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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.

Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

Vehicle safety systems may use occupant physiological information, e.g., occupant heights and weights to further enhance occupant safety. Determining occupant physiological information in a vehicle, however, is a challenging problem due to variations in pose, lighting conditions and background complexity. In this paper, a novel occupant height estimation approach is presented. Depth information from a depth camera, e.g., Microsoft Kinect is used. In this 3D approach, first, human body and frontal face views (restricted by the Pitch and Roll values in the pose estimation) based on RGB and depth information are detected. Next, the eye location (2D coordinates) is detected from frontal facial views by Haar-cascade detectors. The eye-location co-ordinates are then transferred into vehicle co-ordinates, and seated occupant eye height is estimated according to similar triangles and fields of view of Kinect.

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.

Mobility assessment for combat vehicles is often a great challenge for the military due to various subjective attributes. The attributes' characteristics vary significantly depending on the vehicle type and its operating environments such as terrain, weather, and human factors. A clear definition and relationship between multiple attributes including human factors is necessary to assess mobility. To the best of authors' knowledge, many existing mobility assessment techniques use complex analytical methods and focus on individual attributes. In this paper, for the first time, the authors propose a novel approach to define vehicle mobility and its influencing attributes using qualitative linguistic fuzzy variables, which are defined as having values between 0 and 1. The authors also propose a fuzzy logic mobility (FLM) model and a simulation approach to assess a combat vehicle's mobility.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

In a frontal automotive crash, the driver's foot is usually stepping on the brake pedal as an instinctive response to avoid a collision. The tensile force generated in the Achilles tendon produces a compressive preload on the tibia. If there is intrusion of the toe board after the crash, an additional external force is applied to the driver's foot. A series of dynamic impact tests using human cadaveric specimens was conducted to investigate the combined effect of muscle preloading and external force. A constant tendon force was applied to the calcaneus while an external impact force was applied to the forefoot by a rigid pendulum. Preloading the tibia significantly increased the tibial axial force and the combination of these forces resulted in five tibial pylon fractures out of sixteen specimens.

It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.

As advanced electronic technology continues to be integrated into in-vehicle and portable devices, it is important to understand how drivers handle multitasking in order to maintain safe driving while reducing driver distraction. NHTSA has made driver distraction mitigation a major initiative. Currently, several types of Detection Response Tasks (DRTs) for assessing selective attention by detecting and responding to visual or tactile events while driving have been under development by an ISO WG8 DRT group. Among these DRTs, the tactile version (TDRT) is considered as a sensitive surrogate measure for driver attention without visual-manual interference in driving, according to the ISO DRT Draft Standard. In our previous study of cognitive demand, our results showed that the TDRT is the only surrogate DRT task with an acute sensitivity to a cognitive demand increase in an auditory-vocal task (i.e., n-Back verbal working memory task).

Rigid polyurethane (PU) foam finds wide applications as a lightweight material in impact safety design such as improving occupant safety in vehicle crashes. The two principal reacting compounds for formulating such foam are variants of polyol and isocyanate. In the present study, an alternative mechanical engineering-based approach for determining, with confidence, the desirable ratio of reacting compounds for formulation of a rigid/crushable PU foam for mechanical applications is demonstrated. According to the present approach, PU foam samples are prepared by varying the mixing ratio over a wide range. The desirable mixing ratio is shown to be the one that optimizes key mechanical properties under compression such as total absorbed energy, specific absorbed energy and energy absorption efficiency.

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.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

This paper presents experimental investigations of diagnosing and analyzing the low-frequency, low- SNR (Signal to Noise Ratio) noise sources of three motorcycles using a hybrid technology that consists of a passive SODAR (Sonic Detection And Ranging) and modified HELS (Helmholtz Equation Least Squares) methods. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range that is consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, and sound transmission paths through arbitrarily shaped vibrating structures.

A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing industrial tasks. The ability to work alongside humans has increased the importance of collaborative robots in the automation industry, as this unique feature is a much needed property among robots nowadays. Rethink Robotics has pioneered this unique discipline by building many robots including the Baxter Robot which is exclusive not only because it has collaborative properties, but because it has two arms working together, each with 7 Degrees Of Freedom. The main goal of this research is to validate the kinematic equations for the Baxter collaborative robot and develop a unified reconfigurable kinematic model for the Left and Right arms so that the calculations can be simplified.

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.

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 purpose of this study is to provide an understanding of driver kinematics, injury mechanisms and spinal loads causing thoracolumbar spinal fractures in Indianapolis-type racing car drivers. Crash reports from 1996 to 2006, showed a total of forty spine fracture incidents with the thoracolumbar region being the most frequently injured (n=15). Seven of the thoracolumbar fracture cases occurred in the frontal direction and were a higher injury severity as compared to rear impact cases. The present study focuses on thoracolumbar spine fractures in Indianapolis-type racing car drivers during frontal impacts and was performed using driver medical records, crash reports, video, still photographic images, chassis accelerations from on-board data recorders and the analysis tool MADYMO to simulate crashes. A 50th percentile, male, Hybrid III dummy model was used to represent the driver.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. The mechanical properties of the bovine PAC under tensile loading have been characterized previously. However, the transverse properties of this structure, such as shear and normal traction which are equally important to understanding the skull/brain interaction under traumatic loading, have not been investigated. These material properties are essential information needed to adequately define the material model of the PAC in a finite element (FE) model of human brain. The purpose of this study was to determine, experimentally, the material properties of the PAC under normal traction loading. PAC specimens were obtained from freshly slaughtered bovine subjects from various locations.