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Didier Auroux Jacques Blum
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Didier Auroux Jacques Blum

U-Auroux-D810\Didier Auroux, S-1-5-21-172797399-3483302530-1805387423-1005

Didier Auroux Jacques Blum Alternate Text
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Didier Auroux Jacques Blum

U-Auroux-D810\Didier Auroux, S-1-5-21-172797399-3483302530-1805387423-1005

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42 pages

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In this chapter we present and discuss most significant contributions in Multi Disciplinary Optimization MDO The name multidisciplinary optimization is often taken literally We prefer to call it collaborative design optimization Indeed the optimization tool is only one part which can not be separated from the total design process The goal of collaborative optimization is not to create an automatic design process based on optimization algorithms but to allow easy interaction amongst teams from different disciplines
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In this chapter we present and discuss most significant contributions in Multi Disciplinary Optimization MDO The name multidisciplinary optimization is often taken literally We prefer to call it collaborative design optimization Indeed the optimization tool is only one part which can not be separated from the total design process The goal of collaborative optimization is not to create an automatic design process based on optimization algorithms but to allow easy interaction amongst teams from different disciplines

In this chapter we present and discuss most significant contributions in Multi Disciplinary Optimization MDO The name multidisciplinary optimization is often taken literally We prefer to call it collaborative design optimization Indeed the optimization tool is only one part which can not be separated from the total design process The goal of collaborative optimization is not to create an automatic design process based on optimization algorithms but to allow easy interaction amongst teams from different disciplines Alternate Text
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In this chapter we present and discuss most significant contributions in Multi Disciplinary Optimization MDO The name multidisciplinary optimization is often taken literally We prefer to call it collaborative design optimization Indeed the optimization tool is only one part which can not be separated from the total design process The goal of collaborative optimization is not to create an automatic design process based on optimization algorithms but to allow easy interaction amongst teams from different disciplines

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36 pages

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Optimization and Engineering c Kluwer Academic Publishers Manufactured in The Netherlands
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Optimization and Engineering c Kluwer Academic Publishers Manufactured in The Netherlands

Fabrice Veersé

Optimization and Engineering c Kluwer Academic Publishers Manufactured in The Netherlands Alternate Text
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Optimization and Engineering c Kluwer Academic Publishers Manufactured in The Netherlands

Fabrice Veersé

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17 pages

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Applied Mathematics E Notes c ISSN Available free at mirror sites of
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Applied Mathematics E Notes c ISSN Available free at mirror sites of

Jean-Claude Yakoubsohn

Applied Mathematics E Notes c ISSN Available free at mirror sites of Alternate Text
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Applied Mathematics E Notes c ISSN Available free at mirror sites of

Jean-Claude Yakoubsohn

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5 pages

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Didier Auroux Laboratoire J A Dieudonne
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Didier Auroux Laboratoire J A Dieudonne

Didier Auroux

Didier Auroux Laboratoire J A Dieudonne Alternate Text
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Didier Auroux Laboratoire J A Dieudonne

Didier Auroux

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46 pages

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Didier Auroux Laboratoire MIP Institut de Mathematiques de Toulouse Universite Paul Sabatier Toulouse France ups tlse fr
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Didier Auroux Laboratoire MIP Institut de Mathematiques de Toulouse Universite Paul Sabatier Toulouse France ups tlse fr

Didier Auroux

Didier Auroux Laboratoire MIP Institut de Mathematiques de Toulouse Universite Paul Sabatier Toulouse France ups tlse fr Alternate Text
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Didier Auroux Laboratoire MIP Institut de Mathematiques de Toulouse Universite Paul Sabatier Toulouse France ups tlse fr

Didier Auroux

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47 pages

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Data assimilation methods for an oceanographic problem
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Data assimilation methods for an oceanographic problem

Data assimilation methods for an oceanographic problem Alternate Text
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Data assimilation methods for an oceanographic problem

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16 pages

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D AUROUX AND S BONNABEL
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D AUROUX AND S BONNABEL

Silvère Bonnabel

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D AUROUX AND S BONNABEL

Silvère Bonnabel

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13 pages

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UNIVERSITE DE NICE SOPHIA ANTIPOLIS UFR SCIENCES Ecole Doctorale
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UNIVERSITE DE NICE SOPHIA ANTIPOLIS UFR SCIENCES Ecole Doctorale

Sophia Antipolis

UNIVERSITE DE NICE SOPHIA ANTIPOLIS UFR SCIENCES Ecole Doctorale Alternate Text
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UNIVERSITE DE NICE SOPHIA ANTIPOLIS UFR SCIENCES Ecole Doctorale

Sophia Antipolis

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236 pages

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Didier Auroux Institut de Mathematiques de Toulouse Projet MOISE
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Didier Auroux Institut de Mathematiques de Toulouse Projet MOISE

Didier Auroux

Didier Auroux Institut de Mathematiques de Toulouse Projet MOISE Alternate Text
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Didier Auroux Institut de Mathematiques de Toulouse Projet MOISE

Didier Auroux

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42 pages

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Conference on Gromov–Witten theory Institut Fourier Grenoble July 4th 8th
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Conference on Gromov–Witten theory Institut Fourier Grenoble July 4th 8th

Denis Auroux

Conference on Gromov–Witten theory Institut Fourier Grenoble July 4th 8th Alternate Text
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Conference on Gromov–Witten theory Institut Fourier Grenoble July 4th 8th

Denis Auroux

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5 pages

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Identification of velocity fields for geophysical fluids from a sequence of images
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Identification of velocity fields for geophysical fluids from a sequence of images

Didier Auroux

Identification of velocity fields for geophysical fluids from a sequence of images Alternate Text
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Identification of velocity fields for geophysical fluids from a sequence of images

Didier Auroux

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16 pages

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In th The st introdu The m Acad Résum
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In th The st introdu The m Acad Résum

Didier Auroux

In th The st introdu The m Acad Résum Alternate Text
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In th The st introdu The m Acad Résum

Didier Auroux

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6 pages

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An easy to implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging BFN algorithm
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An easy to implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging BFN algorithm

An easy to implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging BFN algorithm Alternate Text
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An easy to implement and efficient data assimilation method for the identification of the initial condition: the Back and Forth Nudging BFN algorithm

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8 pages

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Laboratoire MIP Institut de Mathematiques de Toulouse
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Laboratoire MIP Institut de Mathematiques de Toulouse

Didier Auroux

Laboratoire MIP Institut de Mathematiques de Toulouse Alternate Text
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Laboratoire MIP Institut de Mathematiques de Toulouse

Didier Auroux

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49 pages

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University of Nice Sophia Antipolis
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University of Nice Sophia Antipolis

Didier Auroux

University of Nice Sophia Antipolis Alternate Text
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University of Nice Sophia Antipolis

Didier Auroux

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42 pages

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Symmetry preserving observers for water tank problems: theory and application to an
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Symmetry preserving observers for water tank problems: theory and application to an

Silvère Bonnabel

Symmetry preserving observers for water tank problems: theory and application to an Alternate Text
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Etudes supérieures

Symmetry preserving observers for water tank problems: theory and application to an

Silvère Bonnabel

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43 pages

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Post SAROD Workshop
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Post SAROD Workshop

Didier Auroux

Post SAROD Workshop Alternate Text
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Post SAROD Workshop

Didier Auroux

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17 pages

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presented to obtain the
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Presented to obtain the

Paul Sabatier

presented to obtain the Alternate Text
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Etudes supérieures

Presented to obtain the

Paul Sabatier

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80 pages

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