CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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4 Advanced Methods and Multiphysics The ”Advanced Aerodynamics and Multiphysics” group is a component of the CFD Team. Around 15 researchers (seniors, PhD and Post Doctoral students) are involved in aerodynamics activities. The objective of the group is to develop, maintain and use efficient numerical solvers related to academic and industrial CFD simulations. Most of our efforts focus on the elsA software (owned by Onera) but we also use in-house solvers : AVBP for unstructured Large Eddy Simulation (LES) and NTMIX for Direct Numerical Simulation. During the past two years, LES activities have grown significantly, especially in unsteady simulations (aeroacoustics or aerothermal) where RANS is not sufficient. To be able to deal with accurate LES in elsA, several developments have been done (high order scheme, non reflexive boundary conditions, wall laws, turbulence injection) leading to new applications : jet, airfoil and landing gear noise but also aerothermal jet in cross flow. In addition to advanced turbulence methods, the team (in collaboration with Onera) continues the extension of elsA to the unstructured world. This will allow more flexibility to deal with complex geometries and help us to answer the 2020 challenge ”PUMA” defined by CERFACS in 2011, which ambitions to compute a fully unsteady aircraft. To finish, the activity concerning design optimization is also growing in collaboration with the Algo team. The work presented in the next sections has been done in close collaboration with our industrials partners (Airbus, Snecma, Turboméca) but also with research centers among which Onera, Paris VI, KTH, ECL. 4.1 Numerical methods 4.1.1 Improve LES capabilities (S. Bocquet, J-C. Jouhaud) Large-Eddy Simulation (LES) of industrial high-Reynolds number flows is still far from being practical on a daily basis. Various methods have been proposed to reduce the computational cost of LES. These last years, the team has investigated two approaches : Thin Boundary Layer models and embedded LES. Thin boundary layer laws The cost of LES is mainly due to the resolution of the small but dynamically important structures present in the inner layer of the boundary layer. The LES with wall model approach is one technique to reduce the computational cost of such computations. A coarse mesh is used close to the wall so that the inner layer of the boundary layer is not captured. In the coarse cells adjacent to the wall, the wall fluxes need to be approximated by an additional wall model. The wall model must contain the flow physics present in the inner layer and can be either a quasi-analytical model composed of wall laws or a numerical model like the Thin Boundary Layer (TBL) model described in Balaras (1996) where a simplified one dimensional model is used between the wall and the first LES point in the flow. Despite their cost, TBL models constitute an interesting framework for the derivation of wall models 156 Jan. 2010 – Dec. 2011
COMPUTATIONAL FLUID DYNAMICS (a) Velocity profiles. (b) Temperature profiles. (c) Computational domain. FIG. 4.1: LES with wall modeling on supersonic plane channel flow compared to Coleman DNS : Mach = 1.5 (bottom) and Mach = 3 (top). adapted to various physical effects. Thus, a TBL model based on the work of Monfort (2009) and extended to compressible flows has been implemented in the elsA software. This wall model has been validated on a quasi-incompressible channel flow, with friction Reynolds number Re τ ranging from 1020 to 20000, the latter being representative of the boundary layer at the leading edge of a commercial airplane during cruise. The errors on the friction coefficient C f and wall heat flux Nu remain below 10% for the range of Reynolds number tested. Then a more discriminatory test case, namely the supersonic channel flow of Coleman (1995), has been used to assess the capability of this approach to handle significant compressibility effects. Figure 4.1 shows the velocity and temperature profiles obtained on a coarse mesh of (21 × 21 × 25) points. The excellent agreement obtained on the temperature profile constitutes an encouraging starting point toward LES with wall modeling of compressible flows with convective heat transfer. Embedded LES Within the frame of ASTHER project (FRAE funding, AIRBUS-ONERA-CERFACS collaborative work), we have focused on the embedded LES strategy. The idea is to run sequentially a low computational cost RANS simulation in a large domain around the area of interest, so that the influence of boundary conditions can be neglected. Then a LES simulation is performed in a smaller domain centered on the area of interest. The RANS flow is used to define the LES boundary conditions and the initial solution. A schematic view of this method is shown in Fig. 4.2a for a jet in cross flow configuration. Navier-Stokes Characteristic Boundary Condition (NSCBC) are used for the LES domain. As shown in Fig. 4.2b, a good agreement is obtained compared to experimental data [CFD96]. 4.1.2 Optimization (M. Montagnac, F. Gallard, M. Mouffe) Since 2005, CERFACS works in numerical optimization in the context of aircraft preliminary design. The optimization setup of modern aircraft often ends up with several hundreds of design variables and a few constraints. The work is subdivided into three parts that are integrated in the OPTaliA framework of Airbus CERFACS ACTIVITY REPORT 157
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CERFACS Scientific Activity Report
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Table des matières 1 Foreword xiii
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9 Publications 40 9.1 Books . . . .
