Search Results (121)

In the global energy sector, water-bearing reservoir-typed gas storage accounts for about 30% of underground gas storage (UGS) reservoirs and is vital for natural gas storage, balancing gas consumption, and ensuring energy supply stability. However, when constructing the UGS in the M gas reservoir, selecting suitable areas poses a challenge due to the complicated gas–water distribution in the multi-layered water-bearing gas reservoir with a long production history. To address this issue and enhance energy storage efficiency, this study presents an integrated geomechanical-hydraulic assessment framework for choosing optimal UGS construction horizons in multi-layered water-bearing gas reservoirs. The horizons and sub-layers of the gas reservoir have been quantitatively assessed to filter out the favorable areas, considering both aspects of geological characteristics and production dynamics. Geologically, caprock-sealing capacity was assessed via rock properties, Shale Gouge Ratio (SGR), and transect breakthrough pressure. Dynamically, water invasion characteristics and the water–gas distribution pattern were analyzed. Based on both geological and dynamic assessment results, the favorable layers for UGS construction were selected. Then, a compositional numerical model was established to digitally simulate and validate the feasibility of constructing and operating the M UGS in the target layers. The results indicated the following: (1) The selected area has an SGR greater than 50%, and the caprock has a continuous lateral distribution with a thickness range from 53 to 78 m and a permeability of less than 0.05 mD. Within the operational pressure ranging from 8 MPa to 12.8 MPa, the mechanical properties of the caprock shale had no obvious changes after 1000 fatigue cycles, which demonstrated the good sealing capacity of the caprock. (2) The main water-producing formations were identified, and the sub-layers with inactive edge water and low levels of water intrusion were selected. After the comprehensive analysis, the I-2 and I-6 sub-layer in the M 8 block and M 14 block were selected as the target layers. The numerical simulation results indicated an effective working gas volume of 263 million cubic meters, demonstrating the significant potential of these layers for UGS construction and their positive impact on energy storage capacity and supply stability. Full article

The performance of solar thermal systems for space heating and domestic hot water (DHW) production depends on the tilt angle of solar collectors, which governs the amount and seasonal distribution of captured solar radiation. This study evaluates the impact of fixed collector tilt angles on the annual solar fraction (SF) of a solar heating system designed for a typical single-family house located in Kraków, Poland (50° N latitude). A numerical model based on the f-Chart method was employed to simulate system performance under varying collector areas, storage tank volumes, heat exchanger characteristics, and DHW proportions. The analysis revealed that although total annual irradiation decreases with increasing tilt angle, the SF reaches a maximum at a tilt angle of approximately 60°, which is about 10° higher than the local geographic latitude. This configuration offers a favorable balance between winter energy gain and summer overheating mitigation. The results align with empirical recommendations in the literature and offer practical guidance for optimizing fixed-tilt solar heating systems in temperate climates. Full article

The lead-cooled fast reactor (LFR), a Generation IV nuclear system candidate, presents unique neutronic characteristics distinct from pressurized water reactors. Its neutron spectrum spans wider energy ranges with fast neutron dominance, exhibiting resonance phenomena across energy regions. These features require a fine energy group structure for fuel lattice calculations, significantly increasing computational demands. To balance local heterogeneity modeling with computational efficiency, researchers across the world adopt fuel assembly equivalence methods using 1D cylindrical models through volume equivalence principles. This approach enables detailed energy group calculations in simplified geometries, followed by lattice homogenization for few-group parameter generation, effectively reducing whole-core computational loads. However, limitations emerge when handling strongly heterogeneous components like structural/control rods. This study investigates the 1D equivalence method’s accuracy in lead–bismuth fast reactors under various fuel assembly configurations. Through comprehensive analysis of material distributions and their equivalence impacts, the applicability of the one-dimensional equivalence approach to fuel assemblies of different geometries and material types is analyzed in this paper. The research further proposes corrective solutions for low-accuracy scenarios, enhancing computational method reliability. This paper is significant in its optimization of the physical calculation and analysis process of a new type of fast reactor component and has important engineering application value. Full article

