Browse Topic: Finite element analysis
Ultrasonic TOFD detection is one of the most important non-destructive testing techniques for welds. However, the complex beam deflection, scattering, and attenuation of ultrasonic waves in the heterogeneous weld structure lead to the weak signal of the defect diffraction wave received by the probe and the low signal-to-noise ratio, which has a negative impact on the engineering application of ultrasonic TOFD detection technology in austenitic stainless steel welds. In this study, a numerical model of the ultrasonic TOFD detection process for austenitic stainless steel welds was established based on the finite element method. Combined with the test method, the interaction mechanism between the ultrasonic wave and weld structure is analyzed, and the probe arrangement method to reduce the interference of weld scattering noise is proposed. The results show that the finite element model can simulate the anisotropic characteristics of ultrasonic waves in austenitic stainless steel welds, including sound field distortion, sound energy scattering, and attenuation. Combined with the detection test, it has been proven that the adverse effect of the weld structure on the TOFD detection signal can be reduced by changing the probe detection surface.
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.
Extreme winter weather often leads to ice accretion on transmission lines. Manual removal is inefficient, costly, and poses safety risks. To address this issue, this paper presents the design of a de-icing robot to replace manual operations for transmission line de-icing. The main content focuses on the detailed structural design of the robot, including the mobile platform, de-icing mechanism, and adaptive adjustment module. Finite element simulations are conducted on key components to verify the structural rationality and the correctness of material selection. The proposed de-icing robot enhances the safety of the de-icing process, improves operational efficiency, and provides a valuable reference for transmission line de-icing methods, demonstrating significant practical value.
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.
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