Browse Topic: Safety
Emergency evacuation slides (EVAC slides) are critical safety devices used on aircraft to enable rapid egress during emergencies. While these slides provide a quick and reliable escape route, communication between separated slides during evacuation remains a challenge. Often, during raft deployment over water, slides may drift apart impeding communication among evacuees and rescue personnel potentially compromising safety. Existing aircraft EVAC systems lack integrated wireless communication relying on visual or voice signals that are unreliable in chaotic conditions. This paper explores the integration of wireless IoT technology into EVAC slide systems to facilitate inter-slide communication and monitor critical parameters such as slide air pressure and the floating weight of stranded passengers through embedded sensors. It proposes the adoption of Long Range (LoRa) modulation technology for wireless communication chosen for its low-power, long-range performance and license-free
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance
Aircraft verification and certification entail a variety of testing tasks and require coordination among numerous stakeholders across different disciplines to ensure alignment on requirements. Historically, certification strategies have relied on both physical testing and high-fidelity simulation. The integration of these complementary approaches is essential to address their respective blind spots and to support credible certification evidence. A key challenge lies in the rigorous correlation of simulation models with physical test data. Flutter verification, for instance, is a critical component in defining the aircraft’s flight envelope and plays a foundational role in certifying safe operational boundaries. In this work, the process of freedom from flutter verification is demonstrated. This work introduces a novel approach to combining simulation and test data with the aim to accelerate and streamline the verification process leading to more efficient and cost-effective aircraft
This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence
The aerospace industry is undergoing a significant digital transformation in the way system requirements are defined, communicated, and managed. Major OEMs are moving towards fully model-based development processes, with plans to deliver requirements exclusively in the form of models. It is no longer sufficient to manage requirements using traditional document-based approaches; instead, organizations must adopt tools and processes that enable the consumption, interpretation, and implementation of model-based requirements. However, MBSE itself does not ensure that the requirements defined within the model are complete or consistent. Without rigorous validation techniques, even well-structured models can carry forward poorly defined or conflicting requirements — leading to errors that propagate throughout the development lifecycle. This work proposes an approach that integrates formal methods into MBSE workflows by enabling completeness and consistency checks of SysML-based requirements
Since 2019, sex equity in traffic crashes has been a highly debated topic in vehicle safety, especially following the 2019 study by Forman et al. (1) claiming that female occupants face a 73 percent greater risk of serious injury in frontal crashes compared to male occupants. This was soon followed by a Consumer Reports Article by Keith Barry (2), which attempted to identify underlying factors contributing to the higher risk. These have been embraced by several parties since 2019. Firstly, it was alleged that vehicle design practice over the last four decades considered safety for the male population only and ignored that of the female as evidenced by the exclusive use of the mid-sized male Anthropomorphic Test Devices (ATDs) in Regulatory and Safety Ratings tests and not with an average sized female ATD. The absence of such an ATD for testing of vehicles “set the course for four decades’ worth of car safety design, with deadly consequences” (2). Secondly, although there is a
With new energy vehicles developing rapidly, battery safety, as an important part of the impact on the range of new energy vehicles and vehicle safety, has become the focus of attention. The battery pack protection plate is a core component to protect the battery, its performance needs not only impact resistance, but also lightweight, honeycomb sandwich structure with its excellent energy absorption characteristics and weight reduction performance by the battery pack protection plate performance research. At present, the core-to-face sheet interaction in conventional sandwich structures subjected to impact loads has not been fully elucidated, and the quantitative characterization of damage is insufficient, so this paper aims to optimize the lightweight impact-resistant structure by exploring the synergistic energy dissipation mechanism between the high-strength core material and the steel plate. The study combines theory and simulation, adopting ideal rigid-plastic film theory to
