Multidisciplinary design optimisation (MDO) can be used as an effective tool to improve the design of automotive structures. Large-scale MDO problems typically involve several groups who must work concurrently and autonomously in order to make the solution process efficient. In this article, the formulations of existing MDO methods are compared and their suitability is assessed in relation to the characteristics of automotive structural applications. Both multi-level and single-level optimisation methods are considered. Multi-level optimisation methods distribute the design process but are complex. When optimising automotive structures, metamodels are often required to relieve the computational burden of detailed simulation models. The metamodels can be created by individual groups prior to the optimisation process, and thus offer a way of distributing work. Therefore, it is concluded that a single-level method in combination with meta-models is the most straightforward way of implementing MDO into the development of automotive structures. If the benefits of multi-level optimisation methods, in a special case, are considered to compensate for their drawbacks, analytical target cascading has a number of advantages over collaborative optimisation, but both methods are possible choices.

It is essential to account for variations in the manufacturing process and in loading conditions when improving the robustness and reliability of a product’s design. A finite element study of the robustness of a hat profile beam made from boron steel subjected to a three point bending load is presented, and an approach to incorporate the variations investigated is demonstrated. Fracture risk factors and the maximum deflection of the beam are the measured responses. Spatial variation of the sheet thickness is considered in the forming simulations, along with other input variations. Stress-strain relations from tensile tests have been used in the robustness analyses to represent the variation in material properties. Furthermore, validations of four metamodels have been performed. Both the responses measured were found to be sensitive to input variations. Separate metamodels were created for each risk prone zone in order to improve the performance of the metamodels for risk factor responses.

Spot welds are commonly used to join steel sheets in automotive structures. The number and layout of these spot welds are vital for the performance of the structure. However, reducing the number of spot welds will cut both production time and cost. This article presents three different methods of reducing the number of spot welds in automotive structures: ranking-based selection, topology optimization and size optimization of a parameterized model. The methods are compared in a simple example and it is found that the latter two methods have the best potential of reducing the number of spot welds. Topology optimization requires less preparation and computational effort as compared to size optimization of a parameterized model. However, the method is primarily suitable for studies where load cases involving linear systems are judged to be most important. Otherwise, size optimization of a parameterized model is probably a better choice. The topology optimization approach is successfully demonstrated in a full-scale industrial application example and confirms that the method is useful within contemporary product development.

Automotive companies continuously strive to design better products faster and more cheaply using simulation models to evaluate every possible aspect of the product. Multidisciplinary design optimization (MDO) can be used to find the best possible design taking into account several disciplines simultaneously, but it is not yet fully integrated within automotive product development. The challenge is to find methods that fit company organizations and that can be effectively integrated into the product development process. Based on the characteristics of typical automotive structural MDO problems, a metamodel-based MDO process intended for large-scale applications with computationally expensive simulation models is presented and demonstrated in an example. The process is flexible and can easily fit into existing organizations and product development processes where different groups work in parallel. The method is proven to be efficient for the discussed example and improved designs can also be obtained for more complex industrial cases with comparable characteristics.

Optimisation of vehicle design is necessary to meet increased safety requirements, new emission regulations, and to deal with competition in the global market, etc. However, optimised design using classical optimisation techniques with deterministic models might not meet the desired performance level or might fail in extreme events in real life owing to uncertainties in the design parameters and loading conditions. Consequently, it is essential to account for uncertainties in a systematic manner to generate a robust and reliable design. In this paper, an approach to perform multiobjective, reliability-based, and robust design optimisation is presented using a vehicle side impact crashworthiness application. Metamodels have been used in the optimisation process to decrease computational effort. Variations in material properties, thicknesses, loading conditions, and B-pillar heat-affected zone material strength have been considered for the stochastic optimisation. A comparative study of deterministic, reliability-based, and robust optimisation approaches is performed.

