Este trabalho inicia com uma contextualização histórica e motivação, seguida por revisão bibliográfica nos tópicos discutidos: segurança veicular, crash box, crashworthiness, absorvedores de energia, tubos de impacto, metamodelos, algoritmos genéticos, Planejamento de Experimentos (DoE - Design of Experiments), origami e engenharia, e métodos de otimização na engenharia. Em seguida, o pesquisador propõe um experimento baseado em simulações, avaliando diversas crash box em forma de origami criadas a partir da variação de seus parâmetros dimensionais. Através de um algoritmo baseado em metamodelos, o autor realiza uma análise com o objetivo de maximizar a energia absorvida específica (Specific Energy Absorption - SEA) e a uniformidade de carga (Load Uniformity - LU). A fronteira de Pareto resultante dos dois objetivos é analisada de acordo a exemplos de critérios de decisão, e a configuração escolhida é então comparada a uma crash box da indústria. A configuração escolhida apresenta uma massa quatro vezes menor, e uma uniformidade de carga semelhante à crash box da indústria. Conclui com novas proposições de trabalhos, envolvendo outros métodos de otimização disponíveis. / This research begins with a historical background and motivation, followed by a bibliographic review on the discussed topics: vehicle safety, crash box, crashworthiness, energy absorbers, impact tubes, metamodels, Design of Experiments (DOE), origami and engineering, and optimization in engineering. Next, the researcher proposes a simulation-based experiment, evaluating origami crash boxes created through the variation of several dimensional parameters. Through a metamodel-based algorithm, the author performs an analysis with the objective of maximizing the Specific Energy Absorption (SEA) and the load uniformity (LU). The resultant Pareto frontier of the two objectives is analyzed according to examples of decision criteria, and the chosen design is compared to a crash box from industry. The chosen design presents four times less mass, and a load uniformity similar to the crash box from industry. The research concludes with propositions for new themes, involving other optimization methods available.

Afin de faire face aux nouveaux challenges de l’industrie automobile, les ingénieurs souhaitent appliquer des méthodes d’optimisation à chaque étape du processus de conception. En élargissant l’espace de conception aux paramètres de forme, en augmentant leur nombre et en étendant les plages de variation, de nouveaux verrous sont apparus. C’est le cas de la résistance aux chocs. Avec les temps de calcul long, la non-linéarité, l’instabilité et la dispersion numérique de ce problème de dynamique rapide, la méthode usuellement employée, l’optimisation par plan d’expériences et surfaces de réponse, devient trop coûteuse pour être utilisée industriellement. Se pose alors la problématique suivante : Comment faire de l’optimisation de forme en dynamique rapide avec un nombre élevé de paramètres ?. Pour y répondre, les méthodes d’optimisation par gradient s’avèrent être les plus judicieuses. Le nombre de paramètres a une influence réduite sur le coût de l’optimisation. Elles permettent donc l’optimisation de problèmes ayant de nombreux paramètres. Cependant, les méthodes classiques de calcul du gradient sont peu pertinentes en dynamique rapide : le coût en nombre de simulations et le bruit empêchent l’utilisation des différences finies et le calcul du gradient en dérivant les équations de dynamique rapide n’est pas encore disponible et serait très intrusif vis-à-vis des logiciels. Au lieu de déterminer le gradient, au sens classique du terme, des problèmes de crash, nous avons cherché à l’estimer. L’Equivalent Static Loads Method est une méthode permettant l’optimisation à moindre coût basée sur la construction d’un problème statique linéaire équivalent au problème de dynamique rapide. En utilisant la dérivée du problème équivalent comme estimation du gradient, il nous a été possible d’optimiser des problèmes de dynamique rapide ayant des épaisseurs comme variables d’optimisation. De plus, si l’on construit les équations du problème équivalent avec la matrice de rigidité sécante, l’approximation du gradient n’en est que meilleure. De cette manière, il est aussi possible d’estimer le gradient par rapport à la position des nœuds du modèle de calcul. Comme il est plus courant de travailler avec des paramètres CAO, il faut déterminer la dérivée de la position des nœuds par rapport à ces paramètres. Nous pouvons le faire de manière analytique si nous utilisons une surface paramétrique pour définir la forme et ses points de contrôle comme variables d’optimisation. Grâce à l’estimation du gradient et à ce lien entre nœuds et paramètres de forme, l’optimisation de forme avec un nombre important de paramètres est désormais possible à moindre coût. La méthode a été développée pour deux familles de critères issues du crash automobile. La première est liée au déplacement d’un nœud, objectif important lorsqu’il faut préserver l’intégrité de l’habitacle du véhicule. La seconde est liée à l’énergie de déformation. Elle permet d’assurer un bon comportement de la structure lors du choc. / In order to face their new industrial challenges, automotive constructors wish to apply optimization methods in every step of the design process. By including shape parameters in the design space, increasing their number and their variation range, new problematics appeared. It is the case of crashworthiness. With the high computational time, the nonlinearity, the instability and the numerical dispersion of this rapid dynamics problem, metamodeling techniques become to heavy for the standardization of those optimization methods. We face this problematic: ”How can we carry out shape optimization in rapid dynamics with a high number of parameters ?”. Gradient methods are the most likely to solve this problematic. Because the number of parameters has a reduced effect on the optimization cost, they allow optimization with a high number of parameters. However, conventional methods used to calculate gradients are ineffective: the computation cost and the numerical noise prevent the use of finite differences and the calculation of a gradient by deriving the rapid dynamics equations is not currently available and would be really intrusive towards the software. Instead of determining the real gradient, we decided to estimate it. The Equivalent Static Loads Method is an optimization method based on the construction of a linear static problem equivalent to the rapid dynamic problem. By using the sensitivity of the equivalent problem as the estimated gradient, we have optimized rapid dynamic problems with thickness parameters. It is also possible to approximate the derivative with respect to the position of the nodes of the CAE model. But it is more common to use CAD parameters in shape optimization studies. So it is needed to have the sensitivity of the nodes position with these CAD parameters. It is possible to obtain it analytically by using parametric surface for the shape and its poles as parameters. With this link between nodes and CAD parameters, we can do shape optimization studies with a large number of parameters and this with a low optimization cost. The method has been developed for two kinds of crashworthiness objective functions. The first family of criterions is linked to a nodal displacement. This category contains objectives like the minimization of the intrusion inside the passenger compartment. The second one is linked to the absorbed energy. It is used to ensure a good behavior of the structure during the crash.

