Search Results (896)

To address the limitations of the existing cotton seedling growth prediction methods in field environments, specifically, poor representation of spatiotemporal features and low visual fidelity in texture rendering, this paper proposes an algorithm for the prediction of cotton seedling growth from images based on FCA-STNet. The model leverages historical sequences of cotton seedling RGB images to generate an image of the predicted growth at time t + 1 and extracts 37 phenotypic traits from the predicted image. A novel STNet structure is designed to enhance the representation of spatiotemporal dependencies, while an Adaptive Fine-Grained Channel Attention (FCA) module is integrated to capture both global and local feature information. This attention mechanism focuses on individual cotton plants and their textural characteristics, effectively reducing the interference from common field-related challenges such as insufficient lighting, leaf fluttering, and wind disturbances. The experimental results demonstrate that the predicted images achieved an MSE of 0.0086, MAE of 0.0321, SSIM of 0.8339, and PSNR of 20.7011 on the test set, representing improvements of 2.27%, 0.31%, 4.73%, and 11.20%, respectively, over the baseline STNet. The method outperforms several mainstream spatiotemporal prediction models. Furthermore, the majority of the predicted phenotypic traits exhibited correlations with actual measurements with coefficients above 0.8, indicating high prediction accuracy. The proposed FCA-STNet model enables visually realistic prediction of cotton seedling growth in open-field conditions, offering a new perspective for research in growth prediction. Full article

This study was conducted in the context of China’s latest “double carbon” policy. The objective of this study was twofold: firstly, to examine the characteristics of traditional Chinese residential skywell; and secondly, to investigate and develop climate-adaptive technologies for these structures. To this end, a study was conducted on the Huizhou skywell architecture in China. Firstly, we obtained a large amount of basic data, such as traditional buildings and skywell parameters in Huizhou through field research and on-site mapping. Second, we combined a large number of parameters and typical cases to analyze the data and determine a more scientifically typical model of Huizhou architecture and experimental coverage of skywell data. Different shapes and sizes of skywell were formed by changing the combination of skywell length and width, and the indoor wind environments of these skywell dwelling models were simulated one by one using PHOENIX (v2016) software. Finally, the data obtained from these simulations are analyzed using the variable control method, and the simulated indoor wind environments of skywells under different scale combinations in terms of skywell length, width, and length–width coupling effects are summarized and compared. The following conclusions were drawn: (1) The length of the skywell has a certain effect on all indoor wind environments, and the variation in indoor wind speed is smallest when the length of the skywell is 7.5 m. When selecting the design size of the skywell, the length of the skywell can be increased accordingly. (2) The width of the skywell for the indoor wind environment is divided into two cases, when the length of the skywell is less than 3.75 m, increasing the width of the skywell will make the indoor wind environment more unstable. However, when the length of the skywell is greater than 3.75 m, the width of the skywell is positively related to the comfort of the indoor wind environment. (3) The area of the skywell should not be too large, usually between 11.25 m² and 18.75 m². A slender skywell is more likely to provide a comfortable indoor wind environment. (4) After extensive evaluation, we found that the comfort of the indoor wind environment is high when the width of the skywell is 2 m. The optimum dimensions for the ventilation performance of the skywell are 7.5 m in length and 2 m in width. Full article

In the process of plant protection for fruit trees using rotary-wing UAVs, challenges such as droplet drift, insufficient canopy penetration, and low agrochemical utilization efficiency remain prominent. Among these, the uncertainty in the spatio-temporal distribution of downwash airflow is a key factor contributing to non-uniform droplet deposition and increased drift. To address this issue, we developed a wind field numerical simulation model based on an improved hierarchical leaf density model to clarify the spatio-temporal characteristics of downwash airflow, the scale of turbulence regions, and their effects on internal canopy airflow under varying flight altitudes and different rotor speeds. Field experiments were conducted in orchards to validate the accuracy of the model. Simulation results showed that the average error between the simulated and measured wind speeds inside the canopy was 8.4%, representing a 42.11% reduction compared to the non-hierarchical model and significantly improving the prediction accuracy. The coefficient of variation (CV) was 0.26 in the middle canopy layer and 0.29 in the lower layer, indicating a decreasing trend with an increasing canopy height. We systematically analyzed the variation in turbulence region scales under different flight conditions. This study provides theoretical support for optimizing UAV operation parameters to improve droplet deposition uniformity and enhance agrochemical utilization efficiency. Full article