Bird accidental collision with overhead transmission lines poses a threat to the ecology of rare bird populations. This article analyzes the warning measures to prevent birds from accidental collisions at home and abroad. In response to the low efficiency of manual installation and the poor static warning effect in preventing birds from accidental collisions with overhead transmission lines, the visual characteristics of birds are analyzed. A drone-based automatic installation flash-type bird accidental collision warning device is proposed, which includes a fixture, a disc, and a luminous circuit. The fixture can be carried and installed on the overhead line by a drone and can be easily disassembled. The disc adopts eye-catching colors and has a hollow structure to reduce wind resistance load. The luminous circuit includes solar panels, charge and discharge control circuits, flicker control circuits, batteries, and luminous components. The drone suspension warning device test was
Active collision avoidance methods are crucial components of vehicle active safety systems, which can effectively prevent collisions or mitigate collision-induced losses. To address the limitations of existing methods, particularly their insufficient foresight in dynamic traffic environments, this paper proposes an active collision avoidance control method based on driving intention recognition and an improved Driving Safety Field (DSF) model to enable more proactive and stable collision avoidance. First, a Hidden Markov Model (HMM) is trained using vehicle trajectory data from a public dataset to accurately identify the driving intentions of the obstacle vehicles, including Lane Change Left (LCL), Lane Keeping (LK), and Lane Change Right (LCR). Then, an improved potential field model is established, which incorporates vehicle acceleration to more comprehensively quantify the driving risk faced by the host vehicle within the DSF model framework. Subsequently, an active collision
This SAE Aerospace Information Report (AIR) supplements ARP4754B/ED-79B by identifying the crucial elements to be considered when constructing the development assurance plans described in Section 3 (Development Assurance Planning) of ARP4754B/ED-79B for integrated systems. Section 4.6.4 of ARP4754B/ED-79B expands the aircraft/system integration and verification activities by emphasizing testing during integration to investigate for unintended behaviors. However, guidelines are needed for planning that are specifically aimed at the aircraft level and at integrating across system functions and boundaries. Until such guidelines are more comprehensively provided, this AIR presents a collection of lessons learned from past certification programs involving integrated systems, and as such it may be considered in conjunction with Sections 3 and 4 of ARP4754B/ED-79B. ARP4761A/ED-135 elaborates the safety activities by adding processes and methods such as the Aircraft or System Functional Hazard
Soft robot systems demonstrate exceptional load-bearing capacity and spatial compliance during operation, with transformative potential in disaster response scenarios requiring adaptive morphology and hazardous material manipulation. By integrating the complementary advantages of soft robotics and particle jamming mechanisms, this study proposes a real-time variable-stiffness soft actuator, while systematically investigating its mathematical modeling framework and stiffness modulation principles. A deformation model for the variable stiffness soft actuator is established, followed by static analysis of the variable-stiffness members using particle jamming theory, with theoretical investigation of their stress distributions. Subsequently, a variable-stiffness driver was fabricated via additive manufacturing (3D printing), resulting in a flexible mechanical digit capable of stiffness tuning, A soft mechanical hand grasping test platform was built, and grasping experiments of objects of
Live-line operation is a critical technique for maintaining the reliability and continuity of power supply in modern distribution networks. Insulating mats serve as essential protective equipment during such operations by providing both electrical insulation and mechanical shielding. In practical service conditions, insulating mats are subjected to repeated mechanical contact and friction against conductors, metallic fittings, and ground surfaces, which progressively deteriorates their surface integrity and compromises operational safety. Current performance standards for insulating mats emphasize dielectric and tensile properties, while tribological durability remains unaddressed. In this study, an EVA – PA6 composite film fabricated via the tape casting method was selected as the representative outer insulating layer of insulating mats. Reciprocating friction tests were conducted using an SDR339 abrasion tester to evaluate the effects of normal load and sliding speed on wear behavior
Letter from the Guest Editor
Letter from the Editor-in-Chief
This document applies to off-road forestry work machines defined in SAE J1116 or ISO 6814.
Items per page:
50
1 – 50 of 20460