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March 26, 2026The Proceedings of Mechanical Engineering Congress Japan0 citationsOpen Access

Circumference moment distribution on railway carbody shell made of aluminum alloy

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TKTakeshi KAWASAKI

Key Points

  • The aim is to provide an intuitive method for structural modification in railway carbody design using machine learning.
  • Calculated out-of-plane bending moments using beam theory.
  • Applied the method to a simplified cantilever model under vertical and moment loads.
  • Verified the method against theoretical solutions with maximum differences under 1%.
  • Compared moment distributions with deformation modes across five cross-sections.
  • The method showed good alignment with theoretical predictions.
  • Trends in deformation and moment distribution were consistent across sections.
  • Demonstrated practical application for structural design in railway vehicles.

Abstract

To achieve both lightweight construction and improved ride comfort in railway vehicles, it is essential to provide a method that allows even less-experienced designers to intuitively identify directions for structural modification and solution analysis obtained from machine learning. This study proposes a method for calculating circumferential out-of-plane bending moments in carbody shells made of aluminum hollow extrusions, based on beam theory using surface sheet axial forces discretized at the intersections of ribs and surface sheets. The validity of the method was verified using a simplified cantilever model subjected to vertical and moment loads, showing good agreement with theoretical solutions and a maximum difference of less than 1%. The method was applied to a structure, and the resulting structural moment distributions were compared with deformation modes at five cross-sections. The trends of out-of-plane deformation and structural moment distribution, as well as the relative magnitudes among sections, were consistent. These results demonstrate that the proposed method is sufficiently practical for railway vehicle structural design.

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Cite This Study

Takeshi KAWASAKI (2025) studied this question.

synapsesocial.com/papers/69c4ccebfdc3bde448918885https://doi.org/10.1299/jsmemecj.2025.j181-11
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