Search Results (162)

The high-proportion integration of renewable energy sources, represented by wind power and photovoltaics, into active distribution networks (ADNs) can effectively alleviate the pressure associated with advancing China’s dual-carbon goals. However, the high uncertainty in renewable energy output leads to increased system voltage fluctuations and localized voltage violations, posing safety challenges. Consequently, research on optimal dispatch for ADNs with a high penetration of renewable energy has become a current focal point. This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. Subsequently, it introduces optimization dispatch models for ADNs that focus on three key objectives: safety, economy, and low carbon emissions. Furthermore, addressing the challenge of solving non-convex and nonlinear models, the paper highlights model reformulation strategies such as semidefinite relaxation, second-order cone relaxation, and convex inner approximation methods, along with summarizing relevant intelligent solution algorithms. Additionally, in response to the high uncertainty of renewable energy output, it reviews stochastic optimization dispatch strategies for ADNs, encompassing single-stage, two-stage, and multi-stage approaches. Meanwhile, given the promising prospects of large-scale deep reinforcement learning models in the power sector, their applications in ADN optimization dispatch are also reviewed. Finally, the paper outlines potential future research directions for ADN optimization dispatch. Full article

Blade tip leakage vortex (TLV) is a critical phenomenon in hydraulic machinery, which can significantly affect the internal flow characteristics and deteriorate the hydraulic performance. In this paper, the blade tip leakage flow and TLV characteristics in a novel dishwasher pump were investigated. The correlation between the vorticity distribution in various directions and the leakage vortices was established within a rotating coordinate system. The results show that the TLV in a composite impeller can be categorized into initial and secondary leakage vortices. The initial leakage vortex originates from the evolution of two corner vortices that initially form at different locations within the blade tip clearance. This vortex induces pressure fluctuations at the impeller inlet; its shedding is identified as the primary contributor to localized energy loss within the flow passage. These findings provide insights into TLVs in complex pump geometries and provide solutions for future pump optimization strategies. Full article

Transpiration cooling that utilizes the phase change of a liquid coolant is recognized as an effective thermal protection technique for extreme environments. However, the introduction of phase change within the porous structure brings about challenges, such as vapor blockage, pressure fluctuations, and temperature inversion, which critically influence system reliability. This study conducts numerical analyses of coupled processes of heat transfer, flow, and phase change in transpiration cooling using a Two-Phase Mixture Model. The simulation incorporates a Local Thermal Non-Equilibrium approach to capture the distinct temperature fields of the solid and fluid phases, enabling accurate prediction of the thermal response within two-phase and single-phase regions. The results reveal that under low heat flux, dominant capillary action suppresses dry-out and expands the two-phase region. Conversely, high heat flux causes vaporization to overwhelm the capillary supply, forming a superheated vapor layer and constricting the two-phase zone. The analysis also explains a paradoxical pressure drop, where an initial increase in flow rate reduces pressure loss by suppressing the high-viscosity vapor phase. Furthermore, a local temperature inversion, where the fluid becomes hotter than the solid matrix, is identified and attributed to vapor counterflow and its subsequent condensation. Full article

The timing accuracy of eLoran systems is susceptible to meteorological fluctuations, with medium-to-long-range propagation delay variations reaching hundreds of nanoseconds to microseconds. While conventional models have been widely adopted for short-range delay prediction, they fail to accurately characterize the coupled effects of multiple factors in long-range scenarios. This study theoretically examines the influence mechanisms of temperature, humidity, and atmospheric pressure on signal propagation delays, proposing a hybrid prediction model integrating meteorological data with a back-propagation neural network (BPNN) through path-weighted Pearson correlation coefficient analysis. Long-term observational data from multiple differential reference stations and meteorological stations reveal that short-term delay fluctuations strongly correlate with localized instantaneous humidity variations, whereas long-term trends are governed by cumulative temperature–humidity effects in regional environments. A multi-tier neural network architecture was developed, incorporating spatial analysis of propagation distance impacts on model accuracy. Experimental results demonstrate enhanced prediction stability in long-range scenarios. The proposed model provides an innovative tool for eLoran system delay correction, while establishing an interdisciplinary framework that bridges meteorological parameters with signal propagation characteristics. This methodology offers new perspectives for reliable timing solutions in global navigation satellite system (GNSS)-denied environments and advances our understanding of meteorological–electromagnetic wave interactions. Full article

