Ageing simulation of a hydraulic engine mount: a data informed finite element approach

Hydraulic engine mounts are key elements in an automotive vehicle suspension system that typically experience a change of their designed function during their working lifetime due to progressive material ageing, primarily from the elastomeric component. Ageing of the engine mount, resulting from severe and continuous mechanical and thermal loads, can have a detrimental impact on the ride and comfort and long-term customer satisfaction. This paper introduces a new practical methodology for simulating the ageing behaviour of engine mounts resulting from the change in properties of their elastomeric main spring component. To achieve this, a set of dynamic mechanical thermal analysis tests were conducted on elastomeric coupons taken from a set of engine mounts with different service and ageing conditions. These experimental results were used to characterise the change in mechanical response of the elastomer and to build up an empirical elastomer ageing model. Then a finite element model of the main spring was developed that used the elastomer ageing model so that the ageing behaviour of the engine mount could be simulated. The resulting ageing model was verified by using experimental results from a second batch of ex-service engine mounts. The results show an increasing trend of the vertical static stiffness of the engine mounts with distance travelled (or age) up to a certain distance (approximately 95,000 km). The trend is then reversed and a softening effect is observed. Moreover, the results reveal that both the maximum stiffness value and the distance travelled at the peak stiffness decrease as the temperature increases

Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm

The residual stresses induced during shaping and machining play an important role in determining the integrity and durability of metal components. An important issue of producing safety critical components is to find the machining parameters that create compressive surface stresses or minimise tensile surface stresses. In this paper, a systematic data-driven fuzzy modelling methodology is proposed, which allows constructing transparent fuzzy models considering both accuracy and interpretability attributes of fuzzy systems. The new method employs a hierarchical optimisation structure to improve the modelling efficiency, where two learning mechanisms cooperate together: NSGA-II is used to improve the model’s structure while the gradient descent method is used to optimise the numerical parameters. This hybrid approach is then successfully applied to the problem that concerns the prediction of machining induced residual stresses in aerospace aluminium alloys. Based on the developed reliable prediction models, NSGA-II is further applied to the multi-objective optimal design of aluminium alloys in a ‘reverse-engineering’ fashion. It is revealed that the optimal machining regimes to minimise the residual stress and the machining cost simultaneously can be successfully located

Model fusion using fuzzy aggregation: Special applications to metal properties

To improve the modelling performance, one should either propose a new modelling methodology or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free modelling paradigm is proposed. It does not rely on a fixed structure and can combine various modelling techniques in ‘symbiosis’ using a ‘master fuzzy system’. This approach is shown to be able to include the advantages of different modelling techniques altogether by requiring less training and by minimising the efforts relating optimisation of the final structure. The proposed approach is then successfully applied to the industrial problems of predicting machining induced residual stresses for aerospace alloy components as well as modelling the mechanical properties of heat-treated alloy steels, both representing complex, non-linear and multi-dimensional environments

WiNoCoD : Un réseau d'interconnexion hiérarchique RF pour les MPSoC

International audienceLa multiplication du nombre de cœurs de calcul présents sur les puces va de pair avec une augmentation des besoins en communication. C'est pour palier à ce problème que nous présentons dans cette article un réseau d'interconnexion sur puce utilisant la RF. Nous présentons les raisons du choix de la RF par rapport aux autres nouvelles technologies du domaine que sont l'optique et la 3D, l'architecture détaillée de ce réseau et d'une puce le mettant en œuvre ainsi que l'évaluation de sa faisabilité et de ses performances. Un des avantages potentiels de ce réseau d'interconnexion RF est la possibilité de faire du broadcast à faible coût, ce qui ouvre de nouvelles perspectives notamment en terme de gestion de la cohérence mémoire

Hybrid-modelling of compact tension energy in high strength pipeline steel using a Gaussian Mixture Model based error compensation

In material science studies, it is often desired to know in advance the fracture toughness of a material, which is related to the released energy during its compact tension (CT) test to prevent catastrophic failure. In this paper, two frameworks are proposed for automatic model elicitation from experimental data to predict the fracture energy released during the CT test of X100 pipeline steel. The two models including an adaptive rule-based fuzzy modelling approach and a double-loop based neural network model, relate the load, crack mouth opening displacement (CMOD) and crack length to the released energies during this test. The relationship between how fracture is propagated and the fracture energy is further investigated in greater detail. To improve the performances of the models, a Gaussian Mixture Model (GMM)-based error compensation strategy which enables one monitor the error distributions of the predicted result is integrated in the model validation stage. This can help isolate the error distribution pattern and to establish the correlations with the predictions from the deterministic models. This is the first time a data-driven approach has been used in this fashion on an application that has conventionally been handled using finite element methods or physical models

