Browse Topic: Crashes
Youth bicycle helmet manufacturers often add shell protrusions to make helmets more attractive or fun for children, yet the safety implications of these features are not well understood. While prior work suggests protrusions may affect head impact kinematics, no study has evaluated their effectiveness in location-matched impacts between helmets with and without protrusions. Twelve youth bicycle helmet models, with protrusions intact and removed, underwent matched oblique impacts at three locations and 4.2 m/s to capture resulting peak linear acceleration (PLA) and peak rotational acceleration (PRA). A linear mixed model was used to quantify the effect of protrusion presence on PLA, PRA, and impact duration. The youth bicycle helmet models produced a wide range of kinematics. Protrusion presence had a strong effect on PLA, PRA, and impact duration. PLA averaged 103.0 ± 22.8 g for helmets with protrusions compared to 143.9 ± 21.4 g for helmets without protrusions, while PRA averaged 4432 ± 1570 rad/s2 for helmets with protrusions and 5177 ± 2110 rad/s2 for helmets without protrusions. These findings suggest that helmet protrusions can reduce peak head accelerations in youth bicycle helmet impacts.
Letter from the Guest Editors
Modern combat helmets improve wearer survivability through preventing ballistic penetration via delamination or deformation of the shell material. However, this deformation may impinge upon the skull and present a risk of behind-helmet blunt trauma (BHBT). While legacy aramid helmets from the late 1970s–1980s inform current NIJ testing standards, the advent of lower areal density ultra-high molecular weight polyethylene (UHMWPE) and modern suspensions may incur unknown changes that present an unknown effect on BHBT risk. This study investigates whether current standards relying on a peak acceleration threshold and residual clay deformation may not reflect changes in deformation geometry seen in newer shell materials and suspension designs. Thirty-eight helmets categorized into three groups, older aramid, newer aramid (with new suspension), and prototype UHMWPE (with old suspension), were mounted on Hybrid III ATD head-necks and impacted on the temporal surface with 9 mm NATO projectiles at velocities between 388 and 482 m/s. Flash x-ray imaging captured deformation geometry. Deformations were digitized to measure maximum depth, volume, and surface area recruited. Multiple linear regression identified the influence of shell material and suspension on geometry. Results indicated that shell material significantly affected deformation volume and area (p < 0.05). Notably, UHMWPE exhibited a qualitatively more “pointed” deformation profile compared to aramid, recruiting material differently as depth increased. In contrast, suspension type and helmet design did not significantly influence deformation geometry. These findings suggest that the BHBT geometry in UHMWPE helmets differs fundamentally from aramid helmets. As UHMWPE helmets encounter higher-energy threats, current acceleration threshold or depth-based standards may not fully capture the risk of skull fracture. To future-proof helmet validation, testing standards should evolve beyond current standards to include area recruitment and other geometric measures.
Aiming at the constraint issues of adjacent spacecraft solar panel collision avoidance and formation keeping in the pose tracking control of spacecraft formation, this paper proposes a distributed relative position and attitude cooperative control strategy on the basis of high-order control barrier functions. First, nominal control strategies for relative position and attitude tracking using the sliding mode control method to achieve high-precision tracking of relative motion are de-signed. Then, high-order control barrier functions suitable for solar panel collision avoidance and spacecraft formation keeping constraints are constructed. The control strategy constraints satisfying safety specifications are derived based on the forward invariant set theory. Finally, a quadratic programming optimization framework is established by combining the nominal control strategies and constraint conditions and then we obtain the optimal control strategy by solving this framework. Numerical simulations verify that the designed control scheme achieves precise tracking of relative position and attitude for spacecraft formation, avoids collisions between solar panels of adjacent spacecraft and prevents excessive loosening of the formation configuration.
