Biomass composites are ever-increasing in agricultural engineering. This study aims to enhance the mechanical properties and aging resistance of bamboo-plastic composites (BPC), in order to realize the environmental friendliness and application of its pallet products. Firstly, three ratios of bamboo fiber (BF) and high-density polyethylene (HDPE) were used to prepare the BPC. Then mechanical property tests were conducted to determine the optimal ratio of BF to HDPE. Among them, nano-TiO2 was widely used to enhance the performance of plant fiber/thermoplastic polymer composites, due to its chemical inertness, anti-aging, anti-bacterial properties, and non-toxic nature. An organic-inorganic co-modification was also employed to enhance the BPC properties for strong compatibility with bamboo fiber and plastic matrix. Nano-SiO2 was coated onto nano-TiO2 to prepare SiO2@TiO2 nanoparticles for the high dispersion and aging resistance of TiO2. Nano-SiO2@TiO2 modified BPC (KH550-ST-BPC) was prepared using the silane coupling agent KH550 as a reinforcing agent by a spray coating. The properties were evaluated to compare the mechanical properties, SEM images, and UV aging properties of BPC before and after modification. In addition, ANSYS Workbench software was used to perform the finite element analysis of BPC integrated pallets before and after modification, in order to verify the application performance of reinforced BPC pallets. The results indicated: 1) The bending and tensile properties of BPC shared an increasing trend with the increase of bamboo fiber content. The optimal mechanical properties of BPC were obtained at a 5:5 mass ratio of BF to HDPE, with a 38.34% increase in the bending strength and a 62.19% increase in the bending modulus, compared with the 3:7 ratio. The tensile strength and modulus increased by 14.95% and 101.18%, respectively. SEM images revealed that there was a smoother interface for BPC55, which was better consistent with the mechanical test. 2) The bending and tensile strength of BPC were enhanced by 31.11% and 11.86%, respectively, in the modified nano KH550-SiO2@TiO2, while the bending and tensile modulus were enhanced by 52.27% and 21.92%, respectively. The interfacial gaps of modified BPC were significantly reduced in the SEM images, indicating the strong bonding between the bamboo fibers and HDPE. The KH550-SiO2@TiO2 was introduced to fill the interface gaps for the BPC compatibility, which was better consistent with the mechanical property test. 3) The surface morphology revealed that KH550-SiO2@TiO2 modified BPC maintained better color stability for the high resistance to UV aging. While the unmodified BPC showed significant color fading after 1 200 h UV irradiation aging. Colorimetric analysis confirmed that the color stability of KH550-ST-BPC was significantly better during UV aging, with a color aberration change value 77.79% lower than before. 4) Finite element analysis indicated that the modified BPC pallet exhibited the better-bending properties and load-bearing capacity, with a 27.36% reduction in the maximum deformation under the rated load and a 23.41% reduction under the ultimate load in stacking simulation. These research findings can provide a strong reference for the application of nano-SiO2@TiO2 reinforced BPC as logistics turnover units.
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Bioelectricity generated by standing living trees is a new topic. In this work, by studying the influence of different habitat factors on the power of the bioelectricity generated by living trees and its variation law, the habitat conditions with the highest bioelectric power generation were determined to provide a theoretical basis for the optimal environment selection for the low-energy consumption equipment in the forest.
The common tree species in northern China, Larix gmelinii and Ulmus americana, were selected as the research objects. The voltage and current of living trees, temperature and relative humidity of air and soil, soil pH and other habitat factors around the trees were measured in the temperature range of -15℃ to 10℃ at different heights of the tree trunk. Combined with the soil-sap equivalent circuit, bioelectric power was calculated. The significant factors affecting bioelectric power were determined by statistical analysis. The relationship model between the bioelectric power and the main habitat factors was established to determine the influencing law of different habitat factors on the bioelectric power generated by living trees.
The results showed that temperature, humidity and soil pH all had significant effects on the bioelectricity power generated by living trees. Among them, air and soil temperature had the most significant effect, followed by relative soil humidity and soil pH. The influence of relative air humidity was relatively weak. The height of the electrode had a significant effect on the power generation of Larix gmelinii, which interacted with temperature and humidity conditions. The relationship model between the bioelectric power of living trees and the habitat factors was determined, whose coefficients of determination were 0.64-0.97 (above zero temperature) and 0.96-0.99 (below zero temperature), respectively. The bioelectric power generated by Larix gmelinii was about 2.6 times that of Ulmus americana When the temperature was above zero, the bioelectric power generated by Ulmus americana was better.
According to the established relationship model between air temperature and the bioelectric power of living trees, the power could be predicted by the air temperature change, and the optimal environmental conditions for bioelectricity collection could be determined. When the temperature was above 0℃, Larix gmelinii could be used as the tree species for bioelectricity collection. Ulmus americana could be used for bioelectricity collection when the temperature was below 0℃.
Acoustic emission (AE) is used to detect the damage of poplar plywood in the whole process of stress damage, and BP neural network is applied to identify the results of AE, so as to improve the damage detection accuracy of plywood.
Poplar plywood used in pallets with high market share was taken as the research object. During the joint AE and stress damage test, six AE characteristic parameters were extracted, the crack types of plywood were distinguished by acoustic emission RA-AF joint analysis method, and the corresponding relationship between damage evolution degree and AE characteristic parameters was determined by K-means clustering analysis method. The damage identification model was established by BP neural network, and the identification network was trained by test.
AE signal amplitude and rise time effectively characterized the evolution process of stress damage from microcrack initiation, macroscopic crack to complete fracture; Through RA-AF analysis, it was found that in the first stage of bending test, the main damage of poplar plywood is shear failure. In the second and third stages, the main damage was tensile failure; Based on cluster analysis, it was found that there was a strong corresponding relationship between damage types and AE Peak frequencies, the different damage patterns could be effectively characterized: matrix cracking within 31 kHz, debond and delamination within 31-100 kHz, and fiber fracture above 100 kHz; The AE-BP neural network model could identify the fuzzy damage types with the goodness of fit of the training samples was 95.94%, the goodness of fit of the test set was 98.89%, and the total goodness of fit of the model was 96.51%, and the network training was more effective.
The damage types of poplar plywood during AE monitoring can be effectively detected and accurately identified by constructing AE-BP model.
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