Mortality after Transplantation for Hepatocellular Carcinoma: A Study from the European Liver Transplant Registry

Background and Aims: Prognosis after liver transplantation differs between hepatocellular carcinoma (HCC) arising in cirrhotic and non-cirrhotic livers and aetiology is poorly understood. The aim was to investigate differences in mortality after liver transplantation between these patients. Methods: We included patients from the European Liver Transplant Registry transplanted due to HCC from 1990 to November 2016 and compared cirrhotic and non-cirrhotic patients using propensity score (PS) calibration of Cox regression estimates to adjust for unmeasured confounding. Results: We included 22,787 patients, of whom 96.5% had cirrhosis. In the unadjusted analysis, non-cirrhotic patients had an increased risk of overall mortality with a hazard ratio (HR) of 1.37 (95% confidence interval [CI] 1.23-1.52). However, the HR approached unity with increasing adjustment and was 1.11 (95% CI 0.99-1.25) when adjusted for unmeasured confounding. Unadjusted, non-cirrhotic patients had an increased risk of HCC-specific mortality (HR 2.62, 95% CI 2.21-3.12). After adjustment for unmeasured confounding, the risk remained significantly increased (HR 1.62, 95% CI 1.31-2.00). Conclusions: Using PS calibration, we showed that HCC in non-cirrhotic liver has similar overall mortality, but higher HCC-specific mortality. This may be a result of a more aggressive cancer form in the non-cirrhotic liver as higher mortality could not be explained by tumour characteristics or other prognostic variables

Optimal anchoring of a foldamer inhibitor of ASF1 histone chaperone through backbone plasticity

Sequence-specific oligomers with predictable folding patterns, i.e., foldamers, provide new opportunities to mimic.-helical peptides and design inhibitors of protein-protein interactions. One major hurdle of this strategy is to retain the correct orientation of key side chains involved in protein surface recognition. Here, we show that the structural plasticity of a foldamer backbone may notably contribute to the required spatial adjustment for optimal interaction with the protein surface. By using oligoureas as. helix mimics, we designed a foldamer/peptide hybrid inhibitor of histone chaperone ASF1, a key regulator of chromatin dynamics. The crystal structure of its complex with ASF1 reveals a notable plasticity of the urea backbone, which adapts to the ASF1 surface to maintain the same binding interface. One additional benefit of generating ASF1 ligands with nonpeptide oligourea segments is the resistance to proteolysis in human plasma, which was highly improved compared to the cognate alpha-helical peptide

Damage in dual phase steel DP1000 investigated using digital image correlation and microstructure simulation

Microstructure failure mechanisms and void nucleation in dual-phase (DP) steels during deformation have been studied using a combination of in situ tensile testing in a scanning electron microscope (SEM), digital image correlation (DIC) and finite element (FE) modelling. SEM images acquired during in situ tests were used to follow the evolution of damage within the microstructure of a DP1000 steel. From these images, strain maps were generated using DIC and used as boundary conditions for a FE model to investigate the stress state of martensite and ferrite before the onset of the martensite phase cracking. Based on the simulation results, a maximum principal stress of about 1700 MPa has been estimated for crack initiation in the martensite of the investigated DP1000 steel. The SEM image observations in combination with the FE analyses provide new insights for the development of physically-based damage models for DP-steels

Experimental and modelling study of fatigue crack initiation in an aluminium beam with a hole under 4-point bending

Slip band formation and crack initiation during cyclic fatigue were investigated by in-situ experiments and non-local CPFEM simulations systematically. Experimental techniques including EBSD, digital image correlation (DIC) and SEM have been used to obtain consistent grain orientations, local strains, as well as the locations where slip bands and micro-cracks form on the sample surface. The realistic microstructure based on the EBSD map has been generated and used for finite element modelling. An advanced non-local crystal plasticity model, which considers the isotropic and kinematic hardening of the plastic strain gradient, has been adopted. The simulation results match well the corresponding experimental results. It was found that total strain and averaged slip on all slip systems, combined with accumulated slip on specific slip planes help predict the location and orientation of slip bands and micro-crack initiation correctly. Furthermore, a fatigue indicating parameter based on competition between maximum slip and the total slip has been proposed to reproduce the experimental observations