Fuzzy MCDM-Based Selection of 3D Printed Lattice Architectures for Underbody Blast Protection in Armored Vehicles

Abstract

Additively manufactured lattice structures combine high energy absorption, low weight, and blast resistance, making them suitable for underbody protection in armored vehicles. Selecting an optimal design requires balancing mechanical performance, manufacturability, and deformation behavior, which traditional approaches often overlook. This study presents a two-stage fuzzy multi-criteria decision-making (MCDM) framework integrating Fuzzy AHP with three ranking methods: Fuzzy MARCOS, Fuzzy EDAS, and Fuzzy CRADIS. Two decision matrices were analyzed: (i) a core set of eight established lattices, and (ii) an extended set of 27 geometries covering strut-based, triply periodic minimal surfaces (TPMS), and hybrid designs. Eight defense-relevant criteria guided the evaluation, with ranking stability assessed using Spearman's correlation and rank variability index (RVI). TPMS-Skeletal Split P, TPMS-Gyroid (Skeletal), and Fluorite consistently ranked highest, while Hex Star and TPMS-Sheet Schwarz showed high variability. Auxetic and BCC displayed stable mid-to-high performance. High correlation in the core set (rho > 0.90) and low correlation in the extended set (rho < 0.35) highlighted the effect of structural diversity. The framework enables transparent, robust lattice down-selection for blast-resistant defense applications.