0000000000350792

AUTHOR

Jacques Periaux

showing 21 related works from this author

Three Faces of Fitz: Science, Communication and Leadership

2018

In what follows we provide a brief overview of the life and work of Professor William Fitzgibbon ( University. of Houston)

Work (electrical)Science communicationSociologyManagement
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Efficient Parallel Nash Genetic Algorithm for Solving Inverse Problems in Structural Engineering

2015

A parallel implementation of a game-theory based Nash Genetic Algorithm (Nash-GAs) is presented in this paper for solving reconstruction inverse problems in structural engineering. We compare it with the standard panmictic genetic algorithm in a HPC environment with up to eight processors. The procedure performance is evaluated on a fifty-five bar sized test case of discrete real cross-section types structural frame. Numerical results obtained on this application show a significant achieved increase of performance using the parallel Nash-GAs approach compared to the standard GAs or Parallel GAs.

Computer Science::Computer Science and Game TheoryMathematical optimizationbusiness.industryBar (music)Structural systemGenetic algorithmStructural engineeringInverse problembusinessAlgorithmFinite element methodMathematicsNash games
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Agile Deep Learning UAVs Operating in Smart Spaces: Collective Intelligence Versus “Mission-Impossible”

2017

The environments, in which we all live, are known to be complex and unpredictable. The complete discovery of these environments aiming to take full control over them is a “mission-impossible”, however, still in our common agenda. People intend to make their living spaces smarter utilizing innovations from the Internet of Things and Artificial Intelligence. Unmanned aerial vehicles (UAVs) as very dynamic, autonomous and intelligent things capable to discover and control large areas are becoming important “inhabitants” within existing and future smart cities. Our concern in this paper is to challenge the potential of UAVs in situations, which are evolving fast in a way unseen before, e.g., em…

Engineeringbusiness.industryProcess (engineering)media_common.quotation_subjectBig dataCollective intelligenceCloud computing02 engineering and technologyReuseComputer securitycomputer.software_genre020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality (business)businesscomputerSemantic WebAgile software developmentmedia_common
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Roland Glowinski: The Unconventional and Unexpected Path of a Mathematician

2009

More than 10 years have elapsed since the conference, “Computational Science for the Twentieth Century”, was held in Tours, France. The Tours event honored the 60th birthday of Roland Glowinski. The world has witnessed many changes in the last decade, but Roland and his lovely wife, Angela, seem to barely have changed at all. Indeed, they are like fine French wine or Tennessee whiskey; they improve with age. As we reflect upon the career of Roland, it is important that we not underestimate the role of Angela. Everyone knows the old saying, Beside every great man stands a great woman.

Great Man theorymedia_common.quotation_subjectArt historyWifePerformance artArtEvent (philosophy)media_common
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Digital Technologies for Transport and Mobility: Challenges, Trends and Perspectives

2020

This white paper aims at presenting the ideas emerging from the different fields pertaining to transport and mobility, to describe the capacities of current state-of-the-art digital technologies and the perspectives that are expected to shape the future of transport and mobility.

White paperComputer sciencebusiness.industryLogisticSurface transportLogisticsAeronautics and aviationCurrent (fluid)Cyber securityTelecommunicationsbusinessAeronautics and aviation; Cyber security; Logistics; Surface transport
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Multidisciplinary shape optimization in aerodynamics and electromagnetics using genetic algorithms

1999

SUMMARY A multiobjective multidisciplinary design optimization (MDO) of two-dimensional airfoil is presented. In this paper, an approximation for the Pareto set of optimal solutions is obtained by using a genetic algorithm (GA). The first objective function is the drag coefficient. As a constraint it is required that the lift coefficient is above a given value. The CFD analysis solver is based on the finite volume discretization of the inviscid Euler equations. The second objective function is equivalent to the integral of the transverse magnetic radar cross section (RCS) over a given sector. The computational electromagnetics (CEM) wave field analysis requires the solution of a two-dimensi…

Mathematical optimizationElectromagneticsHelmholtz equationFictitious domain methodApplied MathematicsMechanical EngineeringMultidisciplinary design optimizationComputational MechanicsSolverComputer Science ApplicationsEuler equationssymbols.namesakeMechanics of MaterialssymbolsComputational electromagneticsShape optimizationMathematicsInternational Journal for Numerical Methods in Fluids
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Evolutionary Algorithms and Metaheuristics : Applications in Engineering Design and Optimization

2018

Article SubjectComputer scienceoptimisationGeneral MathematicsEvolutionary algorithmevoluutiolaskenta02 engineering and technologytekoälyalgorithms01 natural sciences010305 fluids & plasmas0203 mechanical engineeringoptimointi0103 physical sciencesalgoritmitMetaheuristicta113business.industrylcsh:Mathematicsta111General Engineeringlcsh:QA1-939artificial intelligence020303 mechanical engineering & transportslcsh:TA1-2040evolutionary computationArtificial intelligenceEngineering design processbusinesslcsh:Engineering (General). Civil engineering (General)
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A Study of Nash-Evolutionary Algorithms for Reconstruction Inverse Problems in Structural Engineering

