Browse Topic: Hazards and emergency operations
Unmanned aerial vehicles (UAVs) equipped with chemical contaminant sensors offer an innovative approach for rapid and safe remote chemical reconnaissance. However, the proliferation of diverse UAV platforms presents a critical challenge: how to select the optimal platform for a given mission scenario. This paper establishes a systematic suitability analysis framework for deploying chemical contaminant sensors on three mainstream UAV platforms-multirotor, fixed-wing, and vertical take-off and landing (VTOL) types. We analyze payload capacity, endurance, flight stability, environmental adaptability, and mission system integration. To reduce decision subjectivity, we develop an Analytic Hierarchy Process (AHP)-based quantitative evaluation model incorporating expert surveys and consistency tests to validate the weighting process. Beyond the evaluation framework, we explore key engineering challenges in platform-sensor integration, including aerodynamic interference, vibration and electromagnetic compatibility, and power management. We compare quantitative measurements and qualitative features across platforms in simulated mission scenarios. The resulting selection criteria provide a theoretical basis and a reproducible decision-support framework for developing chemical detection systems applicable to emergency response, environmental monitoring, and public safety.
To improve the accuracy and safety margin deficiencies of unmanned aerial vehicles in autonomous medical emergency search-and-rescue missions, this paper develops an adaptive embedded fusion optimizer named CTCM-ALA for rescue UAV path planning. The proposed algorithm hybridizes the tribe-competition member-cooperation strategy and artificial lemming algorithm to construct hierarchically adaptive initial populations, speed up convergence and prevent local convergence traps. Tests on 12 CEC2017 functions prove its better optimization performance. Real-world applications in dense urban and complicated topographic medical rescue cases verify its reliability and precision.
With the development of controlled nuclear fusion technology, the tokamak device, as the most promising magnetic confinement fusion reactor for advanced engineering applications, requires remote maintenance of its internal components, which has become a key factor affecting both operational efficiency and safety. As a critical component directly exposed to high-temperature plasma, the divertor target plate needs to be periodically replaced and carefully maintained to ensure stable and reliable reactor operation. However, this region is subject to extreme conditions, including high temperature, high vacuum, and intense radiation, making conventional manual maintenance infeasible. This necessitates the development of intelligent and automated teleoperation systems. To address the automated assembly and disassembly requirements of divertor target plates, this study designs an integrated target plate actuator comprising key functional units: a positioning module, a screwing module, a quick-change module, and a passive compliance structure. The actuator achieves rapid and precise alignment with target plate holes, accommodates bolts of different specifications, and exhibits excellent impact resistance. Furthermore, stiffness and mechanical analyses, supported by finite element simulations, verify the actuator’s safety and reliability under high loads and impact forces. To further enhance operational performance, a segmented disassembly and assembly control strategy based on reinforcement learning is proposed, enabling the actuator to adaptively handle torque variations and ensure precise and stable bolt operations. The results demonstrate that the proposed actuator and control strategy significantly improve the accuracy, stability, and efficiency of target plate operations under complex working conditions, providing a reliable solution for automated divertor maintenance in tokamak devices.
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 operation in emergency evacuation scenarios. In addition, the usage of this proposed technology can be further extended to locate the aircraft when other existing locating mechanisms fail.
As satellites take on more onboard processing - from Earth imaging to autonomy - spacecraft computing designers are pushing for higher performance under tight thermal and radiation constraints. Here's how suppliers are approaching heat removal, radiation mitigation and production-scale space-grade computing for LEO and beyond.
Just as the world needs the next generation of nuclear reactors to meet climate goals, it needs new options for safely and securely storing radioactive materials. As of 2022, there were approximately 400,000 metric tons of spent fuel being stored globally, with roughly 90,000 tons in the U.S. alone.
Sealing systems in space applications must perform reliably under demanding conditions in engineering: cryogenic temperatures, vibration, leakage control, ultra-high vacuum, ionizing radiation, abrasive particulates, and repeated thermal cycling. Each factor strains conventional sealing technologies. In combination, they can rapidly cause failure in systems where margins are unforgiving and maintenance is impossible. As spacecraft architectures evolve toward longer operational lifetimes and broader mission profiles, sealing requirements continue to tighten. Launch vehicles, satellites, and exploration platforms now operate across wider temperature ranges and in contact with more aggressive propellants and media. As a result, both metal seals and engineered polymer alternatives are evaluated-and selected-against increasingly specific, measurable performance criteria.
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 different shapes and sizes were conducted. Experimental validation confirms the influence of actuator dimensions, particle characteristics, and granule size distribution on both stress states and bending angles at the soft robotic digit’s distal segment. The obtained results establish theoretical foundations and advance variable-stiffness soft robotics research and associated stiffness regulation methodologies.
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