Water vapor plays a crucial role in maintaining global energy balance and water cycle, and it is closely linked to various meteorological disasters. Precipitable water vapor (PWV), as an indicator of variations in atmospheric water vapor content, has become a key parameter for meteorological and climate monitoring. However, due to limitations in observation costs and technology, traditional atmospheric monitoring techniques often struggle to accurately capture the distribution and variations in space–time water vapor. With the continuous advancement of Global Navigation Satellite System (GNSS) technology, ground-based GNSS monitoring technology has shown rapid development momentum in the field of meteorology and is considered an emerging monitoring tool with great potential. Hence, based on the GNSS observation data from July 2023, this study retrieves PWV using the Global Pressure and Temperature 3 (GPT3) model and evaluates its application performance in the “7·31” extremely torrential rain event in Beijing in 2023. Research has found the following: (1) Tropospheric parameters, including the PWV, zenith tropospheric delay (ZTD), and zenith wet delay (ZWD), exhibit high consistency and are significantly affected by weather conditions, particularly exhibiting an increasing-then-decreasing trend during rainfall events. (2) Through comparisons with the PWV values through the integration based on fifth-generation European Centre for Medium-Range Weather Forecasts (ERA-5) reanalysis data, it was found that results obtained using the GPT3 model exhibit high accuracy, with GNSS PWV achieving a standard deviation (STD) of 0.795 mm and a root mean square error (RMSE) of 3.886 mm. (3) During the rainfall period, GNSS PWV remains at a high level (>50 mm), and a strong correlation exists between GNSS PWV and peak hourly precipitation. Furthermore, PWV demonstrates the highest relative contribution in predicting extreme precipitation, highlighting its potential value for monitoring and predicting rainfall events. Full article

Complex carbonate reservoirs feature large-scale karst cavern structures, exhibiting complex pore and bottom water energy distributions, which increase the difficulty of reservoir development and require targeted research. This paper proposes a new method for dynamic reserves calculation in these reservoirs based on the Differential Processing Method (DPM) and aimed at optimizing the development of complex reservoirs. The AD22 unit of the Tarim Oilfield in Xinjiang is taken as the research object, and this reservoir features complex karst and fault characteristics, which traditional reserves calculation methods cannot effectively capture due to its complex heterogeneous distribution. This study constructs a refined reservoir numerical model through 3D geological modeling and impedance inversion techniques, calculates dynamic reserves using the DPM, and compares the result with traditional material balance and production data analysis methods. The results indicate that the DPM has an advantage in estimating the petrophysical parameters and reserve utilization in such reservoirs. The error between the constructed reservoir numerical model and the actual reservoir development historical data is only 2.04%, demonstrating a good reference value. The model shows that more than 60% of the recoverable reserves in the target unit are located in areas shallower than 160 m underground, while the current development degree is only 12.6%. The model shows that the recovery rate is low in the strong bottom water energy areas of the unit, while the recovery potential is high in the weak bottom water areas. Therefore, a differentiated development strategy based on varying bottom water energy is required to enhance development efficiency. The model indicates that this strategy can improve the comprehensive development benefits of the reservoir by 81.66% over the existing baseline, demonstrating significant potential. This study provides new ideas and methods for dynamic reserve estimation and development strategy optimization for complex carbonate reservoirs, verifies the effectiveness of the DPM in evaluating the development of complex bottom water energy reservoirs, and offers data references for related research and field applications. Full article

Gonghe Basin is an important frontier of resource and energy development and environmental protection on the Qinghai–Tibetan Plateau and upper sections of the Yellow River. As a characteristic ecotone, this area exhibits complex and diverse ecosystem types while demonstrating marked ecological vulnerability. The response of ecosystem services (ESs) to human activities (HAs) is directly related to the sustainable construction of an ecological civilization highland and the decision-making and implementation of high-quality development. However, this response relationship is unclear in the Gonghe Basin. Based on remote sensing data, land use, meteorological, soil, and digital elevation model data, the current research determined the human activity intensity (HAI) in the Gonghe Basin by reclassifying HAs and modifying the intensity coefficient. Employing the InVEST model and bivariate spatial autocorrelation methods, the spatiotemporal evolution characteristics of HAI and ESs and responses of ESs to HAs in Gonghe Basin from 2000 to 2020 were quantitatively analyzed. The results demonstrate that: From 2000 to 2020, the HAI in the Gonghe Basin mainly reflected low-intensity HA, although the spatial range of HAI continued to expand. Single plantation and town construction activities exhibited high-intensity areas that spread along the northwest-southeast axis; composite activities such as tourism services and energy development showed medium-intensity areas of local growth, while the environmental supervision activity maintained a low-intensity wide-area distribution pattern. Over the past two decades, the four key ESs of water yield, soil conservation, carbon sequestration, and habitat quality exhibited distinct yet interconnected characteristics. From 2000 to 2020, HAs were significantly negatively correlated with ESs in Gonghe Basin. The spatial aggregation of HAs and ESs was mainly low-high and high-low, while the aggregation of HAs and individual services differed. These findings offer valuable insights for balancing and coordinating socio-economic development with resource exploitation in Gonghe Basin. Full article

