Quasi-static and impact response of PLA 3D-printed kirigami truncated pyramid structures
Source abstract
Abstract
This study proposes a kirigami-inspired optimized truncated pyramid (OTP) structure as a novel thin-walled energy absorber for automotive crash box applications. The OTP was designed to achieve high energy absorption capacity and improved impact resistance and was evaluated against a conventional square tube with same wall thickness, and a folded kirigami (FK) counterpart of identical wall thickness and mass. Quasi-static axial compression tests were conducted to examine collapse behavior and energy absorption characteristics, while validated finite element models were also employed to quantify key crashworthiness indicators, including peak crushing force, average force, specific energy absorption (SEA), and crushing force efficiency (CFE). Results show that the OTP exhibits superior structural stiffness and energy absorption performance, achieving an SEA of 11.01 J/g, about 2.7 times higher than that of the FK. Parametric studies on wall thickness, polygonal corners, and height-to-width ratio revealed that a hybrid configuration of vertical and inclined surfaces maximizes energy dissipation and stability. Low-velocity drop-weight impact tests were further performed to assess dynamic responses. Comparison with quasi-static results highlighted consistent deformation modes, while force–time histories confirmed enhanced impact resistance. Overall, the OTP structure demonstrates significant advantages over the FK design, emphasizing the critical role of geometric tailoring in crashworthiness enhancement. These findings underscore the strong potential of OTP structures as lightweight and high-performance energy absorbers for aerospace, rail transport, and automotive safety applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Cellular and Composite Structures · Advanced Materials and Mechanics · Additive Manufacturing and 3D Printing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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