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Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology

Author

Listed:
  • Xinzhou Wu

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Wuhan Textile and Clothing Digital Engineering Technology Research Center, Wuhan 430073, China)

  • Zhe Cheng

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Wuhan Textile and Clothing Digital Engineering Technology Research Center, Wuhan 430073, China)

  • Victor E. Kuzmichev

    (School of Fashion, Wuhan Textile University, Wuhan 430073, China
    Institute of Textile Industry and Fashion, Ivanovo State Polytechnic University, 153000 Ivanovo, Russia)

Abstract

At present, the traditional mode of research and development for mass-produced wetsuits usually requires repeated sample making and try-on evaluation, and performance cannot be predicted, monitored and evaluated in real time; this can lead to problems including low material utilization and production efficiency. In this study, real human body static and dynamic measurements, material properties and structure data are applied through 3D software to build an accurate virtual model, and new wetsuits are designed through simulation, optimization and evaluation. The static and dynamic fitting performance above and underwater is comprehensively evaluated in virtual and real environments, and it is proved that the virtual development mode can accurately and effectively guide the development and evaluation of wetsuits, and can meet personalized comfort and functional requirements today. This simulation evaluation method avoids repeated sample preparation, some unnecessary waste of materials and environmental pollution, and improves manufacturing efficiency.

Suggested Citation

  • Xinzhou Wu & Zhe Cheng & Victor E. Kuzmichev, 2023. "Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2197-:d:1045906
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    References listed on IDEAS

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    1. Fei Tao & Qinglin Qi, 2019. "Make more digital twins," Nature, Nature, vol. 573(7775), pages 490-491, September.
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