Jordan is a relatively small country with limited natural resources, but it faces a burgeoning demand for water, energy, and food to accommodate a growing population, refugee migration, and the challenges of climate change that will persist through the rest of this century. Jordan’s Main Water Conveyance System is the backbone of distributing scarce water resources to meet domestic and agricultural demands. Therefore, understanding how the future energy requirements of this system may change is critical for managing the country’s water, energy, and food resources. This paper applied a water balance model to calculate the energy consumption of Jordan’s Main Water Conveyance System between 2015 and 2050, and the results point to high energy requirements for the future of distributing Jordan’s water. In the base year of 2015, the unmet water demand was 134.55 MCM, and the supplied water volume delivered was 438.75 MCM, while the energy consumption was 1496.7 GWh. The energy intensities for water conveyance and water treatment were 7.11 kWh/m³ and 0.5 kWh/m³, respectively. We examined five scenarios of future water and energy demand within Jordan: a reference scenario, a continuation of current behavior, two scenarios incorporating improved water management strategies, and a pessimistic scenario with no interventions. According to all scenarios, the energy consumption is expected to be doubled by the year 2050, reaching approximately 3172 GWh. It is recommended that Jordan prioritizes solar-powered conveyance and pumping to reduce the projected doubling of energy demand by 2050. Across all scenarios, the demand for nonrenewable energy associated with water conveyance is projected to rise significantly, particularly in the absence of renewable integration or efficiency interventions. Total water demand is expected to increase by up to 35% by 2050, with urban and agricultural sectors being the primary contributors. Full article

The following study presents the results obtained from a comparative analysis of dry (powder and hard snow) and wet snow based on satellite data and in situ data methods for monitoring in the high mountain belt of Bulgaria. The aim of the study is to analyze the effectiveness of different spectral indices based on satellite data from Synthetic Aperture Radar (SAR), high-resolution (HR) imagery, and spectrometer data for assessing the state and dynamics of the snow cover. The methods studied and the results obtained were validated by instrument-based field observations, with instruments using thermal imaging cameras, spectrometer measurements, ground control points, and HR imagery. Satellite data offer an ever-widening view of trends in snow distribution over time. All these data combined provide a detailed picture of surface temperature and snow properties, which are crucial for understanding snowmelt processes and the energy balance in the high-altitude belt. The findings suggest that a multi-method approach, utilizing the combined advantages of SAR satellite data, offers the most comprehensive and accurate framework for satellite-based snow cover monitoring in the high mountain regions of Bulgaria, such as Rila Mountain. This integrative strategy not only improves the precision of snow cover estimates but can also support many water resource-related studies, such as snowmelt runoff studies, snow avalanche modeling, and better-informed decisions in the management and maintenance of winter tourism resorts. Full article