Wind power output sequences exhibit strong randomness and intermittency characteristics; traditional single forecasting models struggle to capture the internal features of sequences and are highly susceptible to interference from high-frequency noise and predictive accuracy is still notably poor at the peaks where the power curve undergoes abrupt changes. To address the poor fitting at peaks, a short-term wind power forecasting method based on the improved Informer model is proposed. First, the temporal convolutional network (TCN) is introduced to enhance the model’s ability to capture regional segment features along the temporal dimension, enhancing the model’s receptive field to address wind power fluctuation under varying environmental conditions. Next, a discrete cosine transform (DCT) is employed for adaptive modeling of frequency dependencies between channels, converting the time series data into frequency domain representations to extract its frequency features. These frequency domain features are then weighted using a channel attention mechanism to improve the model’s ability to capture peak features and resist noise interference. Finally, the Informer generative decoder is used to output the power prediction results, this enables the model to simultaneously leverage neighboring temporal segment features and long-range inter-temporal dependencies for future wind-power prediction, thereby substantially improving the fitting accuracy at power-curve peaks. Experimental results validate the effectiveness and practicality of the proposed model; compared with other models, the proposed approach reduces MAE by 9.14–42.31% and RMSE by 12.57–47.59%. Full article

Dual three-phase PMSMs (DTP-PMSMs) have attracted increasing attention in the field of robotics industry for their higher power density and enhanced fault-tolerant ability. The non-phase-shifted DTP-PMSM (NPSDTP-PMSM), which shows naturally prevailed performance on zero-sequence current (ZSC) suppression, necessitates the investigation on the control method with improved fault-tolerant performance. In this paper, a novel fault-tolerant control (FTC) method for NPSDTP-PMSM is proposed, which concurrently simultaneously reduces copper loss and suppresses torque ripple under single and dual open phase fault. Firstly, the mathematical model of NPSDTP-PMSM is established, where the ZSC self-suppressing mechanism is revealed. Based on which, investigations on open phase fault and the copper loss characteristics for NPSDTP-PMSM are conducted. Subsequently, a novel fault-tolerant control method is proposed for NPSDTP-PMSM, where the torque ripple is reduced by mutual cancellation of harmonic torques from two winding sets and minimized copper loss is achieved based on the convex characteristic of copper loss. Experimental validation on an integrated robotic joint motor platform confirms the effectiveness of the proposed method. Full article

Accurate prediction of drifting trajectories is essential for improving the operational efficiency of maritime search and rescue (SAR), particularly within the complex geomorphological settings of island and reef regions, such as those in the South China Sea. This study investigates the drift characteristics of life rafts under varying loading conditions across both open-sea and island–reef regions. Comprehensive field experiments were conducted over 15 days in the waters around the Wanshan Archipelago, using advanced instruments to collect wind, current, and drift trajectory data. Based on these observations, two models—the AP98 leeway model and a BP neural network model—were developed and validated. The results show that the AP98 model performs better in open-sea conditions, whereas the BP neural network provides more accurate predictions in island and reef areas with complex environmental factors. A Monte Carlo simulation was also integrated to enhance the robustness of drift area predictions. These findings offer valuable insights into life raft drift behavior in complex marine environments and provide technical support for improving SAR operations in island–reef regions. Full article