Jilin Province is an important ecological security barrier and major grain-producing region in northeast China, playing a crucial role in ensuring ecological security and promoting regional sustainable development. This study examines ecological resilience from three dimensions: resistance, adaptability, and resilience. Based on multi-source data from 2000 to 2020, an ecological resilience indicator system was constructed. Spatial autocorrelation and OPGD models were employed to analyze temporal and spatial evolution and the driving mechanisms. The results indicate that ER exhibits an overall spatial pattern of “high in the east, low in the west, and under pressure in the central region.” The eastern mountainous areas demonstrate high and stable resilience, while the central plains and western ecologically fragile regions exhibit weaker resilience. In terms of resistance, the eastern mountainous regions are primarily forested, with high and sustained ESV, while the western sandy edge regions primarily have low ESV, making ecosystems susceptible to disturbance. In terms of adaptability, the large-scale farmland landscapes in the central regions exhibit strong disturbance resistance, while water resource adaptability in the western ecologically fragile regions has locally improved. However, adaptability in the eastern mountainous regions is relatively low due to development impacts. In terms of resilience, the eastern core regions possess stable recovery capabilities, while the central and western regions generally exhibit lower resistance with fluctuating changes. Between 2000 and 2020, the ecological resilience Moran’s I index slightly decreased from 0.558 to 0.554, with the spatial aggregation pattern remaining largely stable. Among the driving factors, DEM remains the most stable. The influence of NDVI has weakened, while temperature (TEM) and NPP-VIIRS have become more significant. Overall, factor interactions have grown stronger, as reflected by the q-value rising from 0.507 to 0.5605. This study provides theoretical support and decision-making references for enhancing regional ecological resilience, optimizing ecological spatial layout, and promoting sustainable ecosystem management. Full article

Our study aims to analyze the spatiotemporal dynamics of six lakes in Ifrane National Park (Morocco) using remote sensing and satellite imagery over the period 2000–2024. Spectral indices such as NDWI, MNDWI, EWI, AWEI, and ANDWI were employed to extract water bodies from Landsat images, while the NDVI index was used to identify irrigated agricultural lands. Additionally, the SPEI and RDI indices were applied to assess the impact of climate fluctuations on the hydrological evolution of the lakes. The results reveal an alarming reduction in lake surface areas, with some lakes having completely dried up. This decline is correlated with decreased precipitation and the expansion of irrigated agricultural lands, highlighting the impact of human activities. The analysis of hydrological correlations between lakes demonstrates significant interactions, although some indices show disparities. The rapid expansion of agricultural land, particularly arboriculture, increases pressure on water resources. These changes threaten local biodiversity and heighten the socio-economic vulnerability of surrounding populations. Full article

This study addresses inlet flow distribution and pressure pulsation-induced vibration in LNG dual-pump parallel systems. We investigate an LNG dual-submerged pump tower system. Our approach combines computational fluid dynamics with vortex dynamics theory. We examine inlet flow characteristics under different flow conditions. Pressure pulsation propagation patterns are analyzed. System stability mechanisms are investigated. A 3D model incorporates inducers, impellers, guide vanes, outlet sections, and base structures. The SST k-ω turbulence model and Q-criterion vortex identification reveal key features. Results show minimal head differences during parallel operation. The inlet flow field remains uniform without significant vortices. However, local low-velocity zones beneath the base may cause flow separation at low flows. Pressure pulsations are governed by guide vane rotor–stator interactions. These disturbances propagate backward to impellers and inducers. Outlet sections show asymmetric pressure fluctuations. This asymmetry results from spatial positioning differences. Complex base geometries generate low-intensity vortices. Vortex intensity stabilizes at higher flows. These findings provide theoretical foundations for vibration suppression. Full article

