SAE International celebrates Women's History Month by spotlighting female engineers who are paving the way for the aerospace, automotive, and commercial vehicle industries.
This SAE Recommended Practice provides minimum performance requirements and uniform laboratory procedures for fatigue testing of disc wheels, demountable rims, and bolt-together divided wheels intended for normal highway use on military trucks, buses, truck-trailers, and multipurpose vehicles. Users may establish design criteria exceeding the minimum performance requirement for added confidence in a design. For other (non-military) wheels and rims intended for normal highway use on trucks and buses, refer to SAE J267. For wheels intended for normal highway and temporary use on passenger cars, light trucks, and multipurpose vehicles, refer to SAE J328. For wheels used on trailers drawn by passenger cars, light trucks, or multipurpose vehicles, refer to SAE J1204. This document does not cover off-highway or other special application wheels and rims.
Explore what’s next in the world of mobility by discovering the latest standards, technical advancements, professional development and networking opportunities here
Abstract - The Warrior Injury Assessment Manikin (WIAMan) was developed to assess injury in Live Fire Test and Evaluation (LFTE) and laboratory development tests of vehicles and vehicle technologies subjected to underbody blast (UBB) loading. While UBB events impart primarily vertical loading, the occupant location in the vehicle relative to the blast can result in some inherent non-vertical, or off-axis loading. In this study, the WIAMan Technology Demonstrator (TD) was subjected to 18 tests with a 350g, 5-ms time duration drop tower pulse using an original equipment manufacturer (OEM) energy attenuating seat in four conditions: purely vertical, 15° forward tilt, 15° rearward tilt, and 15° lateral tilt to simulate the partly off-axis loading of an UBB event. The WIAMan TD showed no signs of damage upon inspection. Time history data indicates the magnitude, curve shape, and timing of the response data were sensitive to the off-axis loading in the lower extremity, pelvis, and spine.
Vehicle navigation in off-road environments is challenging due to terrain uncertainty, various approaches have been investigated that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using infrared seekers in combat missions. This work is developing a vehicle infrared signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the Delta-TRSS vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner.
We describe how we apply the SAE AS 5506 Architecture and Analysis Design Language (AADL) [4] to reason about contextual and architectural concerns for cyber security. A system’s cyber security certification requires verification that the system’s cyber security mechanisms are correct, non-bypassable, and tamper-resistant. We can verify correctness by examining the mechanism itself, but verifying the other qualities requires us to examine the context in which that mechanism resides. Understanding that context and validating the system’s evolving design against that context is an objective for the Architecture Centric Virtual Integration Process (ACVIP), an AADL-based approach to model and detect system design defects before they become too costly to fix. We describe our work to apply AADL to assess non-bypassability and tamper-resistance. The results of our research - tool plugins for cyber security architectural validation - support system developers today in their ACVIP activities.
Game-changing opportunities abound for the application of vehicle health management (VHM) across multiple transportation-related sectors, but key unresolved issues continue to impede progress. VHM technology is based upon the broader field of advanced analytics. Much of traditional analytics efforts to date have been largely descriptive in nature and offer somewhat limited value for large-scale enterprises. Analytics technology becomes increasingly valuable when it offers predictive results or, even better, prescriptive results, which can be used to identify specific courses of action. It is this focus on action which takes analytics to a higher level of impact, and which imbues it with the potential to materially impact the success of the enterprise. Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.
The “holy grail” for prognostics and health management (PHM) professionals in the aviation sector is to have integrated vehicle health management (IVHM) systems incorporated into standard aircraft maintenance policies. Such a change from current aerospace industry practices would lend credibility to this field by validating its claims of reducing repair and maintenance costs and, hence, the overall cost of ownership of the asset. Ultimately, more widespread use of advanced PHM techniques will have a positive impact on safety and, for some cases, might even allow aircraft designers to reduce the weight of components because the uncertainty associated with estimating their predicted useful life can be reduced. We will discuss how standard maintenance procedures are developed, who the various stakeholders are, and – based on this understanding - outline how new PHM systems can gain the required approval to be included in these standard practices.
While the pandemic continues, aerospace companies are rising to embrace new and emerging challenges at a time when there’s so much innovation. This innovation can be seen in the emergence of urban air mobility (UAM), the rebirth of supersonic flight, the drive towards a “zero emission” aircraft, and the continued use of autonomous drones for delivery, freight, search & rescue, and defense. There are exciting new developments in space as companies are developing products for commercial exploration and space tourism, and new ways to launch satellites. A new generation of engineering is also emerging in the defense sector and its development of not only aircraft, but also ships, tankers, and even flight trainers.
In recent years, the increasing complexity of modern aerospace systems has driven the rapid adoption of robust Model-Based Systems Engineering (MBSE). MBSE is a development methodology centered around computational models, which are instrumental in supporting the design and analysis of intricate systems. In this context, the Architecture Analysis and Design Language (AADL) and Systems Modeling Language (SysML) are two prominent modeling languages for specifying and analyzing the structure and behavior of a cyber-physical system. Both languages have their own specific use cases and tool environments and are typically employed to model different aspects of system design. Although multiple software tools are available for transforming models from one language to another, their effectiveness is limited by fundamental differences in the semantics of each language.
No longer “20 years in the future,” hydrogen and fuel cells are a vital, high-growth solution for carbon reduction across the transportation and other industry sectors.
Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.
Advancements in electric vertical takeoff and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry. One particularly promising application involves on-demand, rapid-response use cases to broaden first responders, police, and medical transport mission capabilities. With the dynamic and varying public service operations, eVTOL aircraft can offer potentially cost-effective aerial mobility components to the overall solution, including significant lifesaving benefits.
Leadership is about more than making effective strategic decisions for business outcomes. It is also about creating a positive workplace in which leaders can adapt to change and manage conflicts effectively. Leaders can build skills that can develop their presence by adopting the mindset of an improv actor. This means learning and practicing how to show up and be ready – ready to lead, to influence, and to contribute whether things go the way they are expected or not. And to have leadership presence: something that builds the trust we need to work together through good times and bad.