Search Results (939)

In the context of Industry 4.0, digital transformation is reshaping global energy systems. Among the key enabling technologies, Digital Twin (DT)—a dynamic, virtual replica of physical systems—has emerged as a critical tool for improving the performance, reliability, and safety of clean energy infrastructure. In line with the United Nations Sustainable Development Goals (SDGs)—particularly SDG 7 (Affordable and Clean Energy) and SDG 11 (Sustainable Cities and Communities)—the integration of DTs presents unprecedented opportunities to enhance operational efficiency and support proactive decision making. This state-of-the-art review, focused on studies published in 2020–2025, summarizes applications of DTs across the energy value chain, encompassing a broad spectrum of sectors—including solar, wind, hydropower, hydrogen, geothermal, bioenergy, nuclear, and tidal energy—and their critical role in building-to-grid integration. It synthesizes foundational concepts, assesses the evolution of the DT from a predictive tool to a system-level risk-management platform, and provides a critical analysis of its impact. Furthermore, this review discusses the key challenges hindering widespread adoption, including the critical need for interoperability across systems, ensuring the cybersecurity of socio-technical infrastructure, and addressing the complexities of the human-in-the-loop problem. Key research gaps are identified to guide future innovation. Ultimately, this study underscores the transformative potential of DTs as essential tools for accelerating the digital transformation of the energy sector, offering a robust framework for both methodological development and practical deployment. Full article

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short circuits. It is therefore necessary to detect ITSCs at an early stage. In the literature, ITSC detection is often based on current signal processing methods. One of the challenges that these methods face is the presence of imperfections in the stator coils, which also affects the three-phase symmetry. Moreover, when the stator coils are connected in parallel, this type of fault becomes important, as circulating currents will flow between the parallel windings. This, in turn, increases the thermal stress on the insulation and the permanent magnets, while also exacerbating the vibrations of the generator. In this study, a finite-element analysis (FEA) model has been developed to simulate a dual-rotor PMSG under conditions of coil asymmetry. To further investigate the impact of this asymmetry, mathematical modeling has been conducted. For fault detection, negative-sequence current (NSC) analysis and torque monitoring have been used to distinguish coil asymmetry from ITSCs. While both methods demonstrate potential for fault identification, NSC induced small amplitudes and the torque analysis was unable to detect ITSCs under low-severity conditions, thereby underscoring the importance of developing advanced strategies for early-stage ITSC detection. The innovative aspect of this work is that, despite these limitations, the combined use of NSC phase-angle tracking and torque harmonic analysis provides, for the first time in a core-less PMSG with parallel-connected coils, a practical way to distinguish ITSC from coil asymmetry, even though both faults produce almost identical signatures in conventional current-based indices. Full article

The global transition to renewable energy sources is essential to carbon neutrality and ensuring energy security. First, the paper presents a comprehensive literature review of the main technological breakthroughs in bioenergy, hydro energy, solar energy, onshore and offshore wind energy, ocean energy, and geothermal energy, selecting the latest papers published. Next, key scientific challenges, environmental and economic constraints, and future research priorities for each of the six renewable energies were outlined. Then, to emphasize the important contribution of renewable energies to total energy production and the proportions of each type of renewable energy, the evolution of global electricity generation from all six renewable sources between 2000 and 2023 was analyzed. Thus, in 2023, the global electricity generation weight of each renewable energy in total renewable energy ranks hydro energy (47.83%) first, followed by onshore and offshore wind energy (25.8%), solar energy (18.19%), bioenergy (7.07%), geothermal energy (1.1%), and ocean energy (0.01%). After that, the bibliometric analysis, conducted between 1 January 2021 and 1 October 2025 on the Web of Science (WoS) database and using the PRISMA approach and VOSviewer version 1.6.20 software, enabled the identification of the most cited papers, publications and citation number by WoS categories, topics, correlation with Sustainable Development Goals, authors’ affiliation, publication title, and publisher. Furthermore, the paper presents a network visualization of the link between co-occurrences and all keywords, imposing minimum thresholds of 10, 20, and 30 occurrences per keyword, and computes the network density based on the number of edges and nodes. Finally, additional analysis included the most used keywords in different co-occurrences, a word cloud of occurrences by total link strength, regression of occurrences versus total link strength, and correlations between citations and documents and between citations and authors. Carbon neutrality and a resilient energy future can only be achieved by integrating renewable sources into hybrid systems and optimized smart grids. Each technological progress stage will bring new challenges that must be addressed cost-effectively. Full article