2014

In this paper we deal with solving inverse problems in structural engineering (both the reconstruction inverse problem and the fully stressed design problem are considered). We apply a game-theory based Nash-evolutionary algorithm and compare it with the standard panmictic evolutionary algorithm. The procedure performance is analyzed on a ten bar sized test case of discrete real cross-section types structural frame, where a significant increase of performance is achieved using the Nash approach, even achieving super-linear speed-up.

Mathematical optimizationsymbols.namesakeBar (music)business.industryComputer scienceNash equilibriumStructural systemEvolutionary algorithmsymbolsStructural engineeringInverse problembusiness
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Shock control bump design optimization on natural laminar aerofoil

2011

The chapter investigates Shock Control Bumps (SCB) on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 for Active Flow Control (AFC). A SCB approach is used to decelerate supersonic flow on the suction/pressure sides of transonic aerofoil that leads delaying shock occurrence or weakening of shock strength. Such an AFC technique reduces significantly the total drag at transonic speeds. This chapter considers the SCB shape design optimisation at two boundary layer transition positions (0 and 45%) using an Euler software coupled with viscous boundary layer effects and robust Evolutionary Algorithms (EAs). The optimisation method is based on a canonical Evolution Strategy (ES) algorithm and inco…

AirfoilHybrid OptimisationEngineeringUAVAvions -- AlesDrag Reduction:Matemàtiques i estadística::Anàlisi numèrica [Àrees temàtiques de la UPC]Aerofoils--Mathematical modelsTransition pointWave dragAerospace engineeringAerodinàmica -- Mètodes numèricsSuction Sidebusiness.industry:Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics [Àrees temàtiques de la UPC]Laminar flow010303 Optimisation090100 AEROSPACE ENGINEERINGMechanicsBoundary Layer TransitionACTIVE FLOW CONTROL:Aeronàutica i espai::Aerodinàmica [Àrees temàtiques de la UPC]Superfícies de sustentacióLift (force)Boundary layerWave DragDragUASbusinessBaseline DesignTransonic090104 Aircraft Performance and Flight Control Systems
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A New Distributed Optimization Approach for Solving CFD Design Problems Using Nash Game Coalition and Evolutionary Algorithms

2013

For decades, domain decomposition methods (DDM) have provided a way of solving large-scale problems by distributing the calculation over a number of processing units. In the case of shape optimization, this has been done for each new design introduced by the optimization algorithm. This sequential process introduces a bottleneck.

Mathematical optimizationProcess (engineering)Computer sciencebusiness.industryEvolutionary algorithmDomain decomposition methodsComputational fluid dynamicsBottlenecksymbols.namesakeNash equilibriumDifferential evolutionsymbolsShape optimizationbusiness
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A Domain Decomposition/Nash Equilibrium Methodology for the Solution of Direct and Inverse Problems in Fluid Dynamics with Evolutionary Algorithms

2008

Mathematical optimizationsymbols.namesakeNash equilibriumGenetic algorithmFluid dynamicsEvolutionary algorithmA domainsymbolsDecomposition (computer science)Inverse problemMathematics
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Olivier Pironneau Career Paper

2018

In what follows we provide a brief overview of the life and work of Professor Olivier Pironneau Fitzgibbon ( LJLL Sorbonne Universite)

Art historySociology
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Career of Prof. Yuri Kuznetsov

2018

In what follows we provide a brief overview of the life and work of Professor Yuri Kuznetsov ( University of Houston)

Art historySociology
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Shape design optimization in 2D aerodynamics using Genetic Algorithms on parallel computers

1996

Publisher Summary This chapter presents two Shape Optimization problems for two dimensional airfoil designs. The first one is a reconstruction problem for an airfoil when the velocity of the flow is known on the surface of airfoil. The second problem is to minimize the shock drag of an airfoil at transonic regime. The flow is modeled by the full potential equations. The discretization of the state equation is done using the finite element method and the resulting non-linear system of equations is solved by using a multi-grid method. The non-linear minimization process corresponding to the shape optimization problems are solved by a parallel implementation of a genetic algorithm (GA). Some n…

Physics::Fluid DynamicsAirfoilOptimal designMathematical optimizationDiscretizationApplied mathematicsShape optimizationAerodynamicsTransonicFinite element methodMathematicsSequential quadratic programming
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NASH EVOLUTIONARY ALGORITHMS: TESTING PROBLEM SIZE IN RECONSTRUCTION PROBLEMS IN FRAME STRUCTURES