Orientador: Marco Lucio Bittencourt / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-09T12:36:20Z (GMT). No. of bitstreams: 1 Martins_DanielLeonardo_M.pdf: 3435063 bytes, checksum: 5e1595f9983245a24712a596e4b1f0a1 (MD5) Previous issue date: 2007 / Resumo: Este trabalho apresenta uma metodologia de otimização de forma aplicada a estruturas submetidas a cargas de impacto, de modo a aumentar sua capacidade de absorção de energia de impacto. Para isso, é necessário conhecer as propriedades mecânicas dos materiais empregados em tais estruturas, as quais são obtidas através de uma metodologia de abordagem dupla experimental- otimização. São obtidos os parâmetros ótimos das leis constitutivas de Cowper-Symonds e Johnson-Cook para materiais sensíveis à taxa de deformação que melhor se ajustam aos respectivos dados experimentais. Finalmente, esses parâmetros são utilizados na análise de uma estrutura complexa, a qual tem sua capacidade de absorção de energia de impacto melhorada utilizando a Metodologia de Resposta da Superfície / Abstract: This work presents a shape optimization methodology applied to structures submitted to impact loads in order to improve their crashworthiness. To this end, it is necessary to know the structural material properties, which were obtained using a dual experimental-optimization methodology. Optimum parameters are obtained for the Cowper-Symonds and Johnson-Cook strain rate sensitive constitutive laws which best fit the material experimental data. These parameters were then used in the analysis of a complex structure, which is crashworthy optimized using a Response Surface Methodology / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