Understanding the coupling mechanisms and coordinated development dynamics of the water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on the Yellow River Basin, conducting a comprehensive analysis of the system’s coupling mechanisms and influencing factors. A structured evaluation framework is established, integrating the entropy weight–TOPSIS method, the coupling coordination degree model, and spatial correlation analysis. Empirical analysis is conducted using data from nine provinces (regions) along the Yellow River from 2003 to 2022 to assess the spatiotemporal evolution of the coupling coordination level. The Tobit regression model is employed to quantify the impact of various factors on the system’s coupling coordination degree. Results indicate that the comprehensive evaluation index of the WEF system in the Yellow River Basin exhibits an overall upward trend, with the system coupling degree remaining at a high level for an extended period, up from 0.231 to 0.375. The interdependence among the three major systems is strong (0.881–0.939), and while the coupling coordination degree has increased over time despite fluctuations, a qualitative leap has not yet been achieved. The evaluation index follows a spatial distribution pattern of midstream > downstream > upstream, characterized by a predominantly high coupling degree. However, the coordination degree frequently remains at a forced coordination level or below, with a general trend of midstream > downstream > upstream. From 2003 to 2008, a positive spatial autocorrelation was observed in the coupling and coordinated development of the WEF system across provinces, indicating a strong spatial agglomeration effect. By 2022, most provinces were clustered in “high-high” and “low-low” areas, reflecting a positive spatial correlation with minimal regional differences. Key factors positively influencing coordination include economic development levels, industrial structure upgrading, urbanization, and transportation networks, while technological innovation negatively affects the system’s coordination. Based on these findings, it is recommended to strengthen balanced economic development, optimize the layout of industrial structures, improve the inter-regional resource circulation mechanism, and promote the deep integration of technological innovation and production practices to address the bottlenecks hindering the coordinated development of the water–energy–food system. Policy recommendations are proposed to provide strategic references for the sustainable socioeconomic development of the Yellow River Basin, thereby achieving the high-quality coordinated growth of the water–energy–food system in the region. Full article

Wildfires increasingly threaten forest ecosystems, particularly in arid Mediterranean regions impacted by climate change. This study presents a novel quantitative framework for optimizing silvicultural interventions to reduce combustion energy loads and enhance resource conservation. Using dendrometric equations, biomass removal calculations, and geospatial modeling (Ordinary Kriging, SAGA-GIS and Q-GIS), the methodology evaluates the spatial distribution of calorific energy before and after thinning interventions. The results show that a 20% thinning intervention reduced calorific energy by 13.45% and water demand by 8.38%, while thinning at 30% and 40% intensities achieved even greater reductions. Specifically, thinning reduced the higher calorific potential by 14,000 kJ/m² and saved approximately 861,390 L of water across the study area. These findings provide actionable insights for forest managers to balance ecological health, optimize thinning practices, and mitigate wildfire risks in vulnerable ecosystems. Full article

The reverse addition process in anti-solvent crystallization is safer and more efficient than sieving when dealing with energetic compounds. A new mathematical model has been developed to understand the crystal size mechanism during the reverse addition of solvent in a binary system. This model incorporates droplet dynamics, distribution moments, and mass balance constraints. It can be used to predict the appropriate crystal size for designing explosive recipes with a desired particle size distribution to maximize energy output. The model was validated by conducting reverse-addition crystallization of sodium chloride in a deionized water/ethanol binary system at temperatures ranging from 10 to 50 degrees Celsius. The predicted results closely matched the experimental findings, which were confirmed using a Laser Particle Size Analyzer and Electron Microscope Scanning. Full article

Canopy water interception is a key parameter to study the hydrological cycle, water utilization efficiency, and energy balance in terrestrial ecosystems. Especially in sprinkler-irrigated farmlands, the canopy interception further influences field energy distribution and microclimate, then plant transpiration and photosynthesis, and finally crop yield and water productivity. To reduce the field damage and increase measurement accuracy under traditional canopy water interception measurement, UAVs equipped with multispectral cameras were used to extract in situ crop canopy information. Based on the correlation coefficient (r), vegetative indices that are sensitive to canopy interception were screened out and then used to develop canopy interception models using linear regression (LR), random forest (RF), and back propagation neural network (BPNN) methods, and lastly these models were evaluated by root mean square error (RMSE) and mean relative error (MRE). Results show the canopy water interception is first closely related to relative normalized difference vegetation index (R_△NDVI) with r of 0.76. The first seven indices with r from high to low are R_△NDVI, reflectance values of the blue band (Blue), reflectance values of the near-infrared band (Nir), three-band gradient difference vegetation index (TGDVI), difference vegetation index (DVI), normalized difference red edge index (NDRE), and soil-adjusted vegetation index (SAVI) were chosen to develop canopy interception models. All the developed linear regression models based on three indices (R_△NDVI, Blue, and NDRE), the RF model, and the BPNN model performed well in canopy water interception estimation (r: 0.53–0.76, RMSE: 0.18–0.27 mm, MRE: 21–27%) when the interception is less than 1.4 mm. The three methods underestimate the canopy interception by 18–32% when interception is higher than 1.4 mm, which could be due to the saturation of NDVI when leaf area index is higher than 4.0. Because linear regression is easy to perform, then the linear regression method with NDVI is recommended for canopy interception estimation of sprinkler-irrigated winter wheat. The proposed linear regression method and the R_△NDVI index can further be used to estimate the canopy water interception of other plants as well as forest canopy. Full article

