52 research outputs found
Aircraft shape optimization for mission performance
An aircraft encounters a wide range of operating conditions during its missions, i.e. flight altitude, Mach number and angle of attack, which consideration at the design phase enhances the system robustness and consequently the overall fleet consumption. Numerical optimization of aerodynamic shapes contributes to aircraft design, and relies on the automation of geometry generation and numerical simulations of the flight physics. Minimization of aerodynamic shapes drag must take into account multiple operating conditions, since optimization at a single operating condition leads to a strong degradation of performance when this operating condition varies. Besides, structural flexibility deforms the wings differently depending on the operating conditions, so has to be simulated during such optimizations. In the present thesis, the mission fuel consumption minimization is formulated as an optimization problem.
The focus is made on the choice of operating conditions to be included in the optimization problem, since they have a major impact on the quality of the results, and the computational cost is proportional to their number. A new theoretical framework is proposed, overcoming and giving new insights on problematic situations revealed by state-of-the-art methods for multipoint optimization problem setup. An algorithm called Gradient Span Analysis is proposed to automate the choice of operating conditions. It is based on a reduction of dimension of the vector space spanned by adjoint gradients obtained at the different operating conditions. Programming contributions to the optimization chain enabled the evaluation of the new method on the optimizations of the academic RAE2822 airfoil, and the XRF-1 wing-body configuration, representative of a modern transport aircraft. While the shapes resulting of single-point optimizations present strong degradations of the performance in off-design conditions, adequately formulated multi-Machmulti- lift optimizations present much more interesting performance compromises. It is finally shown that fluid-structure interaction adds new degrees of freedom, and has consequences on multiple flight conditions optimizations, opening the perspective of passive shape adaptation
Non-Uniform Time Sampling for Multiple-Frequency Harmonic Balance Computations
A time-domain harmonic balance method for the analysis of almost-periodic (multi-harmonics) flows is presented. This method relies on Fourier analysis to derive an efficient alternative to classical time marching schemes for such flows. It has recently received significant attention, especially in the turbomachinery field where the flow spectrum is essentially a combination of the blade passing frequencies. Up to now, harmonic balance methods have used a uniform time sampling of the period of interest, but in the case of several frequencies, non-necessarily multiple of each other, harmonic balance methods can face stability issues due to a bad condition number of the Fourier operator. Two algorithms are derived to find a non-uniform time sampling in order to minimize this condition number. Their behavior is studied on a wide range of frequencies, and a model problem of a 1D flow with pulsating outlet pressure, which enables to prove their efficiency. Finally, the flow in a multi-stage axial compressor is analyzed with different frequency sets. It demonstrates the stability and robustness of the present non-uniform harmonic balance method regardless of the frequency set
Gradient Span Analysis Method: Application to the Multipoint Aerodynamic Shape Optimization of a Turbine Cascade
