Cette thèse s’inscrit dans le cadre des travaux menés par PSA Peugeot Citroën pour l’allègement de ses véhicules. Les optimisations masse multi-prestations réalisées sur le périmètre de la structure contribuent directement à cette démarche en recherchant une allocation d’épaisseurs de tôles à masse minimale qui respectent des spécifications physiques relatives à différentes prestations (choc, vibro-acoustique, etc.). Ces spécifications sont généralement évaluées à travers des modèles numériques à très haute-fidélité qui présentent des temps de restitution particulièrement élevés. Le recours à des fonctions de substitution, connues sous le nom de métamodèles, reste alors la seule alternative pour mener une étude d’optimisation tout en respectant les délais projet. Cependant la prestation qui nous intéresse, à savoir le choc frontal, présente quelques particularités (grande dimensionnalité, fortes non-linéarités, dispersions physique et numérique) qui rendent sa métamodélisation difficile.L’objectif de la thèse est alors de proposer une approche d’optimisation basée sur des métamodèles adaptatifs afin de dégager de nouveaux gains de masse. Cela passe par la prise en compte du choc frontal dont le caractère chaotique est exacerbé par la présence d’incertitudes. Nous proposons ainsi une méthode d’optimisation fiabiliste avec l’introduction de quantiles comme mesure de conservatisme. L’approche est basée sur des modèles de krigeage avec enrichissement adaptatif afin de réduire au mieux le nombre d’appels aux modèles éléments finis. Une application sur un véhicule complet permet de valider la méthode. / One of the most challenging tasks in modern engineering is that of keeping the cost of manufactured goods small. With the advent of computational design, prototyping for instance, a major source of expenses, is reduced to its bare essentials. In fact, through the use of high-fidelity models, engineers can predict the behaviors of the systems they design quite faithfully. To be fully realistic, such models must embed uncertainties that may affect the physical properties or operating conditions of the system. This PhD thesis deals with the constrained optimization of structures under uncertainties in the context of automotive design. The constraints are assessed through expensive finite element models. For practical purposes, such models are conveniently substituted by so-called surrogate models which stand as cheap and easy-to-evaluate proxies. In this PhD thesis, Gaussian process modeling and support vector machines are considered. Upon reviewing state-of-the-art techniques for optimization under uncertainties, we propose a novel formulation for reliability-based design optimization which relies on quantiles. The formal equivalence of this formulation with the traditional ones is proved. This approach is then coupled to surrogate modeling. Kriging is considered thanks to its built-in error estimate which makes it convenient to adaptive sampling strategies. Such an approach allows us to reduce the computational budget by running the true model only in regions that are of interest to optimization. We therefore propose a two-stage enrichment scheme. The first stage is aimed at globally reducing the Kriging epistemic uncertainty in the vicinity of the limit-state surface. The second one is performed within iterations of optimization so as to locally improve the quantile accuracy. The efficiency of this approach is demonstrated through comparison with benchmark results. An industrial application featuring a car under frontal impact is considered. The crash behavior of a car is indeed particularly affected by uncertainties. The proposed approach therefore allows us to find a reliable solution within a reduced number of calls to the true finite element model. For the extreme case where uncertainties trigger various crash scenarios of the car, it is proposed to rely on support vector machines for classification so as to predict the possible scenarios before metamodeling each of them separately.

Collision avoidance systems have become an integrated part of modern vehicles and aim to avoid accidents or mitigate the crash severity for the occupant. For example, the autonomous emergency braking system influences the pre-crash state of the occupant in sitting posture, stress state, or velocity. The occupant might try to retain its posture by activating muscles, which induce muscle bracing and could counteract the movement of the occupant in the pre-crash phase.  Therefore, it is essential to study the influence of active musculature on occupant response in pre-crash and crash events. A finite element human body model (HBM) with and without closed-loop muscle activation control was used to simulate the occupant response during those events. Comparing the HBM responses & head kinematics reveal an influence of muscle bracing in the evasive braking manoeuvre. Simulating the pre-crash and in-crash phase in two stages can provide multiple benefits. However, the correlation between a single-stage simulation (baseline) and a two-stage simulation needs to be investigated. The baseline simulation uses an active HBM to model an occupant during an evasive braking manoeuvre and the muscles are deactivated when entering the frontal impact phase. The parameters of the final pre-crash state, which are needed to mimic the baseline’s response when transitioning from the pre-crash to the in-crash event are investigated in this study. For that reason, sitting position, stress state and velocity are transferred respectively to the initial passive in-crash HBM state. The simulations enabled the comparison of occupant response and calculation of cross-correlation. Each retainment strategy gave a good cross-correlation with the baseline simulation. / Kollisionsundvikande system har blivit en viktig del i moderna fordon där syftet är att undvika olyckor samt att minska allvarhetsgraden av olyckor för de åkande. Ett exempel är nödbromssystem som kan påverka den åkandes initiala tillstånd direkt före en krock som, till exempel, sittposition, spänningstillstånd, eller initial hastighet inför krock. Den åkande kan försöka att bibehålla sin hållning genom att aktivera sina muskler vilket påverkar rörelsen av dess kropp under för-krocks fasen. Det är därför viktigt att studera hur aktiva muskler påverkar rörelsen av kroppen hos den åkande under både före krocksfasen och själva krockfasen. En finit element humanmodell (HBM) med och utan reglerad muskelaktivitet används för att prediktera responsen hos den åkande i båda faserna. En jämförelse mellan simuleringarna visar att aktiva muskler kan påverka åkandekinematiken under bromsningsförloppet. Att simulera fasen före krock och fasen under krock i två steg kan medföra flera fördelar. Korrelationen mellan en enkelstegssimulering (originalsimulering) och en tvåstegssimulering måste dock studeras. Som originalsimulering används en aktiv HBM för att modellera den åkande under för-krocksfasen där den reglerade muskelaktiviteten inaktiveras under krockfasen. I denna studie undersöks den åkandes initiala tillstånd före krocken som behövs för att efterlikna originalsimulerings respons vid övergången från för-krocksfasen till krockfasen. Av den anledningen mappas det passiva HBM-tillståndet till det slutliga tillståndet av före krocksfasen för sittposition, spänningstillstånd respektive hastighet. Simuleringarna möjliggjorde en jämförelse av åkande respons och beräkning av korskorrelation. Varje mappningsstrategi gav en bra korskorrelation med originalsimuleringen.