Coastal dune systems are dynamic landforms shaped by aeolian processes, in which onshore winds transport and deposit sediments behind natural or artificial barriers. The Çukurova Delta Plain, Turkey’s largest delta along the Eastern Mediterranean, contains extensive dune fields, particularly within the Seyhan and Ceyhan Deltas. Despite technological advances in UAV photogrammetry and Structure-from-Motion (SfM) techniques, studies on coastal dune dynamics in Turkey remain scarce. This study demonstrates the first comprehensive assessment of the spatiotemporal evolution of coastal dunes in the Çukurova Delta Plain. Historical aerial photographs and high-resolution UAV imagery were analyzed to evaluate long-term and seasonal morphological changes. The results indicate notable spatial and temporal variability in sediment budgets, with distinct erosion and accretion patterns across the two deltas. While some dune segments remained stable over decades, others displayed strong seasonal responses to wind and sediment dynamics. These findings enhance the understanding of deltaic coastal geomorphology and provide critical insights for sustainable management of vulnerable dune ecosystems under increasing human and climatic pressures. Full article

The current research indicates that the Ecological Spatial Network (ESN) supports critical regulating services, yet the quantitative coupling between its topological structure and the sand fixation function has received limited attention. This study investigates this relationship in the Zhangbei region, China, from 2002 to 2022. By integrating the Minimum Cumulative Resistance (MCR) model, complex network theory, and the Revised Wind Erosion Equation (RWEQ), we systematically evaluated the network’s structural evolution and its correlation with the sand fixation capacity. The results reveal a significant enhancement in ecosystem service: the actual wind erosion amount decreased from 20.18 t/ha in 2002 to 2.83 t/ha in 2022, while the network structure matured, characterized by stable high modularity (Q ≈ 0.67) and a marked “core densification” trend. Correlation and regression analyses confirm that topological metrics—specifically PageRank, Betweenness Centrality, and Degree—are effective indicators, jointly explaining 48–65% of the spatial variation in the sand fixation capacity. Notably, PageRank emerged as the most robust predictor, highlighting the functional importance of high-quality patch clusters. Furthermore, optimization simulations suggest that a low-eigenvector centrality edge-adding strategy is most effective for enhancing network connectivity. These findings provide a theoretical basis and spatial guidance for ecological restoration in arid and semi-arid regions. Full article

Scientific planning and optimal development of multi-type power sources are critical prerequisites for supporting the robust evolution of emerging power systems. However, existing techno-economic evaluation methods often face challenges such as higher-order uncertainty and weight conflicts, making it difficult to provide reliable support for comparing and selecting power source schemes. To address this, this paper proposes an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method based on Fermatean Fuzzy Sets (FFS) for techno-economic evaluation of multi-type power sources. First, building on the traditional TOPSIS framework, we introduce Fermatean Fuzzy Sets to construct a FF Hybrid Weighted Distance (FFHWD) measure. This measure simultaneously captures the subjective importance of evaluation indicators and decision-makers’ risk preferences. Second, we design a subjective-objective coupled weighting strategy integrating Fuzzy Analytic Hierarchy Process (FAHP) and Entropy Weight Method (EWM) to achieve dynamic weight balancing, effectively mitigating biases caused by single weighting approaches. Finally, the FFHWD is integrated into the improved TOPSIS framework by defining FF positive and negative ideal solutions. The comprehensive closeness coefficients of each power source scheme are calculated to enable robust ranking and optimal selection of multi-type power source alternatives. Empirical analysis of five representative power generation technologies—thermal power, hydropower, wind power, photovoltaics (PV), and energy storage—demonstrates the following comprehensive techno-economic ranking: hydropower > photovoltaics > thermal power > wind power > energy storage. Hydropower achieves the highest closeness coefficient (−0.4198), whereas energy storage yields the lowest value (−2.8704), effectively illustrating their respective advantages and limitations within the evaluation framework. This research provides scientific decision-making support and methodological references for optimizing multi-type power source configurations and planning new power systems. Full article