This paper presents the application of the gradient span analysis (GSA) method to the multipoint optimization of the two-dimensional LS89 turbine distributor. The cost function (total pressure loss) and the constraint (mass flow rate) are computed from the resolution of the Reynolds-averaged Navier-Stokes equations. The penalty method is used to replace the constrained optimization problem with an unconstrained problem. The optimization process is steered by a gradient-based quasi-Newton algorithm. The gradient of the cost function with respect to design variables is obtained with the discrete adjoint method, which ensures an efficient computation time independent of the number of design variables. The GSA method gives a minimal set of operating conditions to insert into the weighted sum model to solve the multipoint optimization problem. The weights associated to these conditions are computed with the utopia point method. The single-point optimization at the nominal condition and the multipoint optimization over a wide range of conditions of the LS89 blade are compared. The comparison shows the strong advantages of the multipoint optimization with the GSA method and utopia-point weighting over the traditional single-point optimization
Optimisation de forme dâun avion pour sa performance sur une mission
Les avions rencontrent de nombreuses conditions dâopĂ©rations au cours de leurs vols, comme le nombre de Mach, lâaltitude et lâangle dâattaque. Leur prise en compte durant la conception amĂ©liore la robustesse du systĂšme et finalement la consommation des flottes dâavions. Lâoptimisation de formes aĂ©rodynamiques contribue Ă la conception des avions, et repose sur lâautomatisation de la gĂ©nĂ©ration de gĂ©omĂ©tries ainsi que la simulation numĂ©rique de la physique du vol. La minimisation de la trainĂ©e des formes aĂ©rodynamiques doit prendre en compte de multiples conditions dâopĂ©ration, Ă©tant donne que lâoptimisation a une unique condition de vol mĂšne a des formes dont la performance se dĂ©grade fortement quand cette condition de vol est perturbĂ©e. De plus, la flexibilitĂ© structurelle dĂ©forme les ailes diffĂ©remment selon la condition de vol, et doit donc ĂȘtre simulĂ©e lors de telles optimisations. Dans cette thĂšse, la minimisation de la consommation de carburant au cours dâune mission est formulĂ©e en problĂšme dâoptimisation. Une attention particuliĂšre est apportĂ©e au choix des conditions dâopĂ©rations Ă inclure dans le problĂšme dâoptimisation, Ă©tant donne que celles-ci ont un impact majeur sur la qualitĂ© des rĂ©sultats obtenus, et que le cout de calcul est proportionnel Ă leur nombre. Un nouveau cadre thĂ©orique est proposĂ© pour adresser cette question, offrant un point de vue original et surmontant des difficultĂ©s rĂ©vĂ©lĂ©es par les mĂ©thodes a lâĂ©tat-de-lâ art en matiĂšre de mise en place de problĂšmes dâoptimisation multipoints. Un algorithme appelĂ© Gradient Span Analysis (GSA), est proposĂ© pour automatiser le choix des conditions dâopĂ©ration. Il est base sur la rĂ©duction de dimension de lâespace vectoriel engendre par les gradients adjoints aux diffĂ©rentes conditions de vol. Des contributions de programmation a la chaine dâoptimisation ont permis dâĂ©valuer les mĂ©thodes aux optimisations du profil acadĂ©mique RAE2822 et de la configuration voilure-fuselage XRF-1, reprĂ©sentative des avions de transport modernes. Alors que les formes rĂ©sultant dâoptimisation mono-point prĂ©sentent de fortes dĂ©gradations de performance hors du point de conception, les optimisations multipoints adĂ©quatement formulĂ©es fournissent de bien meilleurs compromis. Il est finalement montre que les interactions fluide-structure ajoutent de nouveaux degrĂ©s de libertĂ©, et ont un impact sur les optimisations en de multiples conditions de vol, ouvrant des perspectives en matiĂšre dâadaptation passive de forme. ABSTRACT : An aircraft encounters a wide range of operating conditions during its missions, i.e. flight altitude, Mach number and angle of attack, which consideration at the design phase enhances the system robustness and consequently the overall fleet consumption. Numerical optimization of aerodynamic shapes contributes to aircraft design, and relies on the automation of geometry generation and numerical simulations of the flight physics. Minimization of aerodynamic shapes drag must take into account multiple operating conditions, since optimization at a single operating condition leads to a strong degradation of performance when this operating condition varies. Besides, structural flexibility deforms the wings differently depending on the operating conditions, so has to be simulated during such optimizations. In the present thesis, the mission fuel consumption minimization is formulated as an optimization problem.
