Polyethylene terephthalate/basalt stab-resistant sandwich composites based on the Box–Behnken design: Parameter optimization and empirical regression model

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Abstract
In this study, the thicknesswise fibers of the low-melting polyethylene terephthalate (LPET) nonwoven fabrics are needle punched and intertwined with the intra-laminar basalt fibers (BF) of basalt plain woven fabric in order to strengthen the stab-resistant property of LPET/BF sandwich composites as well as to fabricate armor that is composed of less lamination layers. Two LPET nonwoven fabrics and a BF plain woven fabric as an interlayer are laminated and combined using a needle-punch reinforcing method. The response surface analysis based on the Box–Behnken design is used to examine the influences of structure parameters of low-melting PET nonwoven fabrics including areal density (AD) and manufacture parameters including needle punching density (ND), and depth of needle punch (DP) on the spike stab resistance, knife stab resistance, bursting resistance, and tensile property. An empirical regression model of AD, ND, and DP is thereby established. The test results show that the bursting strength and quasi-static stab resistance of sandwich composites are highly dependent on AD and ND. Likewise, DP has a significant influence on the knife stab resistance and bursting strength, while the tensile strength is solely dependent on ND. According to the empirical regress model, the acquired optimal needle punching parameters of sandwich composites are an AD of 400 g/m2, ND of 143.77 needles/cm2, and DP of 6.41 mm. The 95% confidence interval yielded by the empirical regression model is in conformity with the test results. The empirical regression model of the stab resistance is proven to provide effective prediction of the number of lamination layers required by armor in the future.
Funding Information
  • Opening Project of Green Dyeing and Finishing Engineering Research Center of Fujian University
  • National Natural Science Foundation of China (11502163)
  • National Natural Science Foundation of China (11702187)
  • National Natural Science Foundation of China (51503145)
  • Natural Science Foundation of Tianjin Municipality (16JCZDJC36600)
  • Natural Science Foundation of Tianjin Municipality (17JCQNJC03000)

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