In the past two decades, advancements in thermochemical technologies have improved biomass gasification for distributed power generation, enhancing efficiency, scalability, and emission control. This study aims to optimize syngas production from biomass gasification by comparing two computational models: a quasi-equilibrium thermodynamic model implemented in Aspen Plus and an artificial neural network (ANN) model. Operating at 850 °C with varying steam-to-biomass (S/B) ratios, both models were validated against experimental data. Results show that hydrogen concentration in syngas increased from 19.96% to 43.28% as the S/B ratio rose from 0.25 to 0.5, while carbon monoxide concentration decreased from 24.6% to 19.1%, consistent with the water–gas shift reaction. The ANN model provided rapid predictions, showing a mean absolute error of 3% for hydrogen and 2% for carbon monoxide compared to experimental data, though it lacks thermodynamic constraints. Conversely, the Aspen Plus model ensures mass and energy balance compliance, achieving a cold gas efficiency of 95% at an S/B ratio of 0.5. A Multivariate Statistical Analysis (MVA) further clarified correlations between input and output variables, validating model reliability. This combined modelling approach reduces experimental costs, enhances gasification process control and offers practical insights for improving syngas yield and composition. Full article

The Chinese Loess Plateau (CLP) is ecologically fragile, and water resources are extremely scarce. Soil thermal conductivity (λ) is a vital parameter for controlling surface heat transfer and is the key to studying the energy exchange and water balance of the soil surface. The objective of this study is to investigate the spatial distribution characteristics of soil thermal conductivity on the Loess Plateau. The research primarily employed soil heat transfer models and the Google Earth Engine (GEE) platform for remote sensing cloud computing, compares and analyzed the suitability of six models (Cambell model, Lu Yili model, Nikoosokhan model, LT model, LP1 model, and LP2 model), and utilized the selected improved model (LT model) to analyze the spatiotemporal characteristics of thermal conductivity on the CLP, examining the impacts of soil particle composition, bulk density, elevation, moisture content, and land use on thermal conductivity. The results show that the LT model is the best in the relevant evaluation indices, with a determination coefficient (R²) of 0.84, root mean square error (RMSE) of 0.18, and relative error (RE) of 0.16. Furthermore, the λ on the CLP shows an overall trend of increasing from northwest to southeast, with a lower λ between May and August and a higher one between September and October. The λ of different land use types is as follows: built-up land > cropland > grassland > forest land > barren. The bulk density (ρ_b) and altitude mainly influence λ in the CLP. The results of this study can provide a theoretical basis for studying hydrothermal variation in the CLP, model application, energy development, and land resource use. Full article

During the waterflood development of low-permeability reservoirs, the lithology of barrier and intercalated layers adjacent to the reservoir, with specific permeability and porosity, has a significant impact on water injection efficiency and reservoir energy recovery. However, current research on injection–production parameters and pressure changes in low-permeability reservoirs has not fully considered the effect of these barrier layers. Therefore, this study focuses on the Chaoyanggou Oilfield, a typical low-permeability reservoir, aiming to reveal the influence of water absorption by barrier layers on water injection efficiency and pressure changes in the reservoir. The study systematically analyzes the evolution of the injection–production ratio at different development stages by constructing a comprehensive lithological geological model and applying numerical simulation methods. It explores how the water absorption characteristics of barrier layers affect reservoir pressure and injection efficiency. The results demonstrate that argillaceous siltstone and silty mudstone have significant water absorption effects on injected water, critically influencing pressure distribution and fluid flow dynamics in the reservoir. As the water cut increases, the injection–production ratio gradually stabilizes, and the elastic water storage in the reservoir becomes crucial for establishing an effective oil displacement system. The water absorption of barrier layers accounts for 30% to 40% of the injected water. A high injection–production ratio alone does not lead to rapid energy recovery or increased production. Only by balancing the injection–production ratio, reservoir pressure, and water absorption in barrier layers can the efficiency and recovery rate of waterflood development in low-permeability reservoirs be further improved. Full article