The paper presents a case study on the impact of a shallow landslide in overconsolidated clays, which was triggered during the winter of 2004–2005 due to exceptionally high pore pressures, on the operativity and serviceability of a key road artery in Sicily. During the period from 2004 to 2021, the landslide experienced several reactivations, particularly during the winter months when increased rainfall led to rising pore water pressures. These recurrent events resulted in temporary road closures and continuous restoration efforts, causing significant inconvenience for local communities and substantial economic losses for commercial, tourism, and agricultural activities in the area. In 2018, a comprehensive study was launched to reconstruct the detailed geotechnical model of the landslide, analysing its mechanical and kinematic characteristics, pore pressure regime, the depth and geometry of the sliding surface, and the causes of the landslide. The study indicates that the primary causes of both the initial landslide and its subsequent reactivations were the poor mechanical properties of the involved soils and seasonal fluctuations in pore water pressures. To ensure long-term stabilisation, the most suitable interventions were identified as the permanent reduction of pore pressures through the installation of drainage trenches and the construction of a road embankment using gabions, which also serve as drainage structures. These measures are highly effective, relatively cost-efficient, easy to implement, and environmentally sustainable. Full article

Monitoring the blast furnace shaft static pressure is crucial for maintaining a stable ironmaking process. Traditional rule-based methods and manual inspections suffer from high labor costs and inconsistent standards. This article proposes a new unsupervised anomaly detection framework that combines adversarial autoencoder with variational mode decomposition (VMD). Firstly, using VMD combined with sample entropy calculation and clustering algorithm, the trend, period, and other components of multidimensional signals are extracted, and then these components are integrated into an improved adversarial training autoencoder to detect global and local anomalies. The proposed method has an accuracy of 0.95, a recall rate of 0.91, and an F1 score of 0.93. Which demonstrates the method effectively captures multi-scale anomalies including value bias, morphological changes, and sudden fluctuations, while providing analysts with interpretable anomaly detail diagnosis. Full article

To enhance the precision of regional agricultural drought resilience evaluation, a convolutional neural network optimized with Adam with weight decay (AdamW–CNN) was constructed. Based on local agricultural economic development regulations and utilizing the Driving Force–Pressure–State–Impact–Response (DPSIR) conceptual model, sixteen indicators of agricultural drought resilience were selected. Subsequently, data preprocessing was conducted for Qiqihar City, Heilongjiang Province, China, which encompasses an area of 42,400 km². The drought resilience was accurately assessed based on the developed AdamW–CNN model from 2000 to 2021 in the study area. The key driving factors behind the spatiotemporal evolution of drought resilience were identified using gray relational analysis, and the future evolution trend of agricultural drought resilience was revealed through Ridge regression analysis improved by the Kepler optimization algorithm (KOA–Ridge). The results indicated that the agricultural drought resilience in Qiqihar City exhibited a trend of initial fluctuations, followed by a significant increase in the middle phase, and then stable development in the later stage. Precipitation, investment in the primary industry, grain output per unit of cultivated area, per capita cultivated land area, and the proportion of effective irrigation area were the primary driving factors in the study area. By simulating the drought resilience index of four typical regions and analyzing its evolution, it was found that the AdamW–CNN model, combined with the KOA–Ridge model, has greater advantages over the RMSProp-CNN model and the CNN model in terms of fit, stability, reliability, and evaluation accuracy. These findings provide a robust model for measuring agricultural drought resilience, offering valuable insights for regional drought prevention and management. Full article

