Optimisation multi-objectif par l'algorithme des colonies de fourmis

International audienceL'objectif de ce travail est de montrer qu'il est possible de mener l'optimisation multiobjectifs en utilisant un algorithme heuristique aussi performant qu'un Algorithme Génétique (AG), qui est actuellement le plus utilisé dans les solveurs d'optimisation. Il s'agit de l'algorithme d'optimisation basé sur l'approche Pareto (Pareto Ant Colony Optimization : P-ACO). Dans ce papier on montrera à travers l'étude d'une plaque raidie en composite multicouches que l'algorithme P-ACO est aussi performant qu'un AG mais a l'avantage d'être plus aisé à mettre en oeuvre numériquement. La modélisation de la structure composite est réalisée par le code de calcul commercial ANSYS®

Réduction de modèles dynamiques non-linéaires en grands déplacements-Application aux plaques minces

Cet article présente une méthode de réduction adaptée au problème de dynamique non-linéaire. La non-linéarité étudiée est de type géométrique en grands déplacements. L'outil de réduction est basé sur la méthode de combinaison approximée qui consiste à construire une base de série binomiale actualisée. Cette base est issue du comportement non-linéaire traduit comme une modification du modèle linéaire. La simulation numérique de la réponse temporelle d'une plaque mince modélisée en éléments finis (MEF) montre l'intérêt de la méthode proposée

UTICAJI PRELAZNIH TEMPERATURSKIH POLJA NA VIŠEPROLAZNO ZAVARIVANJE U SUČEONOM SPOJU AUSTENITNIH CEVI

This work uses computational thermomechanical model-based finite element analysis (FEA) to explore the effects of welding sequences on residual stresses that accumulate in the material and distortions of welded components, which are a direct outcome of residual stresses, the material micro-structures, material properties, and eventually the fracture toughness. The consequences of the welding process are evaluated in this study in an austenitic pipe butt weld.U ovom radu je korišćena računarska termomehanička analiza na bazi modela konačnim elementima (FEA) kako bi se istražili uticaji sekvenci zavarivanja na zaostale napone koji se pojavljuju u materijalu, i deformacije zavarenih delova, koje su direktna posledica zaostalih napona, mikrostrukture materijala, svojstva materijala, kao i žilavosti loma. Posledice postupka zavarivanja su utvrđene u ovom radu kod spoja austenitnih cevi

Numerical study of perforated obstacles effects on the performance of solar parabolic trough collector

The current work presents and discusses a numerical analysis of improving heat transmission in the receiver of a parabolic trough solar collector by introducing perforated barriers. While the proposed approach to enhance the collector’s performance is promising, the use of obstacles results in increased pressure loss. The Computational Fluid Dynamics (CFD) model analysis is conducted based on the renormalization-group (RNG) k-ɛ turbulent model associated with standard wall function using thermal oil D12 as working fluid The thermo-hydraulic analysis of the receiver tube with perforated obstacles is taken for various configurations and Reynolds number ranging from 18,860 to 81,728. The results are compared with that of the receiver without perforated obstacles. The receiver tube with three holes (PO3) showed better heat transfer characteristics. In addition, the Nusselt number (Nu) increases about 115% with the increase of friction factor 5–6.5 times and the performance evaluation criteria (PEC) changes from 1.22 to 1.24. The temperature of thermal oil fluid attains its maximum value at the exit, and higher temperatures (462.1 K) are found in the absorber tube with perforated obstacles with three holes (PO3). Accordingly, using perforated obstacles receiver for parabolic trough concentrator is highly recommended where significant enhancement of system’s performance is achieved

Cross electromagnetic nanofluid flow examination with infinite shear rate viscosity and melting heat through Skan-Falkner wedge

This demonstration of study focalizes the melting transport and inclined magnetizing effect of cross fluid with infinite shear rate viscosity along the Skan-Falkner wedge. Transport of energy analysis is brought through the melting process and velocity distribution is numerically achieved under the influence of the inclined magnetic dipole effect. Moreover, this study brings out the numerical effect of the process of thermophoresis diffusion and Brownian motion. The infinite shear rate of viscosity model of cross fluid reveals the set of partial differential equations (PDEs). Similarity transformation of variables converts the PDEs system into nonlinear ordinary differential equations (ODEs). Furthermore, a numerical bvp4c process is imposed on these resultant ODEs for the pursuit of a numerical solution. From the debate, it is concluded that melting process cases boost the velocity of fluid and velocity ratio parameter. The augmentation of the minimum value of energy needed to activate or energize the molecules or atoms to activate the chemical reaction boosts the concentricity inclined magnetized flow, infinite shear rate viscosity, Brownian motion, 2-D cross fluid, melting process of energy, thermophoresis diffusion melting of energy.Campus Chiclay

Synthèse modale non-linéaire par une méthode d'approximations combinées généralisée

International audienceSynthèse modale non-linéaire par une méthode d'approximations combinées généralisé

The coupling of robust metamodel and heuristic methods in reliability based design optimization

International audienceThe context of this paper is the establishment of help tools to aid in the decisions for robust design of mechanical structures in an uncertain environment. The problem considered is how to determine an optimized structure with regard to the security level criteria. This problem is called reliability optimization; that means the optimization is with regard to the constraint reliability. With a falling probability level, the engineer can decide if the structure has sufficient reliability. This paper presents a coupling between the methods of reliability approximation (FORM, SORM) and a set of modern techniques from the domain of the artificial intelligence which are characterized by their importance in the process of collectionand analysis of the uncertainties. Among these techniques, the particular swarm, the genetic algorithms and the ant colony techniques should be mentioned. In this paper, a coupling of the reliability method and dynamics with metamodels (condensed models) to guide reliability optimization of such systems is proposed. Two numerical examples are presented to illustrate the performance of the proposed approach

Reliability optimization in structural dynamics using the heuristic methods

International audienceReliability optimization in structural dynamics using the heuristic method

Reanalysis of nonlinear structures by a reduction method of combined approximations

International audienceComplex structure optimization is an important part of the design process where the initial state of the structure is modified, sometimes in a significant way, in order to reach the best possible performance, for a given set of constraints.By exploring as much as possible the design parameter space, optimal solutions (displacements, constraints, eigenmodes, etc.) are then calculated. These successive multiple analysis or reanalysis thus imply a large computation cost which often remains prohibitive. The modifications applied to the structure can be of various types: topological, acting on the form of the structure or its boundary conditions; parametric, acting on the physical parameters of the structure (mass, stiffness, thickness); in a global (whole structure level) or a local way (component level). Therefore, the aim of reanalysis methods [1] is to approximate the responses of a structure whose parameters have been perturbed or even modified without solving the new equilibrium equation system associated to the updated structure: only the initial solutions and the perturbed data are used. Moreover, when the problem is non-linear, the re-actualization of the tangent stiffness matrix at each time step of the Newton-Raphson integration algorithm implies many reanalysis leading to a high computational time. To mitigate these difficulties, one proposes a robust reduction method adapted to non-linear and large sized dynamic models. This study especially focuses on geometrical non-linearities, i.e. large displacements [2]. The presented reduction method is based on the combined approximations method introduced by Kirsch [3,4]