This paper presents a novel system dynamics-based framework for forecasting market share evolution in the telecommunications sector. The framework conceptualizes market share as flows of subscribers—driven by churn, attraction, and market growth—between interconnected compartments representing providers. It is designed to operate with limited available market data and incorporates stochastic processes to capture market uncertainty, enabling risk-informed forecasts. The framework is applied to the Greek mobile telecommunications market using historical data (2006–2022), with a 5-year hold-back period for validation. Results highlight the dominant role of churn management in market share variability, particularly for the incumbent provider Cosmote, while subscriber attraction parameters show moderate influence for alternative providers Vodafone and Wind Hellas. Sensitivity analysis confirms the model’s robustness and identifies key drivers of forecast variability. The proposed framework provides actionable insights for strategic decision-making, making it a valuable tool for providers and policymakers to address churn, optimize attraction strategies, and ensure long-term competitiveness in dynamic markets. Full article

Energy storage is vital for on-demand electricity generation from renewable sources like wind and solar. Besides employing batteries, retrofitting conventional fossil-fired power plants with thermal energy storage might present a highly cost-effective solution. State-of-the-art molten salt storage systems currently operate at a maximum temperature of 565 °C. At a higher permanent temperature, nitrate salts start to decompose. The actual wall temperatures of power components for heating, such as solar receivers and electrical heaters, may exceed temperature limits. To date, there is no clear threshold identified up to which heating surfaces in contact with nitrate salt can be operated without leading to the degradation of the salt, which is inevitably followed by increased corrosivity. In this study, possible mechanisms affecting the maximum permissible wall temperature of heating surfaces are identified. The local production of oxygen and nitrite at hot surfaces and its accumulation in the entire system is looked at in an experiment with 9.3 kg of nitrate salt. The effect of high wall temperatures on the evolution of oxygen and nitrite content over time is monitored and analyzed. Parametric studies with an experimentally validated physical model focusing on the nitrate/nitrite equilibrium reveal major influencing factors, with wall temperatures significantly exceeding current design limits. These findings potentially allow for more compact and cost-effective heating components. This work supports the advancement of high-temperature thermal energy storage systems essential for the scalability and economic competitiveness of renewable energy infrastructure. Full article

The safe operation of hydrogen transmission pipeline stations is paramount for the widespread adoption of hydrogen energy. This study addresses the significant hazard of hydrogen leakage in high-pressure pipeline stations by employing numerical simulations to investigate the dispersion behavior under various conditions. It specifically focuses on the complex interplay between meteorological factors, operational parameters, and station layout. A key finding is that the structural configuration of obstacles—namely their height and distance from the leakage source—serves as the dominant mechanism controlling the evolution of the hazard radius, overshadowing the influence of traditional parameters like wind speed and leak diameter in obstructed environments. Based on this insight, a novel and robust predictive model for the dynamic hazard radius was developed using multiple regression analysis. The model accurately quantifies the impact of leakage duration, obstacle spacing, and obstacle height, achieving an excellent fit (R² = 0.9848) with a prediction error of less than 5% compared to simulation data. This study provides valuable insights for defining risk zones and supports the development of effective safety measures and emergency response strategies for hydrogen infrastructure, thereby contributing to the secure and sustainable deployment of hydrogen energy. Full article

