Energy Science & Engineering最新文献

Mountain climbing often involves sudden weather changes, group separation, and mobile device battery depletion, which can lead to life-threatening emergencies. Enhancing survival and extending rescue time in such situations are crucial, making power supply and emergency equipment essential considerations. Existing equipment designs have emphasized solar power, lighting, communication, or navigation, but few address an integrated solution that simultaneously addresses survival needs such as warmth, power supply, and location tracking. To overcome these limitations, this study presents the design of an emergency rescue backpack, which serves as a self-rescue and assisted-rescue tool for climbers stranded in mountainous terrain. The backpack is equipped with light emitting diode (LED) light strips, a heating module, a global positioning system (GPS) tracking system, and a flexible solar photovoltaic panel integrated with a portable power bank. A key innovation of this study lies in the integration of the heating module, which utilizes a carbon fiber heating element sewn into the back of the backpack. By hugging the backpack, climbers can generate and retain heat to help maintain body temperature in cold environments, thereby reducing the risk of hypothermia. Additionally, the LED lighting provides illumination for nighttime navigation and deters wildlife. The GPS enables rescuers to track the stranded individual's location via satellite positioning. The flexible solar panel converts sunlight into electrical energy, which is stored in the internal power bank. Moreover, a switch-controlled USB hub with four ports is installed to minimize power consumption when not in use. Therefore, the practical contribution of the overall design is to extend rescue time and enhance the survival chances of lost hikers.

This article provides a methodological guide for applying SWOT analysis to Turkiye's solar photovoltaic (PV) market and shows how local developers can translate sector‑level insights into firm‑level strategies. The study clarifies scope: it does not report an empirical SWOT; instead, it offers an illustrative matrix (Table 3) and a three‑step pathway—mapping, strategic priorities, and actionable recommendations—operationalized in Table 4. Drawing on policy documents, market reports, and academic literature, guidance is outlined on how factors such as regulatory design, financing access, regional solar resource variation, and technology trends (e.g., storage and smart grids) should be incorporated into a structured SWOT. The approach is positioned alongside complementary methods, and the regional solar equity model (RSEM) is briefly introduced as a conceptual tool for region‑sensitive policy design. Limitations are noted: the guide synthesizes secondary sources without primary data collection; empirical validation, prioritization (e.g., via MCDM), and RSEM calibration are proposed for future work. The guide aims to support researchers and practitioners designing market entry and growth strategies consistent with national energy objectives.

This study explores the effects of surface wettability and particle size distribution on the stability of petroleum coke–water slurry (PCWS). Significant differences in stability were observed among slurries prepared from four types of petroleum coke. Notably, reduced surface wettability was found to enhance slurry stability. The average particle size of all petroleum coke powders was consistently maintained at 23 ± 5 μm, with their size distributions well fitted by the Rosin–Rammler equation. The model parameter n, ranging from 0.60 to 0.84, indicates a relatively uniform particle size distribution, suggesting improved packing efficiency within the slurry. As a result, PCWSs with particle size distributions falling within this optimal range exhibited markedly higher stability than those outside it. The novelty of this study lies in the combined quantitative investigation of two fundamental physicochemical factors—surface wettability (via contact angle) and particle size distribution (via Rosin–Rammler model parameters)—and their synergistic influence on the static stability of PCWS.

In the process of fracturing, proppant flowback is unavoidable, and excessive proppant flowback will cause sand plugging in the wellbore, change the morphology of proppant fractures, reduce the effective flow-conducting capacity of fractures, weaken the effect of fracturing to increase production, and affect the extraction of hydrocarbons in the later stage of the fracturing process. At present, the research on proppant flowback during fracturing and re-discharge process mainly focuses on the force of proppant and its critical flowback rate at the time of startup, and there are fewer studies on the factors affecting proppant flowback, and there is not yet a theoretical model to specifically analyze the flowback characteristics of proppant in a rough fracture. Combining the above reasons, this paper constructs a three-dimensional numerical simulation model of proppant flowback in rough fracture by using the coupled computational fluid dynamics-discrete element method to study the factors affecting proppant flowback in rough fracture, and it is found that the rough fracture can reduce the flowback of proppant by comparing the flowback of proppant in the smooth fracture and the rough fracture. Meanwhile, it is clearly understood that the flow rate of return fluid and proppant particle size are the main influencing factors affecting proppant flowback. This study can provide theoretical references for the program design and field construction of the actual fracturing return phase.

To address the problem of the chaos phenomenon caused by the parameter drift of a doubly-fed induction generator (DFIG) due to a changing operating environment, a fractional-order stator voltage/flux-oriented control model is developed, and bifurcation theory and numerical simulations reveal that the chaos mechanism originates from supercritical pitchfork bifurcation. First, the fractional-order DFIG model is constructed by introducing Caputo fractional-order derivatives and combining linear affine transformation and time-scale transformation. Second, we analyze the bifurcation characteristics of the system's equilibrium point under diverse axial rotor voltages. Third, we apply the central manifold theorem to reduce the system dimensions to derive an equivalent downscaling model and describe the bifurcation behavior near the equilibrium point. Finally, the dynamics of the DFIG system at different fractional orders are explored by employing different numerical simulation methods for the changes in the rotor d-axis voltage component and the wind turbine output torque. The analytical results indicate that the DFIG system plunges into chaos via supercritical pitchfork bifurcation. As the fractional order diminishes, the system transitions from chaotic conditions to stable conditions. Transient chaos can occur in the DFIG system under particular combinations of fractional orders and parameters.

