Qualitative property

Qualitative properties are properties that are observed and can generally not be measured with a numerical result. They are contrasted to quantitative properties which have numerical characteristics. Some engineering and scientific properties are qualitative. A test method can result in qualitative data about something. This can be a categorical result or a binary classification (e.g., pass/fail, go/no go, conform/non-conform). It can sometimes be an engineering judgement. The data that all share a qualitative property form a . A variable which codes for the presence or absence of such a property is called a binary categorical variable, or equivalently a dummy variable. In businesses Some important qualitative properties that concern businesses are: Human factors, 'human work capital' is probably one of the most important issues that deals with qualitative properties. Some common aspects are work, motivation, general participation, etc. Although all of these aspects are no

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Splitting methods based on algebraic factorization for fluid-structure interaction

Annalisa Quaini, Alfio Quarteroni

We discuss in this paper the numerical approximation of fluid-structure interaction (FSI) problems dealing with strong added-mass effect. We propose new semi-implicit algorithms based on inexact block-LU factorization of the linear system obtained after the space-time discretization and linearization of the FSI problem. As a result, at each iteration the fluid velocity is computed separately from the coupled pressure-structure velocity system, reducing the computational cost. We investigate explicit-implicit decomposition through algebraic splitting techniques originally designed for the FSI problem. This approach leads to two different families of methods which extend to FSI the algebraic pressure correction method and the Yosida method, two schemes that were previously adopted for pure fluid problems. Furthermore, we have considered the inexact factorization of the fluid- structure system as a preconditioner. The numerical properties of these methods have been tested on a model problem representing a blood-vessel system.

2008

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Stability Analysis of a Partitioned Fluid-Structure Thermal Coupling Algorithm

Ojas Joshi, Pénélope Leyland

Numerical multiphysics coupling is gaining more and more importance in engineering. Partitioned algorithms are among the most efficient methods to solve the coupled problem. However, they present some drawbacks, with the stability of the algorithm itself being the crucial one. The principal factors that lead to instability are the physical and numerical properties of the system. In this paper, a thermal coupling between a fluid and a solid, performed through a parallel partitioned algorithm, is considered. A condition that ensures the stability of the algorithm is derived.

Amer Inst Aeronautics Astronautics2014

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Multi space reduced basis preconditioners for parametrized Stokes equations

Niccolò Dal Santo, Simone Deparis, Andrea Manzoni, Alfio Quarteroni

We introduce a two-level preconditioner for the efficient solution of large scale saddle point linear systems arising from the finite element (FE) discretization of parametrized Stokes equations. This preconditioner extends the Multi Space Reduced Basis (MSRB) preconditioning method proposed in Dal Santo et al. (2018); it combines an approximated block (fine grid) preconditioner with a reduced basis (RB) solver which plays the role of coarse component. A sequence of RB spaces, constructed either with an enriched velocity formulation or a Petrov - Galerkin projection, is built. Each RB coarse component is defined to perform a single iteration of the iterative method at hand. The flexible GMRES (FGMRES) algorithm is employed to solve the resulting preconditioned system and targets small tolerances with a very small iteration count and in a very short time. Numerical test cases for Stokes flows in three dimensional parameter-dependent geometries are considered to assess the numerical properties of the proposed technique in different large scale computational settings. (C) 2018 Elsevier Ltd. All rights reserved.

PERGAMON-ELSEVIER SCIENCE LTD2019

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Variable catégorielle

En statistique, une variable qualitative, une variable catégorielle, ou bien un facteur est une variable qui prend pour valeur des modalités, des catégories ou bien des niveaux, par opposition aux var

PHYS-442: Modeling and design of experiments

In the academic or industrial world, to optimize a system, it is necessary to establish strategies for the experimental approach. The DOE allows you to choose the best set of measurement points to minimize the variance of the results. The concepts learned are applicable in all areas.

BIO-341: Dynamical systems in biology

Ce cours introduit les systèmes dynamiques pour modéliser des réseaux biologiques simples. L'analyse qualitative de modèles dynamiques non-linéaires est développée de pair avec des simulations numériques. L'accent est mis sur les exemples biologiques.

MGT-301: Foundations in financial economics

The aim of this course is to expose EPFL bachelor students to some of the main areas in financial economics. The course will be organized around six themes. Students will obtain both practical insights through real-world examples and understand how one can model the main economic trade-offs.