A performance evaluation study of thin-wall tube design in the front bumper uses the altered TOPSIS-rank order clustering algorithm-integrated approach


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Yurdakul M., İç Y. T., Ülke İ., Sağol B. B.

Multiscale and Multidisciplinary Modeling, Experiments and Design, cilt.7, sa.1, ss.53-67, 2024 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s41939-023-00183-8
  • Dergi Adı: Multiscale and Multidisciplinary Modeling, Experiments and Design
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
  • Sayfa Sayıları: ss.53-67
  • Anahtar Kelimeler: Direct compression, Energy absorption, Finite element analysis, Oblique compression, Rank order clustering, TOPSIS method, Tube structures
  • Gazi Üniversitesi Adresli: Evet

Özet

The rising growth of the economy in developing countries led to a significant increase in the number of vehicles on the roads. The number of vehicles in road transport is also increasing significantly due to the increase in automobile ownership due to the increase in city populations. As a result of this increase, there is an increase in traffic accidents. For this reason, automobile manufacturers make significant efforts to develop lighter and more robust bumpers. Also, they used performance measurement studies for the thin-walled bumpers. The motivation of the study is based on the examines the dynamic performance of thin-walled bumpers within the impact of both oblique and axial compression. The crash performance of thin-wall tubes is analyzed based on factors such as speed, mass, and cross-section geometries. We developed a new rank order clustering (ROC) algorithm that integrated altered technique for order preferences by similarity to ideal solution (A-TOPSIS) method-based comparative analysis to determine the best thin-wall tube among the alternatives. For the first time in the literature, the A-TOPSIS results-integrated ROC algorithm is proposed to obtain the best tube profiles considering different expectations from their performance according to the determined criteria.