Artificial Intelligence (AI) and Machine Learning (ML) are increasingly transforming Computer-Aided Engineering (CAE) workflows by enabling faster design iterations and reducing computational costs. This paper presents the application of Ansys SimAI and Ansys GeomAI in modelling an automotive side impact scenario using high-fidelity data from LS-DYNA simulations. Two AI models are trained on datasets with systematically varied parameters: one encompassing pole impact position and door beam configurations, and another focusing on rocker panel reinforcements. Both models exhibit strong predictive performance, reliably capturing deformation patterns and force-time histories for previously unseen configurations. The datasets are subsequently merged to train a comprehensive surrogate model capable of simultaneously representing variations in pole position, door beam geometry, and rocker reinforcement design, demonstrating robust generalization across a multidimensional design space. To address the emerging bottleneck of geometry creation, GeomAI’s geometry exploration functionality is employed to generate new rocker reinforcement geometries from existing ones, which are then rapidly validated using the pre-trained surrogate model. The results confirm that LS-DYNA simulations can be leveraged effectively to build AI models that dramatically reduce design exploration time. With SimAI and GeomAI in the loop, CAE workflows can evolve from simulation-driven design toward AI-augmented autonomous engineering, where geometry generation, simulation, validation, and optimization converge into an intelligent closed loop.
The persistent rate of accidents and fatalities involving legacy tactical military vehicles underscores a critical need for Enhanced Situational Awareness (ESA) technologies. However, the prohibitive cost and lengthy development cycles associated with full MIL-STD ruggedization often prevent these safety systems from reaching the in-service non-combat vehicles with limited driver visibility. This paper suggests a strategic shift in procurement policy: The adoption of relaxed ruggedization standards for vehicles operating in non-combat, administrative, and training roles. By deriving requirements from high-stress commercial sectors— such as heavy mining, steel production, and NASCAR racing—the military can utilize electronics designed for "extreme industrial" rather than "battlefield" environments. The principal objectives of this relaxation is cost reduction, lowering the barrier to entry and increasing the likelihood of ESA deployment across the legacy fleet. Furthermore, this approach aligns with Modular Open Systems Approach (MOSA) principles by enabling the integration of non-proprietary commercial devices. Utilizing these accessible technologies on legacy platforms creates a real-world testbed to evaluate technological advances rapidly. These insights can then inform and accelerate the development of future MIL-STD systems for combat vehicles, effectively shortening the traditional development life cycle while prioritizing the immediate enhanced protection of service member lives.
To address the lack of safe and effective on-site vehicle blocking and control methods in the event of fires or other emergencies in extra-long tunnels — which can significantly reduce traffic safety risks and prevent secondary accidents — this study proposes a novel barrier-free light–smoke curtain interception method. The method integrates conventional traffic safety warning facilities (gantry-mounted variable message signs and audio–visual alarms) with two light–smoke curtain interception images to form a composite early-warning and interception system. Driving simulation experiments were conducted to comprehensively evaluate its warning effectiveness, interception performance, and operational safety in comparison with methods employing only traditional warning facilities or light curtain images. Furthermore, field drills were performed to validate its real-world applicability and interception effectiveness under both daytime and nighttime conditions. The main findings are as follows: 1) The fixation ratio and interception success rate associated with the proposed method were significantly higher than those of the other two methods, demonstrating enhanced visual attention and superior warning and interception performance. 2) The maximum deceleration observed with the proposed method was lower than that of the light curtain–only method and did not trigger emergency braking, thereby indicating high operational stability and driver comfort. 3) In field drills, after activation of the interception equipment, only one and two vehicles entered the tunnel under daytime and nighttime conditions, respectively, and full control of on-site vehicles was achieved within two minutes without any traffic accidents, verifying the system’s rapid response and effective safety assurance.
As special pressure-bearing vessels, spherical tanks are widely used in chemical, oil refining, and other fields. However, their safe operation faces the dual challenges of structural failure and leakage diffusion. Meanwhile, due to its low lower explosive limit and the low ignition energy required, propane will evaporate rapidly after leakage to form an explosive mixed gas, which may further trigger severe accidents such as combustion and explosion. Therefore, this paper takes a 3000 m3 propane spherical tank as the research object, comprehensively applies the finite element analysis method, and systematically researches stress distribution, aiming to provide theoretical support for the safety design of spherical tanks and accident prevention and control.
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