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Abstract Soft actuators with pneumatic network have innovative potential applications in medical and rehabilitation areas. The performance of this kind of actuators is determined by the design of chambers and the properties of the active extensible layer and the passive inextensible layer. In this article, actuator with isosceles trapezoidal chambers is proposed. Orthogonal experiment design and finite element method are used to optimize the structure of actuators. Results indicate that adding constrain-limiting paper in the passive layer can significantly reduce the bending radius. Position of the paper in the passive layer also affects the bending radius. Actuators with trapezoidal chambers can have a smaller bending radius compared with that with rectangle chambers. The bending radius decreases as the ratio of short base to long base of trapezoid decreases. Increasing the number density of chambers can further reduce the bending radius.

To improve the biofidelity of the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD), the National Highway Traffic Safety Administration (NHTSA) has developed the Large Omnidirectional Child (LODC) ATD. The LODC head is a redesigned HIII-10C head with mass properties and modified skin material required to match pediatric biomechanical impact response targets from the literature. A dynamic, nonlinear finite element (FE) model of the LODC head has been developed using the mesh generating tool Hypermesh based on the three-dimensional CAD model. The material data, contact definitions, and initial conditions are defined in LS-PrePost and converted to LS-Dyna solver input format. The aluminum head skull is stiff relative to head flesh material and was thus modeled as a rigid material. For the actual LODC, the head flesh is form fit onto the skull and held in place through contact friction.

Additive manufacturing (AM) technology, also known as 3D printing, has transitioned from concepts and prototypes to part-for-part substitution and the creation of unique AM-specific part geometries. These applications are increasingly present in demanding, mission-critical fields such as medicine and aerospace, which require materials with certain thermal, stiffness, corrosion, and static loading properties. To advance in these arenas, metallic, ceramic, and polymer composite AM parts need to be free from discontinuities. The manufacturing processes have to be stable, robust, and repeatable. And the nondestructive testing (NDT) technology and inspection methods will need to be sufficiently capable and reliable to ensure that discontinuities will be detected to prevent the components from being accepted for use. As the second installment of a six-part series of SAE EDGE™ Research Reports on AM, this one discusses the need, challenges, technologies, and opportunities for NDT in AM.

Under body blast (UBB) loading to military transport vehicles is known to cause foot-ankle fractures to occupants due to energy transfer from the vehicle floor to the feet of the soldier. The soldier posture, the proximity of the event with respect to the soldier, the personal protective equipment (PPE) and age/sex of the soldier are some variables that can influence injury severity and injury patterns. Recently conducted experiments to simulate the loading environment to the human foot/ankle in UBB events (~5ms rise time) with variables such as posture, age and PPE were used for the current study. The objective of this study was to determine statistically if these variables affected the primary injury predictors, and develop injury risk curves. Fifty below-knee post mortem human surrogate (PMHS) legs were used for statistical analysis. Injuries to specimens involved isolated and multiple fractures of varying severity.

Finite Element Analysis (FEA) is a powerful and well recognized tool used in the analysis of heat transfer problems. However, FEA can only analyze solid bodies and, by necessity thermal analysis with FEA is limited to conductive heat transfer. The other two types of heat transfer: convection and radiation must by approximated by boundary conditions. Modeling all three mechanisms of heat transfer without arbitrary assumption requires a combined use of FEA and Computational Fluid Dynamics (CFD).

Finite Element Analysis (FEA) has been an indispensable tool for design simulation for several decades but this wide spread use has been limited to simple types of analyses. Relatively recently, more advanced analyses have given easy-to-use interfaces enabling design engineers to simulate problems formerly reserved for analysts. FEA Beyond Basics targets the FEA users who wish to explore those advanced analysis capabilities. It will demonstrate how to move past the ubiquitous linear structural analysis and solve structural nonlinear problems characterized by nonlinear material, large displacements, buckling or nonlinear connectors.

This standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the BrAC measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.

This SAE Standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the breath alcohol concentration (BrAC) measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.

The experimental investigation aims to improve natural composite materials aligned with feasible development principles. These composites can be exploited across several industries, including the automobile and biomedical sectors. This research employs date seed powder and neem gum powder as reinforcing agents, along with polyester resin as the base material. The fabrication route comprises compression moulding, causing the production of the natural composite material. This study focuses extensively on mechanical characteristics such as tensile strength, flexural strength, hardness, and impact resistance to undergo comprehensive testing. Furthermore, the chemical properties of the composites are examined using the FTIR test to gain understanding by integrating different proportions of date seed powder (5%, 10%, 15%, and 20%) and neem gum powder (0%, 3%, 6%, and 9%) in the matrix phase.

This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Project Management and Advanced Product Quality Planning (APQP) are two critical techniques used in product development in the mobility industry today. This course will bring these techniques together in an easy to understand format that goes beyond the typical concept of constructing timelines and project planning, by exploring not only the Automotive APQP process, but also key aspects of PM processes.

Fatigue is a structural failure mode that must be recognized and understood to develop products that meet life cycle durability requirements. In the age of lightweighting, fatigue strength is an important vehicle design requirement as engineers struggle to meet stringent weight constraints without adversely impacting durability. This technical concept course introduces the fatigue failure mode and analysis methods. It explains the physics of material fatigue, including damage accumulation that may progress to product failure over time, and it provides the needed foundation to develop effective fatigue prediction capabilities.