The present research work has been carried out to develop a unified knowledge-based hybrid methodology combining regression-based, lumped parameter and finite element analyses that can be implemented in the initial phase of vehicle design resulting in a superior side crash performance. As a first step, a regression-based model (RBM) is developed between the injury parameter Thoracic Trauma Index (TTI) of the rear SID and characteristic side impact dynamic response variables such as rear door velocity (final) and intrusion supplementing an existing RBM for front TTI prediction. In order to derive the rear TTI RBM, existing public domain vehicle crash test data provided by NHTSA has been used. A computer-based tool with a Graphical User Interface (GUI) has been developed for obtaining possible solution sets of response variables satisfying the regression relations for both front and rear TTI. As a next step in the formulation of the present hybrid methodology for vehicle side impact safety design, a new Lumped Parameter Model (LPM) representing NHTSA side impact is developed. The LPM developed consists of body sub-systems like B-pillar, front door, rear door and rocker (i.e. sill) on the struck side of the vehicle, MDB, and “rest of the vehicle” as lumped masses along with representative nonlinear springs between them. It has been envisaged that for the initial conceptual design to progress, the targets of dynamic response variables obtained from RBM should yield a set of spring characteristics broadly defining the required vehicle side structure. However, this is an inverse problem of dynamics which would require an inordinate amount of time to be solved iteratively. Hence a knowledge-based approach is adopted here to link the two sets of variables i.e., the dynamic response parameters (such as average door and B-pillar velocities, door intrusion, etc.) and the stiffness and strength characteristics of the springs present in LPM. In effect, this mapping is accomplished with the help of an artificial neural network (ANN) algorithm (referred to as ANN_RBM_LPM in the current work). To generate the required knowledge database for ANN_RBM_LPM, one thousand cases of LPM chosen with the help of the Latin Hypercube technique are run with varying spring characteristics. The goal of finding the desired design solutions describing vehicle geometry in an efficient manner is accomplished with the help of a second ANN algorithm which links sets of dynamic spring characteristics with sets of sectional properties of doors, B-pillar and rocker (referred as ANN_LPM_FEM in the current work). The implementation of this approach requires creation of a knowledge database containing paired sets of spring characteristics and sectional details just mentioned. The effectiveness of the hybrid methodology comprising both ANN_RBM_LPM and ANN_LPM_FEM is finally illustrated by improving the side impact performance of a Honda Accord finite element model. Thus, the unique knowledge-based hybrid approach developed here can be deployed in real world vehicle safety design for both new and existing vehicles leading to enormous saving of time and costly design iterations.

This master thesis focuses on a scaled fuselage design made from composite material. The first part deals with a description of composite materials and used material models in an explicit FEM simulation. Two types of scaled structures were designed that were subjected to drop test. Test results were compared with FEM simulation. Finally the calibration of models was carried out.

This study presents mathematical surrogate models, derived from finite element kinematic response data, to predict car crash-induced occupant head and neck injury risk for a broad range of impact velocities (10 – 45 mph), impact locations, and angles of impact (-45° to 45°). The development of these models allowed for wide-scale injury prediction while significantly reducing the overall required number of impact test cases. From these, increases in both the impact velocity and the impact’s locational proximity to the occupant were determined to result in the greatest head and neck injury risks. Additionally, strong interactions between the impact orientation variables (location and angle) produced significant changes in the head injury risk, while the neck injury risk was relatively insensitive to these interactions; likely due to the uniaxiality of the current standard neck injury risk metrics. Overall, this methodology showed potential for future applications in wide-scale injury prediction or vehicular design optimization.

Indiana University-Purdue University Indianapolis (IUPUI) / Crashworthiness design is gaining more importance in the automotive industry due to high competition and tight safety norms. Further there is a need for light weight structures in the automotive design. Structural optimization in last two decades have been widely explored to improve existing designs or conceive new designs with better crashworthiness and reduced mass. Although many gradient based and heuristic methods for topology and topometry based crashworthiness design are available these days, most of them result in stiff structures that are suitable only for a set of vehicle components in which maximizing the energy absorption or minimizing the intrusion is the main concern. However, there are some other components in a vehicle structure that should have characteristics of both stiffness and flexibility. Moreover, the load paths within the structure and potential buckle modes also play an important role in efficient functioning of such components. For example, the front bumper, side frame rails, steering column, and occupant protection devices like the knee bolster should all exhibit controlled deformation and collapse behavior. This investigation introduces a methodology to design dynamically crushed thin-walled tubular structures for crashworthiness applications. Due to their low cost, high energy absorption efficiency, and capacity to withstand long strokes, thin-walled tubular structures are extensively used in the automotive industry. Tubular structures subjected to impact loading may undergo three modes of deformation: progressive crushing/buckling, dynamic plastic buckling, and global bending or Euler-type buckling. Of these, progressive buckling is the most desirable mode of collapse because it leads to a desirable deformation characteristic, low peak reaction force, and higher energy absorption efficiency. Progressive buckling is generally observed under pure axial loading; however, during an actual crash event, tubular structures are often subjected to oblique impact loads in which Euler-type buckling is the dominating mode of deformation. This undesired behavior severely reduces the energy absorption capability of the tubular structure. The design methodology presented in this paper relies on the ability of a compliant mechanism to transfer displacement and/or force from an input to desired output port locations. The suitable output port locations are utilized to enforce desired buckle zones, mitigating the natural Euler-type buckling effect. The problem addressed in this investigation is to find the thickness distribution of a thin-walled structure and the output port locations that maximizes the energy absorption while maintaining the peak reaction force at a prescribed limit. The underlying design for thickness distribution follows a uniform mutual potential energy density under a dynamic impact event. Nonlinear explicit finite element code LS-DYNA is used to simulate tubular structures under crash loading. Biologically inspired hybrid cellular automaton (HCA) method is used to drive the design process. Results are demonstrated on long straight and S-rail tubes subject to oblique loading, achieving progressive crushing in most cases.