The large-scale integration of wind power, photovoltaic systems, and energy storage systems (ESSs) into power grids has increasingly influenced the transient stability of power systems due to their dynamic response characteristics. Considering the commercial confidentiality of core control parameters from equipment manufacturers, parameter identification has become a crucial approach for analyzing ESS dynamic behaviors during high-voltage ride-through (HVRT) and low-voltage ride-through (LVRT) and for optimizing control strategies. In this study, we present a multidimensional feature-integrated parameter identification framework for ESSs, combining a multi-scenario voltage disturbance testing environment built on a real-time laboratory platform with field-measured data and enhanced optimization algorithms. Focusing on the control characteristics of energy storage converters, a non-intrusive identification method for grid-connected control parameters is proposed based on dynamic trajectory feature extraction and a hybrid optimization algorithm that integrates an improved particle swarm optimization (PSO) algorithm with gradient-based coordination. The results demonstrate that the proposed approach effectively captures the dynamic coupling mechanisms of ESSs under dual-mode operation (charging and discharging) and voltage fluctuations. By relying on measured data for parameter inversion, the method circumvents the limitations posed by commercial confidentiality, providing a novel technical pathway to enhance the fault ride-through (FRT) performance of energy storage systems (ESSs). In addition, the developed simulation verification framework serves as a valuable tool for security analysis in power systems with high renewable energy penetration. Full article

A system of field protective forest belts (FPFBs) was created in the middle of the 20th century in Southern Dobrudzha (Northern Bulgaria) to reduce wind erosion, improve soil moisture storage, and increase agricultural crop yields. Since 2020, prolonged climatic drought during growing seasons and the advanced age of trees have adversely impacted the health status of planted species and resulted in the decline and dieback of the FPFBs. Physiologically stressed trees have become less able to resist pests, such as insects and diseases. In this work, an original new methodology for the integrated assessment of the condition of FPFBs and their protective capacity is presented. The presented methods include the assessment of structural and functional characteristics, as well as the health status of the dominant tree species. Five indicators were identified that, to the greatest extent, present the ability of forest belts to perform their protective functions. Each indicator was evaluated separately, and then an overlay analysis was applied to generate an integrated assessment of the condition of individual forest belts. Three groups of FPFBs were differentiated according to their condition: in good condition, in moderate condition, and in bad condition. The methodology was successfully tested in Southern Dobrudzha, but it could be applied to other regions in Bulgaria where FPFBs were planted, regardless of their location, composition, origin, and age. This methodological approach could be transferred to other countries after adapting to their geo-ecological and agroforest specifics. The methodological approach is an informative and useful tool to support decision-making about FPFB management, as well as the proactive planning of necessary forestry activities for the reconstruction of degraded belts. Full article

With the large-scale global deployment of photovoltaics (PV), traditional monitoring technologies face challenges such as wiring difficulties, high energy consumption, and high maintenance costs in remote or complex terrains, which limit long-term environmental sensing. Therefore, energy-harvesting systems are crucial for the intelligent operation of photovoltaic systems; however, their deployment depends on the accurate mapping of wind energy fields and solar irradiance fields. This study proposes a multi-scale simulation method based on computational fluid dynamics (CFD) to optimize the placement of energy-harvesting systems in photovoltaic power plants. By integrating wind and irradiance distribution analysis, the spatial characteristics of airflow and solar radiation are mapped to identify high-efficiency zones for energy harvesting. The results indicate that the top of the photovoltaic panel exhibits a higher wind speed and reflected irradiance, providing the optimal location for an energy-harvesting system. The proposed layout strategy improves overall energy capture efficiency, enhances sensor deployment effectiveness, and supports intelligent, maintenance-free monitoring systems. This research not only provides theoretical guidance for the design of energy-harvesting systems in PV stations but also offers a scalable method applicable to various geographic scenarios, contributing to the advancement of smart and self-powered energy systems. Full article