The focus is made on the choice of operating conditions to be included in the optimization problem, since they have a major impact on the quality of the results, and the computational cost is proportional to their number. A new theoretical framework is proposed, overcoming and giving new insights on problematic situations revealed by state-of-the-art methods for multipoint optimization problem setup. An algorithm called Gradient Span Analysis is proposed to automate the choice of operating conditions. It is based on a reduction of dimension of the vector space spanned by adjoint gradients obtained at the different operating conditions. Programming contributions to the optimization chain enabled the evaluation of the new method on the optimizations of the academic RAE2822 airfoil, and the XRF-1 wing-body configuration, representative of a modern transport aircraft. While the shapes resulting of single-point optimizations present strong degradations of the performance in off-design conditions, adequately formulated multi-Machmulti- lift optimizations present much more interesting performance compromises. It is finally shown that fluid-structure interaction adds new degrees of freedom, and has consequences on multiple flight conditions optimizations, opening the perspective of passive shape adaptation
On the Consequences of the "No Free Lunch" Theorem for Optimization on the Choice of an Appropriate MDO Architecture
Multidisciplinary design optimization (MDO) based on high- delity models is challenging due to the high computational cost of evaluating the objective and constraints. To choose the best MDO architecture, a trial-and-error approach is not possible due to the high cost of the overall optimization and complexity of the implementation. We propose to address this issue by developing a generic methodology that applies to any (potentially expensive) physical problem and generates a scalable approximation that can be quickly computed, for which the input and output dimensions may be set independently. This facilitates evaluation of MDO architectures for the original MDO problem by capturing its structure and behavior. The methodology is applied to two academic MDO test cases: the Supersonic Business Jet problem and the propane combustion problem. Well-known architectures (MDF, IDF and BLISS) are benchmarked on various instances to demonstrate the dependency between the performance of the architecture and the problem dimensions
Controlled Emissivity Coatings to Delay Ignition of Polyethylene
International audienceSemi-opaque to opaque films containing small amounts of various aluminium particles to decrease emissivity were easily prepared and coated onto low-density polyethylene (LDPE) sheets. The thermal-radiative properties (reflectivity, transmissivity and absorptivity) of the films were measured and related to the aluminum particles' content, size and nature. Time-to-ignition of samples was assessed using a cone calorimeter at different heat flux values (35, 50 and 75 kW/m 2). The coatings allowed significant ignition delay and, in some cases, changed the material behaviour from thermally thin to thick behaviour. These effects are related both to their emissivity and transmissivity. A lower emissivity, which decreases during the degradation, and a lower transmissivity are the key points to ensure an optimal reaction-to-fire
A Multidisciplinary Airplane Research Integrated Library With Applications To Partial Turboelectric Propulsion
International audienc
Biodereplication of antiplasmodial extracts: application of the amazonian medicinal plant piper coruscans kunth
Improved methodological tools to hasten antimalarial drug discovery remain of interest, especially when considering natural products as a source of drug candidates. We propose a biodereplication method combining the classical dereplication approach with the early detection of potential antiplasmodial compounds in crude extracts. Heme binding is used as a surrogate of the antiplasmodial activity and is monitored by mass spectrometry in a biomimetic assay. Molecular networking and automated annotation of targeted mass through data mining were followed by mass-guided compound isolation by taking advantage of the versatility and finely tunable selectivity offered by centrifugal partition chromatography. This biodereplication workflow was applied to an ethanolic extract of the Amazonian medicinal plant Piper coruscans Kunth (Piperaceae) showing an IC50 of 1.36 ug/mL on the 3D7 Plasmodium falciparum strain. It resulted in the isolation of twelve compounds designated as potential antiplasmodial compounds by the biodereplication workflow. Two chalcones, aurentiacin (1) and cardamonin (3), with IC50 values of 2.25 and 5.5 uM, respectively, can be considered to bear the antiplasmodial activity of the extract, with the latter not relying on a heme-binding mechanism. This biodereplication method constitutes a rapid, efficient, and robust technique to identify potential antimalarial compounds in complex extracts such as plant extracts
Towards the Industrialization of New MDO Methodologies and Tools for Aircraft Design