On the morning of 4 April 2025, a rare formation of Cirrostratus undulatus homomutatus was observed over Barcelona. This variety of the homomutatus form of the Cirrostratus cloud genus—originating from the transformation of persistent aircraft contrails—has not previously been documented in the International Cloud Atlas or in any scientific publication, making this observation unique within the current literature. The event was visually recorded and meteorologically analyzed using upper-air data from the Barcelona radiosonde and the ECMWF ERA5 reanalysis at 300 and 500 hPa geopotential heights. Synoptic and thermodynamic analyses revealed a localized region of enhanced wind shear activity coinciding with a thin, moist layer near the tropopause. These conditions likely facilitated the transformation of persistent contrails into cirriform layers exhibiting undulated patterns characteristic of the undulatus variety. This case provides new insight into the microphysical and dynamic mechanisms underlying the evolution of anthropogenic cirriform clouds, contributing to the growing body of knowledge on homomutatus phenomena and their interaction with upper-tropospheric processes. It thus represents the first formal documentation and meteorological interpretation of Cirrostratus undulatus homomutatus, offering a valuable reference for future observational and classification efforts within the WMO framework. Full article

Dunes are key geomorphological features controlling airflow and sediment transport. While these processes are well documented under onshore conditions, this study provides the first high-resolution spatial analysis of dune-beach dynamics under offshore winds, integrating wind flow, sediment transport, and topographic data. The investigated site is a low-elevation (<1 m) dune typical of Mediterranean coasts, characterized by a mixed sand–gravel patch and a distinct beach slope break. Results show that dune height strongly controls the magnitude of airflow adjustment. Directional deflections and accelerations remain limited (<15° and <40%, respectively), and the sheltered zone extends only to the downwind dune toe. During strong wind events (gusts > 50%), sediment transport initiates immediately beyond the crest, feeding offshore-directed fluxes. Under weaker winds (gusts < 20%), enhanced surface roughness from the mixed sand–gravel patch and flow stagnation at the slope break shift the active transport zone toward the lower beach, where the most pronounced morphological changes occur. These findings demonstrate that small dunes provide limited aerodynamic shelter and fail to prevent sediment export under offshore winds. They highlight the need to incorporate additional factors (e.g., microtopography, surface properties) when assessing sediment budgets and the long-term evolution of low-relief coastal systems. Full article

The semi-annual oscillation (SAO) dominates seasonal variability in the equatorial stratosphere and mesosphere. However, the seasonally dependent modulation of the SAO in the stratosphere (SSAO) and mesosphere (MSAO) by sudden stratospheric warmings (SSWs) in the Arctic has not been investigated in detail. In this study, we examine the seasonal evolution of the SAO during 16 major SSW events spanning 2004 to 2024 using the Japanese Atmospheric General Circulation Model for Upper Atmosphere Research Data Assimilation System Whole Neutral Atmosphere Re-analysis (JAWARA). Basic features of the SAO are well captured by JAWARA, as evidenced by the SSAO and MSAO appearing at around 50 km and 85 km, respectively. The different responses of the SAO to early and late winter SSWs are particularly strong during the Northern Hemisphere winter of 2023/24. Early winter SSWs tend to significantly intensify the westward SSAO, while late winter SSWs tend to weaken the eastward SSAO. Similarly, the eastward MSAO is amplified during early winter SSWs, whereas the westward MSAO is slightly weakened during late winter SSWs. The weak MSAO response is probably due to its smaller climatological magnitude. Modulation of the SAO by SSWs is related to meridional temperature changes during SSWs through the thermal wind balance. Our findings contribute to the understanding of coupling between the tropics and high latitudes, as well as interhemispheric coupling. Full article

