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Periprosthetic fractures refer to the fractures that occur in the vicinity of the implants of joint replacement arthroplasty. Most of the fractures during an automotive frontal collision involve the long bones of the lower limbs (femur and tibia). Since the prevalence of persons living with lower limb joint prostheses is increasing, periprosthetic fractures that occur during vehicular accidents are likely to become a considerable burden on health care systems. It is estimated that approximately 4.0 million adults in the U.S. currently live with Total Knee Replacement (TKR) implants. Therefore, it is essential to study the injury patterns that occur in the long bone of a lower limb containing a total knee prosthesis. The aim of the present study is to develop an advanced finite element model that simulates the possible fracture patterns that are likely during vehicular accidents involving occupants who have knee joint prostheses in situ.

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.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

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.

The seatbelt system, originally designed for protecting occupants in frontal crashes, has been reported to be inadequate for preventing occupant head-to-roof contact during rollover crashes. To improve the effectiveness of seatbelt systems in rollovers, in this study, we reviewed previous literature and proposed vertical head excursion corridors during static inversion and dynamic rolling tests for human and Hybrid III dummy. Finite element models of a human and a dummy were integrated with restraint system models and validated against the proposed test corridors. Simulations were then conducted to investigate the effects of varying design factors for a three-point seatbelt on vertical head excursions of the occupant during rollovers. It was found that there were two contributing parts of vertical head excursions during dynamic rolling conditions.

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.

This paper represents the development of a new design methodology based on data mining theory for decision making in vehicle crashworthy components (or parts) development. The new methodology allows exploring the big crash simulation dataset to discover the underlying complicated relationships between vehicle crash responses and design variables at multi-levels, and deriving design rules based on the whole vehicle safety requirements to make decisions towards the component and sub-component level design. The method to be developed will resolve the issue of existing design approaches for vehicle crashworthiness, i.e. limited information exploring capability from big datasets, which may hamper the decision making and lead to a nonoptimal design. A preliminary design case study is presented to demonstrate the performance of the new method. This method will have direct impacts on improving vehicle safety design and can readily be applied to other complex systems.

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.