Theoretical analysis of the spatial variability in tillage forces for fatigue analysis of tillage machines

This paper presents a new theoretical model to describe the spatial variability in tillage forces for the purpose of fatigue analysis of tillage machines. The proposed model took into account both the variability in tillage system parameters (soil engineering properties, tool design parameters and operational conditions) and the cyclic effects of mechanical behavior of the soil during failure ahead of tillage tools on the spatial variability in tillage forces. The stress-based fatigue life approach was used to determine the life time of tillage machines, based on the fact that the applied stress on tillage machines is primarily within the elastic range of the material. Stress cycles with their mean values and amplitudes were determined by the rainflow algorithm. The damage friction caused by each cycle of stress was computed according to the Soderberg criterion and the total damage was calculated by the Miner's law. The proposed model was applied to determine the spatial variability in tillage forces on the shank of a chisel plough. The equivalent stress history resulted from these forces were calculated by means of a finite element model and the Von misses criterion. The histograms of mean stress and stress amplitude obtained by the rainflow algorithm showed significant dispersions. Although the equivalent stress is smaller than the yield stress of the material, the failure by fatigue will occur after a certain travel distance. The expected distance to failure was found to be df=0.825×106km. It is concluded that the spatial variability in tillage forces has significant effect on the life time of tillage machines and should be considered in the design analysis of tillage machines to predict the life time. Further investigations are required to correlate the results achieved by the proposed model with field tests and to validate the proposed assumptions to model the spatial variability in tillage force

Reliability-based design optimization of shank chisel plough using optimum safety factor strategy

Reliability integration into tillage machine design process is a new strategy to overcome the drawbacks of classical design approaches and to achieve designs with a required reliability level. Furthermore, design optimization of soil tillage equipments under uncertainty seeks to design structures which should be both economic and reliable. The originality of this research is to develop an efficient methodology that controls the reliability levels for complex statistical distribution cases of random tillage forces. This developed strategy is based on design sensitivity concepts in order to determine the influence of each random parameter. The application of this method consists in taking into account the uncertainties on the soil tillage forces. The tillage forces are calculated in accordance with analytical model of McKyes and Ali with some modifications to include the effect of both soil–metal adhesion and tool speed. The different developments and applications show the importance of the developed method to improve the performance of the soil tillage equipments considering both random geometry and loading parameters. The developed method so-called OSF (Optimum Safety Factor) can satisfy a required reliability level without additional computing time relative to the deterministic design optimization study. Since the agricultural equipment parameters are extremely nonlinear, we extended the OSF approach to several nonlinear probabilistic distributions such as lognormal, uniform, Weibull and Gumbel probabilistic distribution laws

Identification probabiliste des paramètres élastiques d'un circuit imprimé

Les systèmes mécatroniques embarqués sont soumis à des vibrations provoquant la rupture des joints brasés par fatigue. L'estimation de la durée de vie en fatigue est liée à la connaissance des propriétés dynamiques des matériaux du circuit imprimé. Dans cette communication l'identification du modèle probabiliste est effectuée à partir de mesures expérimentales réalisées par la technique de vibrométrie à balayage laser 3D. En outre, le problème inverse probabiliste vise à quantifier les incertitudes des propriétés des matériaux afin de mieux évaluer l'aléa de la réponse du modèle numériqu

Modélisation et étude numérique de la pollution de la nappe phréatique

Une méthode numérique pour la simulation dynamique du transfert de masse dans le sol, causant la dégradation de la qualité des eaux souterraines est développée. Pour se faire, la méthode des différences finies est utilisée pour résoudre le problème et prévoir le profil des pressions, des vitesses de filtration, des saturations en eau et de la concentration du soluté.Modelisation and numerical study of groundwater pollutionA numerical method for the dynamic simulation of mass transfert in the ground wich participate in groudwater pollution is developed. To that purpose, the finite difference method is used to solve the solution of a system and in order to know profiles of pressure, filtrate velocity, water saturation and solute concentration

Reliability assessment of automotive components under fatigue using numerical simulation and accelerated testing

In this paper, a Stochastic Response Surface (SRS) approach based on Polynomial Chaos Expansion (PCE) is used to conduct reliability analysis of automotive components subjected to fatigue loading. The PCE coefficients have been computed by regression analysis based on a quasi-random experimental design. In addition, an efficient truncation technique, namely low-rank index sets, has been used to reduce the number of unknown coefficients to be estimated, and consequently to reduce the number of finite element model calls required for the construction of the PCE. Once the PCE is obtained, the probability of failure for a target fatigue life is estimated by applying Monte-Carlo simulations. At the same time, fatigue accelerated testing are conducted on full scale automotive component to obtain experimental predictions of the structural reliability. The estimates of the probability of failure are in good agreement with those obtained by numerical computations based on PCE and Monte-Carlo simulations