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Stone waste refers to the waste stone particles generated from mining and stone processing to finished products that are not utilized in a resourceful manner. In this study, a CGF solid waste-based binder (abbreviated as CGF), with calcium carbide residue (CCR), ground granulated blast-furnace slag (GGBS), and fly ash (FA) as components, was developed to solidify the stone waste. Through “treating waste with waste”, the resource utilization of solid waste was realized. In order to improve the performance of the new material, this paper proposes the MAA-SW model for stone waste pavement base material based on the MAA model, establishes the relationship with the target gradation, and obtains the ideal gradation composition of stone waste through the calculation of the response surface analysis so as to obtain an energy-saving stone waste pavement base material with excellent performance.

Large quantities of abandoned marine soft soil are generated from coastal engineering which cannot be directly utilized for construction without modification. The utilization of traditional binders to modify abandoned marine soft soil yields materials with favorable mechanical properties and cost efficiency. However, the production of traditional binders like cement leads to environmental pollution. This study uses a CGF all-solid-waste binder (abbreviated as CGF) composed of industrial solid waste materials such as calcium carbide residue (CCR), ground granulated blast furnace slag (GGBS), and fly ash (FA), developed by our research team, for the modification of abandoned marine soft soil (referred to as modified soil). It is noteworthy that the marine soft soil utilized in this study was obtained from the coastal area of Jiaozhou Bay, Qingdao, China. Physical property tests, compaction tests, and unconfined compressive strength (UCS) tests were conducted on the modified soil. The investigation analyzed the effects of binder content, compaction delay time, and curing time on the physical, compaction, and mechanical properties of CGF-modified soil and cement-modified soil. Additionally, microscopic experimental results were integrated to elucidate the mechanical improvement mechanisms of CGF on abandoned marine soft soil. The results show that after modification with binders, the water content of abandoned marine soft soil significantly decreases due to both physical mixing and chemical reactions. With an increase in compaction delay time, the impact of chemical reactions on reducing water content gradually surpasses that of physical mixing, and the plasticity of the modified soil notably modifies. The addition of binders results in an increase in the optimum moisture content and a decrease in the maximum dry density of CGF-modified soil, while the optimum moisture content decreases and the maximum dry density increases for cement-modified soil. Moreover, with an increase in binder content, the compaction curve of CGF-modified soil gradually shifts downward and to the right, while for cement-modified soil, it shifts upward and to the left. Additionally, the maximum dry density of both CGF-modified and cement-modified soils shows a declining trend with the increase in compaction delay time, while the optimum moisture content of CGF-modified soil increases and that of cement-modified soil exhibits a slight decrease. The strength of compacted modified soil is determined by the initial moisture ratio, binder content, compaction delay time, and curing time. The process of CGF modification of marine soft soil in Jiaozhou Bay can be delineated into stages of modified soil formation, formation of compacted modified soil, and curing of compacted modified soil. The modification mechanisms primarily involve the alkali excitation reaction of CGF itself, pozzolanic reaction, ion-exchange reaction, and carbonization reaction. Through quantitative calculations, the carbon footprint and unit strength cost of CGF are both significantly lower than those of cement.

To minimize pesticide dosage and its adverse environmental impact, Unmanned Aerial Vehicle (UAV) spraying requires precise individual canopy information. Branches from neighboring trees may overlap, preventing image-based artificial intelligence analysis from correctly identifying individual trees. To solve this problem, this paper proposes a segmentation and evaluation method for mingled fruit tree canopies with irregular shapes. To extract the individual trees from mingled canopies, the study fitted the projection curve distribution of the interlacing tree with Gaussian Mixture Model (GMM) and solved the matter of segmentation by estimating the GMM parameters. For the intermingling degree assessment, the Gaussian parameters were used to quantify the characteristics of the mingled fruit trees and then as the input for Extreme Gradient Boosting (XGBoost) model training. The proposed method was tested on the aerial images of cherry and apple trees. Results of the experiments show that the proposed method can not only accurately identify individual trees, but also estimate the intermingledness of the interlacing canopies. The root mean squares (R) of the over-segmentation rate (Ro) and under-segmentation rate (Ru) for individual trees counting were less than 10%. Moreover, the Intersection over Union (IoU), used to evaluate the integrity of a single canopy area, was greater than 88%. An 84.3% Accuracy (ACC) with a standard deviation of 1.2% was achieved by the assessment model. This method will supply more accurate data of individual canopy for spray volume assessments or other precision-based applications in orchards.

Accurate measurement of the downwash flow field of plant protection unmanned aerial vehicles (UAVs) is essential for analyzing the spatial distribution of droplets. To realize on-line rapid detection of the downwash flow field of a multi-rotor UAV, a flexible polypropylene detection device based on the principle of full bridge strain effect was proposed. Its performance principle was based on the physical deformation caused by wind pressure. The Fluid Flow and Static Structural modules of ANSYS 16.0 finite element software were used to simulate one-way fluid-solid coupling interaction. The surface of the resistive strain gauge embedded in the flexible detecting structure responded well to wind speed variation, hence it was suitable for downwash airflow wind field detection. By solving the strain force on the surface of the flexible detection structure, the length and layout of the grating wire of the strain gauge on the surface of the flexible detection structure were optimized. Meanwhile at 4 m·s−1 wind speed, the output voltage at varied bridge flexible acquisition systems in the acquisition card was measured. Results indicated coefficient of variation of 3.67%, 1.63% and 1.5%, respectively, which proved the good data acquisition consistency of the system. Through calibration test, the regression equation for the relationship between output voltage and wind speed for three unique sensor signal measuring circuits was established. The determination coefficients R2 for single bridge, half bridge and full bridge circuits were 0.9885, 0.9866 and 0.9959, respectively. In conclusion, by applying the multi-rotor plant protection UAV test platform, the results indicated the maximum relative error of the wind speed at each sampling point of the system at 1.0 m altitude was below 5.61%. Simulated and measured value had an RMSE maximum error of 0.1246 m·s−1. Moreover, downwash airflow detection not only has high accuracy but also has high sensitivity. Thus, there is convenience and practicability in the plant protection offered by this approach. The rapid measurement of UAV wind field and the established two-dimensional wind field model can provide a basis for precise application of agricultural aviation.