Driven by the intensification of climate change, extreme snow events are becoming more frequent, posing significant risks to the safety of arched-roof structures. The combination of strong winds and heavy snowfall will cause localized snowdrifts that may exceed the safety design values in load codes. Such localized snowdrift phenomena even get worse under the action of mutual interference between buildings. To address this critical safety concern, this study employed a multiphase numerical model to evaluate interference effects on snow accumulation characteristics for grouped arched-roof buildings. Initially, the predictive accuracy of the numerical method was confirmed by comparing the results of a wind tunnel test. On the basis of full validation, a comprehensive numerical investigation was conducted to examine the snow redistribution patterns and aerodynamic interference effects among multiple arch-roofed buildings. Through analysis, the interference effect manifests as additional U-shaped snow accumulation on the windward surface of the disturbed arched roof, and specifically exhibits three distinct evolution stages of snow accumulation in relation to building spacing. Under adverse conditions, the disturbed snow load could increase by up to 1.4~1.5 times the fully exposed load, exceeding values specified in most design codes. Therefore, an amplification factor of 1.4 is recommended for the code-calculated fully exposed snow load to appropriately account for building interference effects. Full article

Wind shear-induced aviation turbulence (WSAT) remains a major safety concern during approach and takeoff phases at complex terrain airports. This study develops an interpretable Explainable Boosting Machine (EBM) framework to classify WSAT events at Hong Kong International Airport (HKIA). The framework integrates Differential Evolution with HyperBand (DEHB) for hyperparameter tuning and applies multiple data balance methods such as SMOTE, Borderline SMOTE, Safe-Level SMOTE, and G-SMOTE. The dataset consists of Pilot Reports (PIREPs) collected between 1 January 2007 and 31 July 2023, with 6838 wind shear events that include variables that relate to wind shear magnitude, altitude, runway distance, rainfall condition, and causal factors. Among all configurations, the EBM tuned via DEHB and trained with SMOTE-treated data achieved the highest predictive performance with BA = 0.710, MCC = 0.321, and G-Mean = 0.708, higher than untreated and other balance variants. EBM-based interpretation showed that wind shear altitude and wind shear magnitude were key predictors, and their interaction reflected a nonlinear pattern where WSAT probability rose under moderate-to-high shear conditions (wind shear altitude ≈ 0.5–2.5 and magnitude ≈ 30–35 knots). The DEHB-optimized EBM–SMOTE framework provides a transparent interpretive foundation for WSAT risk assessment and advances quantitative evaluation in aviation meteorology. Full article

Predicting wildland fire spread requires numerical schemes that can resolve sharp gradients at the fireline while remaining stable and efficient on practical grids. We develop a compact high-order finite-difference scheme for Hamilton–Jacobi level-set formulations of wildfire propagation, based on the anisotropic spread law of Mallet and co-authors. The spatial discretization employs a compact finite-difference derivative scheme to achieve spectral-like resolution with narrow stencils, improving accuracy and boundary robustness compared with wide-stencil ENO/WENO reconstructions. To control high-frequency artifacts intrinsic to non-dissipative compact schemes, an implicit high-order low-pass filter is incorporated and activated after each Runge–Kutta stage. Convergence is verified on the eikonal expanding-circle benchmark, where the method attains the expected high-order spatial accuracy as the grid is refined. The proposed scheme is then applied to wind-driven wildfire simulations governed by Mallet’s non-convex Hamiltonian, including a single ignition under moderate and strong wind. A complex topology test case is also considered, involving two ignitions that merge into a single front with the evolution of an internal unburnt island. The results demonstrate that the proposed method accurately reproduces fireline evolution even on coarse grids, achieving accuracy comparable to fifth-order WENO while maintaining superior fidelity in complex fireline topologies, where it better resolves multi-front interactions and topological changes in the fireline. This makes the method an efficient, accurate alternative for level-set wildfire modeling and readily integrable into existing frameworks. Full article