Multidisciplinary design optimization (MDO) can be used in computer aided engineering (CAE) to efficiently improve and balance performance of automotive structures. However, large-scale MDO is not yet generally integrated within automotive product development due to several challenges, of which excessive computing times is the most important one. In this thesis, a metamodel-based MDO process that fits normal company organizations and CAE-based development processes is presented. The introduction of global metamodels offers means to increase computational efficiency and distribute work without implementing complicated multi-level MDO methods. The presented MDO process is proven to be efficient for thickness optimization studies with the objective to minimize mass. It can also be used for spot weld optimization if the models are prepared correctly. A comparison of different methods reveals that topology optimization, which requires less model preparation and computational effort, is an alternative if load cases involving simulations of linear systems are judged to be of major importance. A technical challenge when performing metamodel-based design optimization is lack of accuracy for metamodels representing complex responses including discontinuities, which are common in for example crashworthiness applications. The decision boundary from a support vector machine (SVM) can be used to identify the border between different types of deformation behaviour. In this thesis, this information is used to improve the accuracy of feedforward neural network metamodels. Three different approaches are tested; to split the design space and fit separate metamodels for the different regions, to add estimated guiding samples to the fitting set along the boundary before a global metamodel is fitted, and to use a special SVM-based sequential sampling method. Substantial improvements in accuracy are observed, and it is found that implementing SVM-based sequential sampling and estimated guiding samples can result in successful optimization studies for cases where more conventional methods fail.

Accidents involving passenger trains happen regularly in India. The reasons for such accidents could be many; such as weather and flooding, faulty tracks, bridge collapse, collisions caused by signaling errors, mechanical failures, driver error, sabotage etc. The annual accident-related deaths as a percentage of the total number of passengers carried by Indian Railway may seem to be negligible, but the aim should be to achieve zero fatality as every single person killed is an irreplaceable loss to his/her family. It needs to be mentioned that in addition to fatalities for which exact numbers are not available, serious injuries and permanent disabilities caused by train accidents in India at present stand completely unaccounted for. In the absence of a large scale renovation and crash avoidance measures coupled with the propensity to increase the number of trains every year, enhancing passive safety is crucial i.e. crashworthiness and occupant safety of passenger coaches of Indian trains. In the current work, crashworthiness and occupant safety of the existing typical three-tier cabin passenger coach of Indian Railway in an event of collision accident are assessed with the aid of a finite element analysis. In the light of the published work on research in railroad equipment crashworthiness, the current work is intended to envisage the methodology to assess the Indian Railway passenger coach from the point of view of the crashworthiness and occupant safety using CAE (Computer aided engineering) based approach. It is involved with an extensive study of the structural crush behavior of an individual passenger coach car and its effect on the interaction between occupants and the coach interior. Here the structural crush behavior of a typical three-tier cabin passenger coach is evaluated for the head-on impact against a fixed and rigid barrier. The occupant response for the same scenario is also studied which can be viewed as a component of the actual occupant response due to the structural crush behavior of the passenger coach. This can give useful estimates of injury severity and fatalities that may occur in actual accidents. An FE model of the passenger coach structure was built and validated using International Railway Union (UIC) specified code OR 567-design requirements in terms of static loads constituting structural proof cases. These proof cases specify the static load values the coach body structure should withstand without any permanent deformation or failure when applied at the specified locations on the structural ends across the longitudinal axis. In addition, a favorable correlation between the simulation and actual experiment for drop impact behavior of the open section specimens, namely C-section and I-section, was obtained to validate the simulation methodology. LS-DYNA a nonlinear dynamic explicit FE solver was used to carry out all the dynamic impact simulations involved in the current work. The material modeling takes into account the strain rate effect which is essential for the material impact behavior study. The contact modeling was done using penalty contact method. The degrading effect of the buffer on the structural crush patterns which induced the undesirable global bending and jackknifing of the whole coach structure was demonstrated with the help of dynamic impact simulations of the coach structure. The quantification of occupant injury was done by occupant safety simulations using the Hybrid III 50th percentile male dummy FE model. The dummy having been designed for simulating automobile accident scenarios, its contacts had to be adapted to suit the excessive mobility conditions in the coach interior. The dummy was revalidated successfully for the head drop test, pendulum chest impact test, neck flexion and extension test and knee impact test. Impact simulations for three different speeds were performed by positioning the dummy close to the impact point. Injury criteria such as Head Injury Criterion, Chest Deceleration, Knee force level and Neck extension-flexion moments were used to estimate the injury severity level and fatality rate.