The integration of hydrogen into existing natural gas networks represents a transformative approach to enhancing the utilization of renewable energy sources. This study focuses on the reliability of systems designed for hydrogen injection into the natural gas grid. We develop a representative system configuration and compile failure/repair data for all major components, then perform a component-level failure mode and effect analysis (FMEA) with exponential-rate assumptions to quantify subsystem and plant reliability. In the baseline (no redundancy), the overall mean time to failure (MTTF) is 186 h. Selective parallelization of pumps and compressors in Subsystems 2–5 (three units in parallel each) increases the plant-level MTTF to ~226 h (+21%), while additional parallel units show diminishing—and eventually negative—returns due to extra failure paths (valves, piping). A severity-probability (S–P) matrix pinpoints pumps and compressors as the dominant contributors to risk; control valves exhibit high impact but are not good candidates for redundancy, and the fresh water pump shows no benefit from duplication. These results provide practical guidance on where redundancy is worth the complexity and cost, and they outline priorities for future validation with hydrogen-specific field data.

To analyze the oil cavity lubrication characteristics of wind turbines sliding bearings with discontinuous flow in mixed lubrication wear caused by strong sudden changes and heavy loads, this paper aims to improve a method to analyze the pressure and temperature of different oil cavity shapes with different condition to enhance the lubrication reliability. This proposed method combining CFD simulation based on the Finite Volume Method with RNG k–ε model is demonstrated to analyze effectively the oil cavity lubrication characteristics with mixed lubrication wear. The different oil cavity shapes—circular cavity, sector cavity, and cross-shaped cavity, and different conditions including eccentricity, input pressure, temperature-viscosity, and surface roughness were analyzed to explore the effects on the maximum pressure, bearing capacity, and temperature. The study accurately evaluates the load-bearing support performance, temperature rise characteristics with different cavity shapes and different conditions. The results provide valuable references for optimizing lubrication reliability for wind power sliding bearing.

The phenomenon of annular pressure buildup (APB) is commonly observed in offshore gas wells, characterized by complex and coupled pressure types across multiple annuli. Field operations, including well shutdowns, pressure relief, and well interventions, further complicate the pressure dynamics, rendering traditional theoretical models incapable of accurately predicting annular pressure under the influence of these coupled conditions. Elevated annular pressure can lead to casing deformation and failure, posing significant risks to well integrity and production safety. This study addresses the challenge of predicting annular pressure under the coupling of multiple APB types by utilizing real-time monitoring data reflecting the annular pressure state of production wells and incorporating the influence of field operations. A convolutional neural network (CNN) is employed to optimize feature extraction, and a bidirectional long short-term memory (Bi-LSTM) network is established based on the optimized CNN kernels to predict annular pressure under complex coupling conditions. A dynamic management chart for APB is developed by incorporating the dynamic variation of wellbore pressure. The results demonstrate that the prediction accuracy of the CNN-optimized Bi-LSTM model exceeds that of the standalone LSTM model, with a mean error of 4.03% when compared with field-measured data. The inclusion of operational characteristic parameters enables the extraction of features related to human intervention, further improving the model's accuracy and reducing the mean error to 2.55%. The dynamic management chart, which incorporates the variation in wellbore pressure, provides effective guidance for field safety operations.

This study investigates the impact of uncertainty in building operation patterns on the design and techno-economic performance of solar photovoltaic (PV) systems in a commercial building in a hot arid region in Abu Dhabi, UAE. Utilizing the Design-Builder software, a model of a commercial hotel building was developed and calibrated to assess its energy demand. Three distinct operational scenarios—Austere, Baseline, and Wasteful—were analyzed in this study, each considering both grid-connected PV systems with and without energy storage solutions. The study employed sensitivity analyses to understand how variations in modeling inputs affect the levelized cost of energy (LCOE) and the levelized cost of storage (LCOS). The findings reveal significant variations in LCOE and LCOS across different scenarios, in which the minimum (LCOE) can be achieved at $0.165/kWh for the Baseline Case, $0.191/kWh for the Austere Case, and $0.162/kWh for the Wasteful Case, while the minimum (LCOS) can reach $0.30/kWh for Baseline case, $0.55/kWh for Austere case, and $0.19/kWh for Wasteful Case, underscoring the necessity of tailored PV system designs to optimize performance and economic feasibility. This study contributes to the growing body of knowledge of sustainable building energy solutions, highlighting the importance of incorporating operational uncertainties into the planning and design of renewable energy systems.

This study investigates the application of photovoltaic (PV) systems in 30-meter high-rise residential buildings in Tehran, evaluating the impact of four geographical orientations (north, south, east, and west). Using PV*SOL software, system energy production and performance were simulated based on Tehran's specific climatic conditions and solar radiation data. The primary goal is to assess the influence of panel orientation on energy efficiency, cost-effectiveness, and environmental benefits. Results show that south-facing systems, receiving 2151.86 kWh/m² of global radiation, achieved the highest energy yield of 57,937 kWh annually, with a 6.9-year payback period. In contrast, north-facing systems generated only 36,328 kWh/year and required 11.1 years for cost recovery. South-oriented systems also achieved the greatest environmental benefit, reducing CO₂ emissions by 27,196 kg per year. The economic analysis demonstrates that optimized orientation significantly improves long-term financial viability. This study highlights the strategic importance of rooftop PV deployment in high-rise buildings to enhance energy efficiency and reduce urban energy consumption. The findings also provide a valuable reference for urban renewable energy planning in cities with similar climate conditions. Future research should include the integration of energy storage systems and assess long-term dust accumulation impacts on PV system performance in dense urban settings.