Multi-objective crashworthiness optimization of lattice structure filled thin-walled tubes


BAYKASOĞLU A., BAYKASOĞLU C., Cetin E.

THIN-WALLED STRUCTURES, cilt.149, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 149
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.tws.2020.106630
  • Dergi Adı: THIN-WALLED STRUCTURES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Thin-walled tubes, Lattice structures, Hybrid structures, Multi-objective crashworthiness optimization, Axial impact loading, FUNCTIONALLY GRADED THICKNESS, SWARM INTELLIGENCE ALGORITHM, SUPERPOSITION ATTRACTION WSA, ENERGY-ABSORPTION, CRUSHING ANALYSIS, IMPACT BEHAVIOR, COMPRESSIVE RESPONSE, ALUMINUM TUBES, COMPOSITE, DESIGN
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Thin-walled tubes have been mostly used in passive vehicle safety systems as crash energy absorber. With the use of additive manufacturing technology, it is possible to produce novel filler materials to further enhance the crashworthiness performance of thin-walled tubes. In this study, optimal designs of novel lattice structure filled square thin-walled tubes are investigated under axial impact loading by using a compromise programming based multi-objective crashworthiness optimization procedure. Types of filler lattice structures (i.e., body-centered cubic, BCC and body-centered cubic with vertical strut, BCC-Z), diameter of lattice member, number of lattice unit cells and tube thickness are considered as design parameters, and the optimum values of these design parameters are sought for minimizing the peak crash force (PCF) and maximizing the specific energy absorption (SEA) values. The validated finite element models are utilized in order to construct the sample design space and carrying out results verification; an artificial neural network is employed for predicting values of the objective functions; the weighted superposition attraction algorithm is used to generate design alternatives and searching for their optimal combination. The compromise programming approach is used to combine multi-objectives and to produce various optimal design alternatives. The optimization results showed that the proposed approach is able to provide good solutions with high accuracy and proper selection of design parameters can effectively enhance the crashworthiness performance of the lattice structure filled thin-walled tubes. The optimum results revealed that BCC hybrid designs have generally superior crashworthiness performance compared to that of their BCC-Z counterparts for the same compromise solutions. In particular, the PCF value of the optimized BCC-Z hybrid structures is up to 44% higher than that of BCC hybrid structures while these structures have similar energy absorption performances. The compromise solutions also show that the SEA of BCC and BCC-Z hybrid structures increases respectively by 29% and 51% depending on the selected weight factors for the design objectives.