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Adhesive bonding provides a versatile strategy for joining metallic as well as non-metallic substrates, and also offers the functionality for joining dissimilar materials. In the design of unibody vehicles for NVH (Noise, Vibration and Harshness) performance, adhesive bonding of sheet metal parts along flanges can provide enhanced stiffening of body-in-white (BIW) leading to superior vibration resistance at low frequencies and improved acoustics due to sealing of openings between flanges. However, due to the brittle nature of adhesives, they remain susceptible to failure under impact loading conditions. The viability of structural adhesives as a sole or predominant mode of joining stamped sheet metal panels into closed hollow sections such as hat-sections thus remains suspect and requires further investigation.

Triggered explosions are increasingly becoming common in the world today leading to the loss of precious lives under the most unexpected circumstances. In most scenarios, ordinary citizens are the targets of such attacks, making it essential to design countermeasures in open areas as well as in mobility systems to minimize the destructive effects of such explosive-induced blasts. It would be rather difficult and to an extent risky to carry out physical experiments mimicking blasts in real world scenarios. In terms of mechanics, the problem is essentially one of fluid-structure interaction in which pressure waves in the surrounding air are generated by detonating an explosive charge which then have the potential to cause severe damage to any obstacle on the path of these high-energy waves.

Recent experimental studies on the behavior of adhesively-bonded steel double-hat section components under axial impact loading have produced encouraging results in terms of load-displacement response and energy absorption when compared to traditional spot-welded hat- sections. However, it appears that extremely limited study has been carried out on the behavior of such components under transverse impact loading keeping in mind applications such as automotive body structures subject to lateral/side impact. In the present work, lateral impact studies have been carried out in a drop-weight test set-up on adhesively-bonded steel double-hat section components and the performance of such components has been compared against their conventional spot-welded and hybrid counterparts. It is clarified that hybrid components in the present context refer to adhesively-bonded hat-sections with a few spot welds only aimed at preventing catastrophic flange separations.

The present work is concerned with the objective of design optimization of an automotive front end structure meeting both occupant and pedestrian safety requirements. The main goal adopted here is minimizing the mass of the front end structure meeting the safety requirements without sacrificing the performance targets. The front end structure should be sufficiently stiff to protect the occupant by absorbing the impact energy generated during a high speed frontal collision and at the same time it should not induce unduly high impact loads during a low speed pedestrian collision. These two requirements are potentially in conflict with each other; however, there may exist an optimum design solution, in terms of mass of front end structure, that meets both the requirements.

The present work is concerned with the objective of developing a process for practical multi-disciplinary design optimization (MDO). The main goal adopted here is to minimize the weight of a vehicle body structure meeting NVH (Noise, Vibration and Harshness), durability, and crash safety targets. Initially, for simplicity a square tube is taken for the study. The design variables considered in the study are width, thickness and yield strength of the tube. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value. The optimum solution is then obtained by using traditional gradient-based search algorithm functionality “fmincon” in commercial Matlab package.

An attractive strategy for joining metallic as well as non-metallic substrates through adhesive bonding. This technique of joining also offers the functionality for joining dissimilar materials. However, doubts are often expressed on the ability of such joints to perform on par with other mechanical fastening methodologies such as welding, riveting, etc. In the current study, adhesively-bonded single lap shear (SLS), double lap shear (DLS) and T-peel joints are studied initially under quasi-static loading using substrates made of a grade of mild steel and an epoxy-based adhesive of a renowned make (Huntsman). Additionally, single lap shear joints comprised of a single spot weld are tested under quasi-static loading. The shear strengths of adhesively-bonded SLS joints and spot-welded SLS joints are found to be similar. An important consideration in the deployment of adhesively bonded joints in automotive body structures would be the performance of such joints under impact loading.

The present work is concerned with the objective of multi disciplinary design optimization (MDO) of an automotive front end structure using truncated finite element model. A truncated finite element model of a real world vehicle is developed and its efficacy for use in design optimization is demonstrated. The main goal adopted here is minimizing the weight of the front end structure meeting NVH, durability and crash safety targets. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value.

Hat sections, single and double, made of steel are frequently encountered in automotive body structural components such as front rails, B-Pillar, and rockers of unitized-body cars. These components can play a significant role in terms of impact energy absorption during collisions thereby protecting occupants of vehicles from severe injury. Modern vehicle safety design relies heavily on computer-aided engineering particularly in the form of explicit finite element analysis tools such as LS-DYNA for virtual assessment of crash performance of a vehicle body structure. There is a great need for the analysis-based predictions to yield close correlation with test results which in turn requires well-proven modeling procedures for nonlinear material modeling with strain rate dependence, effective representation of spot welds, sufficiently refined finite element mesh, etc.

Multidisciplinary Design Optimization (MDO) is of great significance in the lean design of vehicles. The present work is concerned with the objective of cross-functional optimization (i.e. MDO) of automotive body. For simplicity, the main goal adopted here is minimizing the weight of the body meeting NVH and crash safety targets. The stated goal can be achieved following either of two different ways: classic response surface method (RSM) and practical MDO methodology espoused recently. Even though RSM seems to be able to find a design point which satisfies the constraints, the problem is with the time associated with running such CAE algorithms that can provide a single optimal solution for multi-disciplinary areas such as NVH and crash safety.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

Space frame type vehicle construction with extruded aluminum members holds promise in terms of desirable vibration-resistant and crashworthiness characteristics. Efficient design of such vehicles for superior frontal crash performance can be accomplished by judicious use of validated finite element and lumped parameter modeling and analysis. However, design iterations can be reduced considerably by employing energy-absorption targets for key members such as front rails in arriving at the initial design concept. For the NCAP (New Car Assessment Program) test procedure, a constraint is laid in terms of achieving a desirable level of vehicle peak deceleration for occupant safety. Using the information obtained through analysis, a numerical target can be set for energy to be absorbed by front rails. For this energy target, a new relationship is then derived which can be utilized for preliminary design of rail cross-section and material strength.

Vehicle side impact performance is potentially affected by a large number of parameters which may be related to body stiffness and energy absorption characteristics, and packaging dimensions. An understanding of the principal variables controlling TTI (Thoracic Trauma Index) is fundamental to the achievement of high LINCAP (Lateral Impact New Car Assessment Program) rating especially for sedans. In the present study, the effects on TTI of the following are considered: response-related parameters such as velocity and intrusion (which are in turn related to body structure), countermeasures such as side airbag, and dummy to structure clearance dimensions. With the help of test data gathered from side impact tests carried out on cars and trucks at Ford, a new “best subset” regression model is developed and is shown to be able to predict TTI for a number of LINCAP tests which were not part of the suite used in the derivation of the model.