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3 The OpenPALM coupler 104 3.1 Intr
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Table des figures CERFACS chart as
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TABLE DES FIGURES 6 Computational F
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Foreword Welcome to the 2010-2011 S
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CERFACS STRUCTURE CERFACS organizat
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CERFACS STAFF NAME POSITION PERIOD
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CERFACS STAFF SILVA GARZON Ph.D stu
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CERFACS STAFF NAME POSITION PERIOD
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CERFACS Wide-Interest Seminars Pete
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1 Introduction 1.1 Introduction The
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PARALLEL ALGORITHMS PROJECT success
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PARALLEL ALGORITHMS PROJECT Visitor
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3 List of Members of HiePACS HiePAC
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4 Dense and Sparse Matrix Computati
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PARALLEL ALGORITHMS PROJECT Working
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5 Iterative Methods and Preconditio
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PARALLEL ALGORITHMS PROJECT 5.5 Pre
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PARALLEL ALGORITHMS PROJECT We are
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PARALLEL ALGORITHMS PROJECT is to e
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PARALLEL ALGORITHMS PROJECT automor
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PARALLEL ALGORITHMS PROJECT 7.4 Sol
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PARALLEL ALGORITHMS PROJECT precond
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PARALLEL ALGORITHMS PROJECT 7.16 An
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PARALLEL ALGORITHMS PROJECT solutio
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8 Conferences and Seminars 8.1 Conf
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PARALLEL ALGORITHMS PROJECT Decembe
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PARALLEL ALGORITHMS PROJECT July WC
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PARALLEL ALGORITHMS PROJECT Septemb
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PARALLEL ALGORITHMS PROJECT [ALG15]
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PARALLEL ALGORITHMS PROJECT [ALG54]
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1 Overview presentation The main ex
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ELECTROMAGNETISM AND ACOUSTICS TEAM
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1 Introduction Data assimilation is
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DATA ASSIMILATION 2.3 Calibrating o
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3 Data assimilation for atmospheric
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DATA ASSIMILATION BECM using or not
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DATA ASSIMILATION the potential vor
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DATA ASSIMILATION A two years simul
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DATA ASSIMILATION FIG. 4.1: Reducti
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DATA ASSIMILATION FIG. 4.3: April 2
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DATA ASSIMILATION by a surface mode
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6 Data assimilation with EDF neutro
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DATA ASSIMILATION demonstrate that
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DATA ASSIMILATION [DA13] S. Massart
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4 Coupling tools and HPC Climate Mo
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2 The OASIS coupler The OASIS coupl
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THE OASIS COUPLER 2.3 OASIS4 Since
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3 The OpenPALM coupler 3.1 Introduc
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Page 153 and 154: 1 Introduction The CFD (Computation
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Page 191 and 192: 5 Publications 5.1 Conferences Proc
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Page 204 and 205: INTRODUCTION instead of regular ker
Page 206 and 207: SIMULATIONS OF AIRCRAFT WAKES AND R
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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011