The non-metallic armored optoelectronic cable (NAOC) serves as a critical component in deep-sea scientific winch systems. Due to its low density and excellent corrosion resistance, it has been widely adopted in marine exploration. However, as the operational water depth increases, the NAOC is subjected to multi-layer winding on the drum, resulting in a cumulative temperature rise that can severely impair insulation performance and compromise the safety of deep-sea operations. To address this issue, this paper conducts temperature rise experiments on NAOCs using a distributed temperature sensing test rig to investigate the effects of the number of winding layers and current amplitude on their temperature rise characteristics. Based on the experimental results, an electromagnetic thermal multi-physics field coupling simulation model is established to further examine the influence of these factors on the maximum operation time of the NAOC. Finally, a multi-variable predictive model for maximum operation time is developed, incorporating current amplitude, the number of winding layers, and ambient temperature, with a fitting accuracy of 97.92%. This research provides theoretical and technical support for ensuring the safety of deep-sea scientific operations and improving the reliability of deep-sea equipment. Full article

This paper presents the results of laboratory tests on the intensity of mass and heat exchange in a polytunnel, with a focus on the synergy between the polytunnel and a stone accumulator. The subject of study was a standard polytunnel made of double polythene sheathing. In the process of selecting the appropriate working conditions for such a polytunnel, the characteristic operating parameters were modeled and verified. They were related to the process of mass and energy exchange, which takes place in regular controlled-environment agriculture (CEA). Then, experimental tests of a heat accumulator on a fixed stone bed were carried out. The experiments were carried out for various accumulator surfaces ranging from 18.7 m² to 74.8 m², which was measured perpendicularly to the heat medium. To standardize the results obtained, the analysis included the unit area of the accumulator and the unit time of the experiment. In this way, 835 heat and mass exchange events were analyzed, including 437 accumulator charging processes and 398 discharging processes from April to October, which is a standard period of polytunnel use in the Polish climate. During the tests, internal and external parameters of the process were recorded, such as temperature, relative humidity, solar radiation, wind speed and air flow speed in the accumulator system. Based on the parameters, a set of empirical relationships was developed using mathematical modeling. This provided the foundation for calculating heat gains as a result of its storage in a stone accumulator and its discharging process. The research results, including the developed dependencies, not only fill the scientific gap in the field of heat storage, but can also be used in engineering design of polytunnels supported by a heat storage system on a stone bed. In addition, the proposed methodology can be used in the study of other heat accumulators, not only in plant production facilities. Full article

Traditional motor temperature rise testing generally uses temperature sensors. To solve problems such as sensor detachment, aging, and space occupation, this study takes a three-phase asynchronous motor as an example to propose a method for building a temperature rise monitoring model driven by a multi-physics field model based on the digital twin framework of power equipment. A twin monitoring model with defined input–output parameters is constructed to solve the problems of measurement inconvenience in traditional methods. Firstly, the losses of the iron core and the winding copper in the motor were obtained through electromagnetic field simulation. Secondly, the temperature distribution of the motor stator was obtained based on the bidirectional coupling characteristics of the magnetic and thermal fields. Subsequently, a temperature field reduced-order model based on the proper orthogonal decomposition method was built in Twin Builder, achieving fast calculation of the motor stator temperature. Finally, using the YE3-80M1-4 motor as the experimental subject, the model’s output results were compared with and validated against the experimental results. The results indicate that the simulation time of the reduced-order model is 2.1 s, and the relative error compared with the test values is within 5%, which confirms the practical applicability of the proposed method. Full article