Mixed isotropic-distortional hardening allows for individual stress-plastic strain relations in different straining directions. Such hardening can be obtained by allowing the parameters in the effective stress function depend on anisotropy functions of the equivalent plastic strain. A methodology to calibrate these anisotropy functions is proposed in this work, and is demonstrated on an austenitic strainless steel. A high exponent eight parameter effective stress function for plane stress states is utilised. The anisotropy functions are calibrated by the use of experimental data from uniaxial tensile test data in three material directions and a balanced biaxial test. The plastic anisotropy is evaluated at a finite number of plastic strains, and it is assumed to vary piecewise linearly with respect to the equivalent plastic strain. At each level of plastic strain, the anisotropy is correctly represented, even if rather large increments in plastic strain are used in the calibration. It was found that there are at least two sets of anisotropy functions which satisfy the conditions in the calibration procedure. The resulting uniaxial stress-strain relations from the two sets of anisotropy functions in four additional straining directions, not included in the calibration set, were compared to the corresponding experimental data. From this validation, one of the anisotropy function sets could be discarded, whereas the other one gave a good prediction of the stress-strain relations in all the four additional directions. (C) 2015 Elsevier Ltd. All rights reserved.

It is important to understand the strain recovery of a steel sheet in order to predict its springback behaviour. During strain recovery, the stress–strain relation is non-linear and the resulting unloading modulus is decreased. Moreover, the unloading modulus will degrade with increasing plastic pre-straining. This study aims at adding new knowledge on these phenomena and the mechanisms causing them. The unloading behaviour of the dual-phase steel DP600 is characterised experimentally and finite element (FE) simulations of a representative volume element (RVE) of the microstructure are performed. The initial stress and strain state of the micromechanical FE model is found by a simplified simulation of the annealing processes. It is observed from the experimental characterisation that the decrease of the initial stiffness of the unloading is the main reason for the degrading unloading modulus. Furthermore, the developed micromechanical FE model exhibits non-linear strain recovery due to local plasticity caused by interaction between the two phases.

The main objective of this work is to examine the use of anisotropic fracture criteria in order to predict fracture in dual-phase steel. The introduction of a material directional function into the fracture criterion was used in order to account for anisotropy observed in experiments. Selected fracture criteria were fist calibrated by ordinary tensile and in-plane shear tests using specimens cut in three material directions. In order to validate the performance, two types of validation tests were conducted. First, plane strain (notched tensile) tests were carried out in three material directions. Second, Nakajima tests with a waist of 130 mm were conducted, also in three material directions. The fit to the calibration tests was improved with all material directional functions compared to the isotropic criterion. Overall best performance was achieved when a material direction function based on the structural tensors was introduced.

This paper presents a study of two different hybrid composite-aluminum concepts applied to a winglike structure which is exposed to mechanical  and thermal load. The aim of the study is to determine the most suitable  hybrid concept to later on be used in structural fatigue and static testing. In both concepts, the mass is optimized with respect to two different sets of requirements, one of which is currently in use in the fighter aircraft industry and one which is a modified version of the current requirement set. The issues considered in the study are mass, thermal behavior, buckling, bolted joints, failure criteria and fatigue damage, and they are examined in the frame of both requirement sets. The results clearly indicate the order of criticality between the different criteria in the different parts of each concept. Also, the comparison of two requirement sets gives an idea of the degree of influence of the modified criteria on the hybrid concepts and their mass. Based on the mass and the structural behavior in a thermal-mechanical loading one of the hybrid concepts is chosen for further studies and testing.

Failure in ductile sheet metal structures is usually caused by one, or a combination of, ductile tensile fractures, ductile shear fractures or localised instability. In this paper the failure characteristics of the high strength steel Docol 600DP are explored. The study includes both experimental and numerical sections. In the experimental sections, the fracture surface of the sheet subjected to Nakajima tests is studied under the microscope with the aim of finding which failure mechanism causes the fracture. In the numerical sections, finite element (FE) simulations have been conducted using solid elements. From these simulations, local stresses and strains have been extracted and analysed with the aim of identifying the fracture dependency of the stress triaxiality and Lode parameter.