2016

The use of evolutionary algorithms has been enhanced in recent years for solving real engineering problems, where the requirements of intense computational calculations are needed, especially when computational engineering simulations are involved (use of finite element method, boundary element method, etc). The coupling of game-theory concepts in evolutionary algorithms has been a recent line of research which could enhance the efficiency of the optimum design procedure and the quality of the design solutions achieved. They have been applied in several fields of engineering and sciences, mainly, in aeronautical and structural engineering (e.g: in computational fluid dynamics and solid mech…

frame optimizationFrame (networking)Evolutionary algorithmgame strategiesstructural optimizationrakennesuunnitteluevolutionary algorithmsAlgorithmNash equilibriumMathematicsProceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)
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Parallel Genetic Solution for Multiobjective MDO

1997

Publisher Summary This chapter reviews a multiobjective, multidisciplinary design optimization of two-dimensional airfoil designs. The control points on leading and trailing edges remain fixed, and the y-coordinates of the other control points are allowed to change during the optimization process. The grid for the Euler solver depends continuously and smoothly on the design parameters. The number of nodes and elements in the mesh might vary according to design because the meshes for the Helmholtz solver are done using the local fitting. The computations are made on an IBM SP2 parallel computer using high-performance switch and the MPICH message-passing library. As gradients are not required…

symbols.namesakeMathematical optimizationMPICHMultidisciplinary design optimizationHelmholtz free energyConvergence (routing)symbolsPolygon meshShape optimizationSolverGridMathematics
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A Lagrange Multiplier Based Domain Decomposition Method for the Solution of a Wave Problem with Discontinuous Coefficients

2008

In this paper we consider the numerical solution of a linear wave equation with discontinuous coefficients. We divide the computational domain into two subdomains and use explicit time difference scheme along with piecewise linear finite element approximations on semimatching grids. We apply boundary supported Lagrange multiplier method to match the solution on the interface between subdomains. The resulting system of linear equations of the “saddle-point” type is solved efficiently by a conjugate gradient method.

Piecewise linear functionsymbols.namesakeConstraint algorithmLagrange multiplierConjugate gradient methodMathematical analysisMathematicsofComputing_NUMERICALANALYSISsymbolsBoundary (topology)Domain decomposition methodsSystem of linear equationsDomain (mathematical analysis)Mathematics
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Fast Nash Hybridized Evolutionary Algorithms for Single and Multi-objective Design Optimization in Engineering

2014

Evolutionary Algorithms (EAs) are one of advanced intelligent systems and they occupied an important position in the class of optimizers for solving single-objective/reverse/inverse design and multi-objective/multi physics design problems in engineering. The chapter hybridizes the Genetic Algorithms (GAs) based computational intelligent system (CIS) with the concept of Nash-Equilibrium as an optimization pre-conditioner to accelerate the optimization procedure. Hybridized GAs and simple GAs are validated through solving five complex single-objective and multi-objective mathematical design problems. For real-world design problems, the hybridized GAs (Hybrid Intelligent System) and the origin…

Mathematical optimizationbusiness.industryEvolutionary algorithmIntelligent decision support systemInverseCADcomputer.software_genreFinite element methodHybrid intelligent systemSoftwareComputer Aided DesignArtificial intelligencebusinesscomputer
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Evolutionary cloud for cooperative UAV coordination

2014

pilvipalvelutkoordinointiälytekniikkaevoluutiolaskentamiehittämättömät ilma-aluksetsemanttinen webtiedonlouhintaturvallisuustekniikka
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Design challenges and opportunities of 3D printing

2019

In the future, the number and complexity of products made using additive manufacturing (AM) techniques will increase rapidly. The development of softwares and algorithms related to processes will eliminate extra intermediate steps between the product design and the end product, and will finally give us more intelligent way to manufacture these new products. More efficient 3D printing processes will enable the production of cheaper individual items and, furthermore, they will increase the demand for these high - quality tailored unrivalled solutions. The market potential is huge. However, at present the fundamentals of the area are only lightly studied and several key challenges concerning s…

3D-tulostustuotekehitys3D printingproduct development
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Agile Deep Learning UAVs Operating in Smart Spaces : Collective Intelligence Versus “Mission-Impossible”

2018

The environments, in which we all live, are known to be complex and unpredictable. The complete discovery of these environments aiming to take full control over them is a “mission-impossible”, however, still in our common agenda. People intend to make their living spaces smarter utilizing innovations from the Internet of Things and Artificial Intelligence. Unmanned aerial vehicles (UAVs) as very dynamic, autonomous and intelligent things capable to discover and control large areas are becoming important “inhabitants” within existing and future smart cities. Our concern in this paper is to challenge the potential of UAVs in situations, which are evolving fast in a way unseen before, e.g., em…

koneoppiminendeep learningmiehittämättömät ilma-aluksetagile learning
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