Explore the vast range of titles available.

The successful launch of the Landsat 8 satellite provides important data for the monitoring of urban heat island effects. Since the Landsat 8 TIRS data has two thermal infrared bands, it is suitable for many algorithms to retrieve the land surface temperature (LST). However, the selection of algorithms for retrieving the LST, the acquisition of algorithm input parameters, and the verification of the results are problems without obvious solutions. Taking Changchun City as an example, this paper used the mono-window algorithm (MWA), the split window algorithm (SWA), and the single-channel (SC) method to extract the LST from the Landsat 8 image and compared the three algorithms in terms of input parameters, accuracy, and sensitivity. The results show that all three algorithms can achieve good results in retrieving the LST. The SWA is the least sensitive to the error of the input parameters. The MWA and the SC method are sensitive to the error of the input parameters, and compared with the error of the LSE, these two algorithms are more sensitive to the error of atmospheric water vapor content. In addition, the MWA is also very sensitive to the error of the effective mean atmospheric temperature.

Nomex® honeycomb core sandwich structures have been widely used in the aviation industry because of their special structure and performance. Ultrasonic composite processing was introduced to solve the poor machinability of honeycomb core products when subjected to conventional processing methods. Based on the characteristics of ultrasonic longitudinal-torsional vibration, the motion equation of the machining tool was established. The tool was simplified as a straight blade and slide effect was applied to study the torsional characteristics of the tool. Tests were conducted to investigate the influence of machining parameters on cutting force and surface quality. The results showed that the cutting force required during ultrasonic longitudinal-torsional vibration-assisted cutting was smaller than for ultrasonic longitudinal vibration-assisted cutting, regardless of the spindle speed and the feed rate. Compared to the feed rate, spindle speed has a significant influence on the cutting force. The slide effect is effective when cutting off the fiber and can reduce the formation of burrs. Compared to ultrasonic longitudinal vibration-assisted cutting, shorter burrs, a lower burr rate, and fewer tear defects were observed after ultrasonic longitudinal-torsional vibration-assisted cutting. The surface quality of the honeycomb core composites was improved by increasing the spindle speed during ultrasonic longitudinal-torsional vibration-assisted cutting.

In double-sided grinding, the material removal on the surface of the workpiece is non-uniform. The thermal deformation of the material may be one of the influencing factors. However, it is difficult to predict and measure the temperature field distribution in the workpiece in double-sided grinding. In this paper, based on the grain trajectory model, a single effective abrasive grain is regarded as a moving point heat source, and the new model of temperature field and workpiece thermal deformation is established based on the thermal–mechanical coupling effect. The distribution characteristics of the temperature field in the workpiece and the axial deformation of the workpiece under different processing parameters are calculated. Finally, a double-sided grinding experiment is carried out to measure the surface profile of the workpiece under different processing parameters to verify the accuracy of the established model. This article solves the problem of the unpredictable temperature field of the workpiece in double-sided grinding and has guiding significance for improving the surface quality of the workpiece in double-sided grinding through the optimization of processing parameters.

Double side grinding is a process with high processing efficiency in which the wheel and the workpiece are in surface contact. But the phenomenon that the workpiece surface profile is out of tolerance exists because of the material removal non-uniformity in the grinding process. In order to improve the surface integrity of the ground workpiece, the mathematical models of grinding trajectory distribution and material removal were established on the basis of the double side grinding process. The simulation and experimental research were carried out under different grinding parameters. It was shown that when the grinding wheel rotates in the co-rotation to the workpiece, the surface profile of the workpiece was better than that of the opposite direction. The speed ratio of the grinding wheel to the workpiece had a significant influence on the surface trajectory distribution and material removal uniformity. When the speed ratio was irrational, the trajectory distribution was more uniform. At a lower speed ratio, the surface profile of the workpiece was better. Although the simulation results and the experimental results had a good consistency in the trend, the simulated values were obviously smaller than the experimental values, which indicated that the material removal uniformity based on grain trajectories was not the only influencing factor of the phenomenon of convex in the middle of the workpiece during double side grinding.

Nitrate [Formula: see text] pollution of surface and groundwater systems is a major problem globally. For some time now wetlands have been considered potential systems for improving water quality. Nitrate dissolved in water moving through wetlands can be removed through different processes, such as the denitrification process, where heterotrophic facultative anaerobic bacteria use [Formula: see text] for respiration, leading to the production of nitrogen (N2) and nitrous oxide (N2O) gases. Nitrate removal and emission of N2O in wetlands can vary spatially, depending on factors such as vegetation, hydrology and soil structure. This study intended to provide a better understanding of the spatial variability and processes involved in [Formula: see text] removal and emission of N2O in riparian wetland soils. We designed a laboratory experiment simulating surface water flow through soil columns collected from different sites dominated by different plant species within a wetland. Water and gas samples for [Formula: see text] and N2O analyses were collected every 5 days for a period of 30 days. The results revealed significant removal of [Formula: see text] in all the soil columns, supporting the role of riparian wetland soils in removing nitrogen from surface runoff. Nitrate removal at 0 and 10cm depths in sites dominated by Phragmites australis and Carex schnimdtii was significantly higher than in the site dominated by Calamagrostis epigeio. Nitrous oxide emissions varied spatially and temporally with negative flux observed in sites dominated by P. australis and C. schnimdtii. These results reveal that in addition to the ability of wetlands to remove [Formula: see text], some sites within wetlands are also capable of consuming N2O, hence mitigating not only agricultural nitrate pollution but also climate change.

