Wissam Hassan
2015
Journal Articles

Abstract

An adaptive finite element algorithm to compute transonic viscous flows around a wing is presented. The adaptive criteria is based on an anisotropic error estimator in the 115 semi-norm, justified for an advection-diffusion problem with stabilized finite elements. The mesh aspect ratio can be arbitrarily large, upper and lower bounds can be proved, the involved constants being aspect ratio independent. Based on this error estimator, an anisotropic mesh adaptation algorithm is proposed to compute transonic viscous flows around a wing. The mesh is structured around the wing, while the remaining part of the mesh is adapted according to the anisotropic error estimator. This anisotropic adaptive algorithm allows shocks and the wake to be captured accurately, while keeping the number of vertices as low as possible. (C) 2015 Elsevier Ltd. All rights reserved.

Official source

https://infoscience.epfl.ch/entities/publication/2178ad8c-7a97-4f91-87ae-88a9333e0dc3

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Marco Picasso, Wissam Hassan
2015
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/2178ad8c-7a97-4f91-87ae-88a9333e0dc3

About this result

Related concepts (29)

Potential flow

In fluid dynamics, potential flow (or ideal flow) describes the velocity field as the gradient of a scalar function: the velocity potential. As a result, a potential flow is characterized by an irrotational velocity field, which is a valid approximation for several applications. The irrotationality of a potential flow is due to the curl of the gradient of a scalar always being equal to zero. In the case of an incompressible flow the velocity potential satisfies Laplace's equation, and potential theory is applicable.

Compressible flow

Compressible flow (or gas dynamics) is the branch of fluid mechanics that deals with flows having significant changes in fluid density. While all flows are compressible, flows are usually treated as being incompressible when the Mach number (the ratio of the speed of the flow to the speed of sound) is smaller than 0.3 (since the density change due to velocity is about 5% in that case). The study of compressible flow is relevant to high-speed aircraft, jet engines, rocket motors, high-speed entry into a planetary atmosphere, gas pipelines, commercial applications such as abrasive blasting, and many other fields.

Estimator

In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the sample mean is a commonly used estimator of the population mean. There are point and interval estimators. The point estimators yield single-valued results. This is in contrast to an interval estimator, where the result would be a range of plausible values.

Related publications (31)

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Marco Picasso, Paride Passelli

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

Walter De Gruyter Gmbh2024

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Paride Passelli

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

EPFL2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024