Trade ports are the first places where alien species invade and the source of their spread to other areas. Controlling invasions in these regions can effectively reduce invasion pressure and disrupt the spread pathways of invasive species, thereby significantly reducing their threat to local ecosystems and biodiversity loss. Based on 595 field survey plots, the Generalized Linear Model (GLM) and Species Distribution Model (MaxEnt) were employed to analyze and predict the invasion mechanisms and future possible distribution of Solidago canadensis in the Ningbo Port, China. The results indicate that the invasion of S. canadensis in the Ningbo Port was particularly severe, with a 67.7% occurrence rate of all sampling plots in the field survey, and a risk level classified as Grade 1. Biodiversity (p < 0.001) and the minimum temperature of the coldest month (p < 0.01) significantly affect the invasiveness. Highly diverse communities could resist the invasion of alien species, which support Elton’s diversity–invasibility hypothesis. Low temperatures had a restrictive effect on the invasion of S. canadensis. The total suitable area continued to expand under three different climate change scenarios compared to current conditions (increased by 3.73%, 5.67%, and 3.74% by the 2070s). The total potential habitat area of S. canadensis reached its maximum extent (89.77%) under the medium greenhouse gas emission scenario in the 2050s. Meanwhile, the medium suitable area exhibited the greatest fluctuation among the three climate scenarios. Under the low emission condition, the medium suitable area of S. canadensis diminished by 63.10 km², but in the medium and high emission condition, its area expanded by 91.13 km² and 16.20 km², respectively. Under future climate warming scenarios, the invasion risk of S. canadensis in Ningbo Port will continue to increase. The results of our study reveal the diffusion mechanisms of invasive plants at the colonization source, providing important theoretical support for invasive alien species’ initial prevention and control. Full article

Green development is an important path to breaking the “growth-pollution” paradox and realizing the United Nations 2030 Agenda for Sustainable Development. Most of the countries along the “Belt and Road” are developing countries with fragile ecological environments, and the pressure of economic activities on environmental resources exceeds the global average, so the countries have a strong will to promote green development. Accurately grasping the level of green development and the dynamic evolution trend of BRI countries can help to explore the implementation effect of policies at a certain stage, and on this basis, exploring regional correlations and differences can help to provide data support for future regional cooperation and policy formulation. Based on this, this study comprehensively evaluates the level of green development in the BRI countries by constructing a multi-dimensional evaluation index system and then explores the correlation and regional differences of green development in the countries along the route by utilizing the Moran index and the Thiel index. The results indicate that the green development levels of BRI countries have shown an upward trend; the spatial association exhibited a fluctuating upward trend, with significant changes in local clustering characteristics. Overall disparities in green development levels were relatively small, with intra-group differences being the primary contributor to these disparities, and West Asia and the Middle East displayed larger variations in green development levels. This study provides policy recommendations for promoting green development in BRI countries. Full article

Promoting the intensive utilization of arable land is a critical strategy for addressing the scarcity problem of arable land resources and thus ensuring food security. However, public emergencies pose significant challenges to the intensive utilization of arable land. Based on the pressure-state response (PSR) model and taking Sichuan Province, known as China’s “Heavenly Granary”, as an example, this study constructs a suitable evaluation system and analyzes the variation trend of the intensive utilization of arable land from the perspective of public emergencies. Key factors constraining the intensive utilization of arable land are further analyzed using the obstacle diagnostic model. The findings of this study are as follows: (1) Despite the shocks of public emergencies, the intensive utilization level of arable land in Sichuan Province in China shows an overall upward trend, indicating a high level of resilience and adaptability. (2) The pressure to utilize arable land intensively in Sichuan exhibits periodic fluctuations, yet the state remains generally stable. The whole system shows positive adaptive responses to external pressures and contemporary conditions during the mid-to-late stages of the research period. Nevertheless, coordination among subsystems within the PSR framework remains suboptimal, and a dynamic equilibrium across the subsystems has not yet been achieved. (3) Obstacle factors constraining the intensive arable land utilization in Sichuan exhibit notable temporal variations. Early-period constraints centered on multiple cropping indexes, grain yield per unit area, and irrigation index, reflecting limitations of traditional agricultural production modes. In the later stages, key obstacles shifted to factors including per capita cultivated land, population density, and pesticide/fertilizer input index, highlighting the impediment effects caused by evolving socio-demographic dynamics influenced by public emergencies. The findings of this study reveal critical pathways for local governments to achieve sustainable arable land management amidst global uncertainties. Full article