In the abrasive grinding hardening (AGH) of metal materials, the microstructure of the surface changes under the action of the intense grinding heat and forms the evolution layer covering the grinding surface with unique mechanical properties. The effective control of microstructure in the layer has great practical significance for obtaining high-performance surfaces. However, the formation mechanism of evolution layer is not well revealed and few quantitative investigations on microstructure phase content and morphology, which hinders the development of advanced grinding technology and surface performance characterization methods. A novel digital twin model is proposed; the spatial–temporal distribution of grinding heat and the evolution of microstructure along the surface depth direction have been reproduced from the microscale. The results reveal the dynamic effect of grinding parameters on phase content and morphology of the evolution layer. Furthermore, the quantitative relationship between microstructure and surface macroscopic hardening characteristics has been explored, and a novel method is proposed to predict the surface hardness. This research enhances the understanding of the formation mechanisms of grinding hardened surface and is significant to realize effective control and accurate prediction of surface performance.

Firstly, simulation is used to analyze the temperature curve in pre-stress hardening grinding (PSHG). Then, according to the start and the end time of martensitic transformation, three time nodes are selected to study the pre-stress time characteristic; they are 1 s, 3 s, and 7 s after grinding. The influence of pre-stress on the initial temperature and content of martensite transformation in cooling is analyzed; the results indicate the content of martensite increases over the pre-stressed unloading time. To test the theory, experiments of PSHG with different unloading times are carried out. The microstructure of the grinding hardening surface is observed and explored by scanning electron microscopy (SEM). Then, the SEM images are binarized to get the martensite content on the hardening surface. The experimental results show martensite content is consistent with the theoretical analysis. Lath martensite and flake martensite can also be found in these pictures. Flake martensite slightly increases while unloading at 7 s, as it forms at a lower temperature. So the pre-stress time characteristic influences both the martensite content and the morphology of martensite formed.

Pre-stressed high-strength concrete pipe piles (PHC pipe piles) have been widely used in actual soft foundation treatment projects due to their reliable quality, fast construction, assembly line production, and environmental friendliness. However, large-scale slip damage still occurs in construction projects. In order to reduce and avoid such accidents, a highway in Guangdong (section K31+100~K31+388) was taken as an example for this study. Plaxis 2D software (V22.01.00) was used to establish a PHC pipe pile composite roadbed model and investigate the effects of tie beam form, pile lengths, pile spacings, pile verticality, and embankment filling loading modes on the settlement and stability of the composite roadbed. The results show that the original treatment plan, which had the form of a PHC pipe pile with caps, had a low horizontal bearing capacity and a poor anti-disturbance ability, leading to the occurrence of a landslide accident. A comparison of different structural forms revealed that the longitudinal and transverse tie beam form was the most stable, followed by the transverse tie beam form, longitudinal tie beam form, PHC pipe pile form with caps, and PHC pipe pile form without caps. Compared to the structural form of PHC pipe piles with pile caps, the stabilities of the transverse tie beam form and the longitudinal tie beam form were improved by 42.47% and 38.61%, respectively, while that of the longitudinal and transverse tie beam form was improved by 50.87%. The application of longitudinal and transverse tie beams effectively reduced the settlement of the composite roadbed, as confirmed by both measured data and finite element analysis. This structure achieved the desired vertical settlement control and lateral anti-slip effects.

Cloud and snow detection is one of the most significant tasks for remote sensing image processing. However, it is a challenging task to distinguish between clouds and snow in high-resolution multispectral images due to their similar spectral distributions. The shortwave infrared band (SWIR, e.g., Sentinel-2A 1.55–1.75 µm band) is widely applied to the detection of snow and clouds. However, high-resolution multispectral images have a lack of SWIR, and such traditional methods are no longer practical. To solve this problem, a novel convolutional neural network (CNN) to classify cloud and snow on an object level is proposed in this paper. Specifically, a novel CNN structure capable of learning cloud and snow multiscale semantic features from high-resolution multispectral imagery is presented. In order to solve the shortcoming of “salt-and-pepper” in pixel level predictions, we extend a simple linear iterative clustering algorithm for segmenting high-resolution multispectral images and generating superpixels. Results demonstrated that the new proposed method can with better precision separate the cloud and snow in the high-resolution image, and results are more accurate and robust compared to the other methods.

To address limitations in conventional static load tests for composite foundations, a method utilizing an elastic cushion layer is proposed to accurately simulate subgrade behavior, focusing on a highway project in Guangdong Province. Initial finite element calculations justify the elastic cushion layer introduction. Functional correlations are established between the stab deformation of the piles and the thickness, modulus and the pile-soil stress ratio. The reasonable value of the elastic modulus is taken as 4 – 10 MPa when the elastic cushion layer thickness is 60 mm. Lab and field tests of cement fly-ash gravel (CFG) pile composite foundations assess settlement variations and pile-soil stress ratios from the proposed improvements. Results reveal the superior performance of the elastic cushion layer over the sand cushion layer, effectively mimicking embankment subgrade layers and reducing rigid constraints on the loading plate. The elastic cushion layer exhibits a significant stress-regulating effect, allowing the transition from the original “100 – 150 mm sand cushion layer + loading plate” to “less than 100 mm sand cushion layer + 60 mm elastic cushion layer (8 MPa) + loading plate”. This adjustment enhances the practical role of the subgrade in the composite foundation, improving the accuracy and feasibility of static load testing methods.