An overall summary of the Institute of Technology IRT Saint Exupery MDA-MDO project (Multi-Disciplinary Analysis - Multidisciplinary Design Optimization) is presented. The aim of the project is to develop efficient capabilities (methods, tools and a software platform) to enable industrial deployment of MDO methods in industry. At IRT Saint Exupery, industrial and academic partners collaborate in a single place to the development of MDO methodologies; the advantage provided by this mixed organization is to directly benefit from both advanced methods at the cutting edge of research and deep knowledge of industrial needs and constraints. This paper presents the three main goals of the project: the elaboration of innovative MDO methodologies and formulations (also referred to as architectures in the literature 1) adapted to the resolution of industrial aircraft optimization design problems, the development of a MDO platform featuring scalable MDO capabilities for transfer to industry and the achievement of a simulation-based optimization of an aircraft engine pylon with industrial Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) tools
Aircraft shape optimization for mission performance
Les avions rencontrent de nombreuses conditions dâopĂ©rations au cours de leurs vols, comme le nombre de Mach, lâaltitude et lâangle dâattaque. Leur prise en compte durant la conception amĂ©liore la robustesse du systĂšme et finalement la consommation des flottes dâavions. Lâoptimisation de formes aĂ©rodynamiques contribue Ă la conception des avions, et repose sur lâautomatisation de la gĂ©nĂ©ration de gĂ©omĂ©tries ainsi que la simulation numĂ©rique de la physique du vol. La minimisation de la trainĂ©e des formes aĂ©rodynamiques doit prendre en compte de multiples conditions dâopĂ©ration, Ă©tant donne que lâoptimisation a une unique condition de vol mĂšne a des formes dont la performance se dĂ©grade fortement quand cette condition de vol est perturbĂ©e. De plus, la flexibilitĂ© structurelle dĂ©forme les ailes diffĂ©remment selon la condition de vol, et doit donc ĂȘtre simulĂ©e lors de telles optimisations. Dans cette thĂšse, la minimisation de la consommation de carburant au cours dâune mission est formulĂ©e en problĂšme dâoptimisation. Une attention particuliĂšre est apportĂ©e au choix des conditions dâopĂ©rations Ă inclure dans le problĂšme dâoptimisation, Ă©tant donne que celles-ci ont un impact majeur sur la qualitĂ© des rĂ©sultats obtenus, et que le cout de calcul est proportionnel Ă leur nombre. Un nouveau cadre thĂ©orique est proposĂ© pour adresser cette question, offrant un point de vue original et surmontant des difficultĂ©s rĂ©vĂ©lĂ©es par les mĂ©thodes a lâĂ©tat-de-lâ art en matiĂšre de mise en place de problĂšmes dâoptimisation multipoints. Un algorithme appelĂ© Gradient Span Analysis (GSA), est proposĂ© pour automatiser le choix des conditions dâopĂ©ration. Il est base sur la rĂ©duction de dimension de lâespace vectoriel engendre par les gradients adjoints aux diffĂ©rentes conditions de vol. Des contributions de programmation a la chaine dâoptimisation ont permis dâĂ©valuer les mĂ©thodes aux optimisations du profil acadĂ©mique RAE2822 et de la configuration voilure-fuselage XRF-1, reprĂ©sentative des avions de transport modernes. Alors que les formes rĂ©sultant dâoptimisation mono-point prĂ©sentent de fortes dĂ©gradations de performance hors du point de conception, les optimisations multipoints adĂ©quatement formulĂ©es fournissent de bien meilleurs compromis. Il est finalement montre que les interactions fluide-structure ajoutent de nouveaux degrĂ©s de libertĂ©, et ont un impact sur les optimisations en de multiples conditions de vol, ouvrant des perspectives en matiĂšre dâadaptation passive de forme.An aircraft encounters a wide range of operating conditions during its missions, i.e. flight altitude, Mach number and angle of attack, which consideration at the design phase enhances the system robustness and consequently the overall fleet consumption. Numerical optimization of aerodynamic shapes contributes to aircraft design, and relies on the automation of geometry generation and numerical simulations of the flight physics. Minimization of aerodynamic shapes drag must take into account multiple operating conditions, since optimization at a single operating condition leads to a strong degradation of performance when this operating condition varies. Besides, structural flexibility deforms the wings differently depending on the operating conditions, so has to be simulated during such optimizations. In the present thesis, the mission fuel consumption minimization is formulated as an optimization problem. The focus is made on the choice of operating conditions to be included in the optimization problem, since they have a major impact on the quality of the results, and the computational cost is proportional to their number. A new theoretical framework is proposed, overcoming and giving new insights on problematic situations revealed by state-of-the-art methods for multipoint optimization problem setup. An algorithm called Gradient Span Analysis is proposed to automate the choice of operating conditions. It is based on a reduction of dimension of the vector space spanned by adjoint gradients obtained at the different operating conditions. Programming contributions to the optimization chain enabled the evaluation of the new method on the optimizations of the academic RAE2822 airfoil, and the XRF-1 wing-body configuration, representative of a modern transport aircraft. While the shapes resulting of single-point optimizations present strong degradations of the performance in off-design conditions, adequately formulated multi-Machmulti- lift optimizations present much more interesting performance compromises. It is finally shown that fluid-structure interaction adds new degrees of freedom, and has consequences on multiple flight conditions optimizations, opening the perspective of passive shape adaptation
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