In the context of global climate change and intensified anthropogenic pressures, the coordinated development of a social-ecological system (SES) faces unprecedented challenges, necessitating an enhanced understanding of complex system interactions to achieve SES sustainability. This study quantified water resource–water environment–social economy resilience (WR-WE-SEr) and four ecosystem services (ESs)—water yield (WY), habitat quality (HQ), soil retention (SR), and carbon storage (CS)—in Northwest China from 2010 to 2020. Intersystem interactions were analyzed using resilience theory, the InVEST model, and the coupling coordination degree (CCD) model. The key findings include the following: (1) Spatiotemporal evolution patterns (RQ1): WR-WE-SEr exhibited sustained growth with significant regional disparities (Qinghai > Xinjiang > Gansu > Shaanxi > Ningxia), predominantly driven by resistance-dominated dynamics. ESs showed spatial heterogeneity: WY was concentrated in humid areas but declined temporally, while HQ and CS aligned with vegetation/land cover. All ESs followed a “V”-shaped trajectory of initial decline and recovery, with localized fluctuations but regional stability. (2) Coordinated coupling relationships (RQ2): The CCD between WR-WE-SEr and ESs maintained temporal stability but mirrored ESs’ spatial patterns, characterized by a southeast–northwest diminishing gradient. Coordination hierarchy (CS > HQ > WY > SR) and regional performance (Shaanxi > Ningxia > Qinghai > Gansu > Xinjiang) revealed synergies between system resilience and ES provisioning capacity. Transitional coordination (dissonance to coordination) at the integrated ES level highlighted gradual optimization of human–nature interactions. These findings underscore the need for multidimensional strategies to enhance WR-WE-SE-ES synergies in Northwest China. Full article

Wheat, a cornerstone of Jordan’s food security and agricultural economy, has experienced fluctuating production dynamics. Population growth, climate variability, and the gradual integration of advanced farming technologies drive these fluctuations. As the population expands, the demand for wheat naturally escalates, placing increased pressure on local production capabilities. This study aimed to analyze the impact of demographic (population) and climatic parameters of rainfall and maximum and minimum temperature on wheat production in Jordan from 1995 to 2022. Geographic Information Systems (GIS) techniques and statistical analysis methods, specifically utilizing Geographically Weighted Regression (GWR), were used to analyze the relationship between wheat production and population within specific periods; this study revealed an inverse relationship of coefficient of determination with (R² = −0.56, −0.78 and −0.89) for the north, middle, and south regions of Jordan, respectively. A direct relationship between wheat production and rainfall and temperature is explored, especially in the southern areas of Jordan (R² = 0.63 and 0.81), respectively. Generally, rainfall accounted for (32.26%) of the variations in wheat production, while the minimum temperature contributed (30.74%). The effect of maximum temperature was less significant, explaining the variations (13.24%). GWR tests confirmed these climatic factors’ independence, indicating each’s direct impact on wheat production. However, the total decrease in wheat production from 1995 to 2022 comprised approximately 34.19% of production. However, the total reduction in wheat production is shown from 1995 to 2022, approximately 34.19% of production. This study recommends conducting further research to delve deeper into the interplay between population growth, climatic changes, and agricultural practices, exploring the potential for developing sustainable strategies to mitigate the decline in wheat production and ensure food security in Jordan. Full article