Boao Jade Beach, on the east coast of Hainan Island, is a typical sandy beach and is one of the areas where typhoons frequently land in Hainan. This study examined wind speed, wind direction, and sediment transport data obtained from field meteorological stations and omnidirectional sand accumulation instruments from 2020 to 2024 to study the coastal aeolian environment and sediment transport distribution characteristics in the region. The findings provide a theoretical basis for comprehensive analyses of the evolution of coastal aeolian landforms and the evaluation and control of coastal aeolian hazards. The research results showed the following: (1) The annual average threshold wind velocity for sand movement in the study area was 6.13 m/s, and the wind speed frequency was 20.97%, mainly dominated by easterly winds (NNE, NE) and southerly winds (S). (2) The annual drift potential (DP) and resultant drift potential (RDP) of Boao Jade Belt Beach from 2020 to 2024 were 125.99 VU and 29.59 VU, respectively, indicating a low-energy wind environment. The yearly index of directional wind variability (RDP/DP) was 0.23, which is classified as a small ratio and indicates blunt bimodal wind conditions. The yearly resultant drift direction (RDD) was 329.41°, corresponding to the NNW direction, indicating that the sand on Boao Jade Belt Beach is generally transported in the southwest direction. (3) When the measured data from the sand accumulation instrument in the study area from 2020 to 2024 were used for a statistical analysis, the results showed that the total sediment transport rate in the study area was 39.97 kg/m·a, with the maximum sediment transport rate in the S direction being 17.74 kg/m·a. These results suggest that, when sand fixation systems are constructed for relevant infrastructure in the region, the direction of protective forests and other engineering measures should be perpendicular to the net direction of sand transport. Full article

The calculation and evaluation of wave loads represent a critical component in the design process of offshore wind turbines, which is of significant value for ensuring the safety and stability of offshore wind turbines during operation. In recent years, as the offshore wind power industry has extended into deep-sea areas, wind turbines and their foundation structures have gradually increased in scale. Due to the continuously growing diameter of fixed foundation structures, the wave loads they endure can no longer be evaluated solely by traditional methods. This study simplifies the monopile foundation structure of wind turbines into an upright circular cylinder. The open-source CFD platform OpenFOAM is employed to establish a numerical wave tank, and large eddy simulation (LES) models are used to conduct numerical simulations of its force-bearing process in wave fields. Through this approach, the hydrodynamic loads experienced by the single-cylinder structure in wave fields and the surrounding wave field data are obtained, with further investigation into its hydrodynamic characteristics under different wave environments. By analyzing the wave run-up distribution around cylinders of varying diameters and their effects on incident waves, a more suitable value range for traditional theories in engineering design applications is determined. Additionally, the variation laws of horizontal wave loads on single-cylinder structures under different parameter conditions (such as cylinder diameter, wave steepness, water depth, etc.) are thoroughly studied. Corresponding hydrodynamic load coefficients are derived, and appropriate wave force calculation methods are established to address the impact of value errors in hydrodynamic load coefficients within the transition range from large-diameter to small-diameter cylinders in traditional theories on wave force evaluation. This contributes to enhancing the accuracy and practicality of engineering designs. Full article

The sudden increase of fluxes of quasi-trapped energetic electrons under the Earth’s radiation belt (ERB) has remained a puzzling phenomenon for decades. It is known as enhancements of forbidden energetic electrons (FEEs). The FEE enhancements are occasionally observed by low-Earth orbit NOAA/POES satellites. Previously, no strong correlation was established between FEEs and geomagnetic activity, while external control of FEE occurrence by solar activity and interplanetary parameters was revealed on a long time-scale. Two important questions are still open: (1) key parameters of the mechanism and (2) solar wind drivers or triggers. In the present study we conducted detailed analysis of three FEE events that occurred during the greatest geomagnetic storms, which dramatically affected space weather. The FEE enhancements occurred under northward IMF and, thus, Bz and convection electric fields could have been neither driver nor trigger. We found that an abrupt and significant change in solar wind pressure is a key solar wind driver of the FEE enhancements observed. The characteristic time of FEE injection from the inner edge of the ERB at L-shell 1.2 to the forbidden zone at L < 1.1 was estimated to be 10–20 min. In the mechanism of ExB drift, this characteristic time corresponds to the radial inward transport of electrons caused by a transient electric field with the magnitude ~10 mV/m. Full article