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Highlights This study investigates the mechanical properties of composites made from biaxial warp‐knitted glass fiber/epoxy prepregs (BW‐GF/EP) in comparison to plain woven glass fiber/epoxy prepregs (PW‐GF/EP). The BW‐GF/EP composites demonstrated superior tensile strength, with an increase of 9.5%, and bending strength, with an increase of 12.2%, compared to the PW‐GF/EP composites. Despite having a lower tensile modulus, the BW‐GF/EP composites exhibited 8.7% higher interlaminar shear strength. Dynamic mechanical analysis showed that both materials had similar storage and loss moduli at lower temperatures, with PW‐GF/EP performing better at higher temperatures. Microscopy revealed that failure in PW‐GF/EP occurred at weave intersections, while BW‐GF/EP composites showed fiber rupture and delamination. The findings highlight the advantages of using biaxial warp‐knitted fabrics for improved composite performance. Developed biaxial warp‐knitted fabric prepregs to replace liquid molding techniques. Improved interlaminar shear strength, reducing delamination risks in composites. Achieved higher tensile and bending strength compared to plain weave composites. Enhanced resin impregnation and molding efficiency with biaxial warp‐knitted fabrics. Reduced environmental impact and costs by avoiding VOCs and minimizing waste. [ABSTRACT FROM AUTHOR]

The increasing use of glass‐fiber reinforced polypropylene (GFPP) composites in a wide range of applications requiring long‐term service in challenging environments underscores the importance of its long‐term durability. This study aimed to investigate the effect of thermal aging on the long‐term dynamic durability and stress relaxation of GFPP composites. The time–temperature equivalence principle (TTSP) was used to assess the dynamic modulus at various temperatures and frequencies, as well as the relaxation modulus at different temperatures and relaxation times. To better understand long‐term durability behavior, the study also examined the impact of molecular structure on the durability of GFPP. Changes in chemical composition, crystallinity, melting point, and melt flow index of GFPP due to thermal aging were measured and analyzed using Fourier transform infrared spectroscopy, and differential scanning calorimetry, respectively. The results revealed that oxidation led to a decrease in the crystallinity and molecular weight of GFPP. The destruction of GFPP's molecular structure due to oxidation resulted in reduced long‐term durability. While TTSP can predict the long‐term durability of GFPP for decades or even centuries, its application in predicting the long‐term durability of GFPP is more suitable for nonaging conditions. Highlights: Thermal aging reduces glass‐fiber reinforced polypropylene (GFPP's) long‐term durability.Time–temperature equivalence principle predicts GFPP durability under aging.GFPP's activation energy drops with thermal aging.Long‐term GFPP behavior aligns with Williams–Landel–Ferry model.Predictive models refine understanding of GFPP longevity. [ABSTRACT FROM AUTHOR]

In order to improve the flexibility and response efficiency of warehouse dispatching, a cascaded improved differential evolution algorithm is proposed to construct the allocation of goods with the picking trolley running time, shelf stability, and inventory capacity as resource conditions. The maximum completion time for each item in the batch order assigned to the optimal location of the corresponding partition is the two-level target model that is re-batch-allocated for the conditional order. The Lagrangian interpolation algorithm is integrated into the improved algorithm of the standard differential evolution algorithm to solve the two-level target model, and the two-level solution process is cascaded to complete the cascaded differential evolution algorithm to solve the multi-order batch allocation problem. Based on the adaptive adjustment of differential evolution parameters, the improved differential evolution algorithm combines the local search ability of Lagrangian interpolation to optimize the differential evolution algorithm, and uses local and global switching factors to dynamically adjust the evolution direction and improve the convergence performance of the algorithm. The improved differential evolution algorithm is applied to solve the problem of multi-order batch allocation. The experimental results show that the improved algorithm optimization results are better than the particle swarm optimization algorithm, the genetic algorithm, and the standard differential evolution algorithm, which reduces the maximum completion time of each batch of orders and effectively balance the workload.

Fiber breakage is one of the most negative factors that affect the mechanical performance of unidirectional carbon-fiber (CF)-reinforced composites. In the present study, unidirectional CF-reinforced epoxy (CF/epoxy) laminates with and without fiber breakages located in different layers were manufactured from prepreg via hot compression. The static and cyclic flexural mechanical properties of the unidirectional CF/epoxy laminates were determined through static and low-cycle three-point bending tests. Flexural behavior was observed by using optical microscopy to discuss the failure behavior of the unidirectional CF/epoxy laminates. Results indicated that fiber breakages in different layers led to the static and cyclic mechanical degradation of the unidirectional CF/epoxy laminates. Moreover, fiber breakages in the tension side displayed higher flexural strength and better cyclic performance than those in the compression side.

Vibration monitoring is one of the most effective approaches for bearing fault diagnosis. Within this category of techniques, sparsity constraint-based regularization has received considerable attention for its capability to accurately extract repetitive transients from noisy vibration signals. The optimal solution of a sparse regularization problem is determined by the regularization term and the data fitting term in the cost function according to their weights, so a tradeoff between sparsity and data fidelity has to be made inevitably, which restricts conventional regularization methods from maintaining strong sparsity-promoting capability and high fitting accuracy at the same time. To address the limitation, a stepwise sparse regularization (SSR) method with an adaptive sparse dictionary is proposed. In this method, the bearing fault diagnosis is modeled as a multi-parameter optimization problem, including time indexes of the sparse dictionary and sparse coefficients. Firstly, sparsity-enhanced optimization is conducted by amplifying the regularization parameter, making the time indexes and the number of atoms adaptively converge to the moments when impulses occur and the number of impulses, respectively. Then, fidelity-enhanced optimization is carried out by removing the regularization term, thereby obtaining the high-precision reconstruction amplitudes. Simulations and experiments verify that the reconstruction accuracy of the SSR method outperforms other sparse regularization methods under most noise conditions, and thus the proposed method can provide more accurate results for bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced thermoplastic composites are rapidly emerging as alternative materials for auto parts due to recyclability, excellent stiffness, and strength to weight ratio. In the present study, the influence of carbon fiber de-sizing on the structural and mechanical properties of the sized and de-sized Carbon Fiber Reinforced Polypropylene (CFPP) composites molded by the recently developed novel Direct Fiber Feeding Injection Molding technology was studied. The effect of carbon fiber de-sizing on the structural properties was studied from the fiber dispersion status, fiber orientation factor, fiber volume fraction, and the fiber length. The surface morphology of the sized and de-sized carbon fibers was studied from the Scanning Electron Microscopy (SEM) and Atomic Force Microscope images. The static mechanical properties were studied based on the tensile tests at different loading rate and temperature. The Dynamic Mechanical Analysis tests were conducted to analyze the dynamic viscoelastic behavior of the sized and de-sized CFPP composites. The SEM images were used to observe the failure mechanism. The preliminary results indicated that de-sized composites had better fiber dispersion as compared to the sized CFPP composites. It was found that de-sizing the carbon fiber surface does not significantly affect the carbon fiber length, fiber volume fraction, and fiber orientation in the CFPP composites. Also, the de-sized composites showed better static and thermodynamic mechanical properties caused by the enhanced fiber matrix interaction in CFPP composites as compared to the sized CFPP composites. [ABSTRACT FROM AUTHOR]