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Energy storage plays a key role in the energy transition by enabling the effective integration of variable renewable energy sources such as solar and wind power and by supporting the stability and flexibility of modern energy systems. The rapid development of energy storage technologies has become one of the pillars of sustainable energy management; however, it simultaneously raises environmental, material, and systemic challenges. This review analyses the environmental implications of energy storage development using an integrative perspective that combines technological, environmental, and system-level analysis. The paper examines major classes of energy storage technologies, including electrochemical, mechanical and physical, thermal energy storage, and chemical pathways within Power-to-X, with particular emphasis on their technical characteristics, maturity, and life cycle environmental performance. Lithium-ion battery systems typically achieve round-trip efficiencies of 85–92% and cycle lifetimes exceeding 5000 cycles, while flow batteries may exceed 10,000 cycles under stationary operating conditions. Mechanical storage technologies such as pumped hydro provide efficiencies of approximately 70–85% with operational lifetimes exceeding several decades. Key challenges related to critical raw material availability, recycling, end-of-life management, and ecosystem impacts are discussed, highlighting the importance of sustainable production and recovery strategies in supporting the circular economy. In addition, the review addresses the consequences of insufficient reuse of secondary materials and the growing relevance of digitisation and cyber resilience of energy storage systems as indirect contributors to environmental risk. The review also considers geopolitical aspects related to critical material supply chains and the cyber security of energy storage infrastructure, emphasising their growing importance for the resilience and environmental sustainability of future energy systems. The analysis indicates that further development of energy storage technologies will significantly influence not only power systems but also transport, industry, and heat sectors. The results emphasise that sustainable deployment of energy storage requires hybrid system architectures and policy frameworks that account for environmental performance, system flexibility, and long-term resilience in line with the principles of sustainable development. Full article

Accurate freeway Improvements in traffic state prediction accuracy and enhanced stability enable more proactive traffic control and demand management strategies, thereby reducing congestion spillover effects, unnecessary acceleration–deceleration cycles, and the resulting fuel consumption and emissions. Yet, this remains challenging due to the interplay between deterministic traffic flow mechanisms and stochastic disturbances. Purely data-driven models suffer from error accumulation under out-of-distribution conditions, while physics-based models lack flexibility in capturing nonlinear deviations. This paper proposes MDURP, a physics-constrained residual learning framework that reformulates prediction as a residual-space learning problem. A calibrated Cell Transmission Model generates a physically admissible baseline; deep learning models are then restricted to learning the residuals. Wavelet decomposition and GARCH volatility modeling address the multi-scale and heteroskedastic characteristics of these residuals. Experimental results demonstrate that MDURP consistently outperforms baseline models, reducing MAE by an average of 6.8%, RMSE by an average of 4%. The framework also suppresses long-term error accumulation, with MAPE escalation slowing from 0.79% to 0.58% per step. These gains confirm that anchoring deep learning within a physics-defined residual space enhances both accuracy and stability. Full article

To address the issues of safety risk analysis and conflict assessment for integrated flight of manned aircraft and fixed-wing unmanned aerial vehicles (UAVs) in low-altitude mixed-operation airspace, this study enhances the foundational Event model. By incorporating UAV characteristics such as geometric features and aerodynamic mechanisms, alongside design dimensions and onboard performance metrics, an improved collision risk model is developed—the Enhanced Event-Based Framework for Multidimensional Geometry and Quasi-Monte Carlo Analysis of Flight Performance (EMGF-M). This enhancement rectifies the limitations of the basic model regarding parameter coverage and scenario adaptability, thereby improving the reliability and validity of the computational results. Experimental results demonstrate that, in accordance with the target safety level for airspace conflicts set by the International Civil Aviation Organization (ICAO), the application of the improved Event collision model yields quantifiable assessments of safety risks and safe separation distances for integrated operations in low-altitude mixed-use airspace. Utilizing these computational results for integrated flight procedure design at a general airport in Southwest China, the study shows that the air traffic flow in the low-altitude mixed-operation airspace increased from 9.2 to 20.9 operations per hour. The practical significance of this method lies in its guidance for accurately assessing safety risks in mixed airspace operations and for determining quantifiable separation minima for integrated flight trajectory planning. Full article

Supercritical heat transfer in regenerative cooling channels is strongly influenced by thermophysical property variations near the pseudo-critical temperature, yet their direct implications for cooling performance have not been fully addressed. This study investigates how incorporating supercritical property considerations into surrogate fuel formulation affects heat transfer behavior in a regenerative cooling channel. RP-3 surrogate fuels were constructed using a genetic algorithm by matching both temperature-independent properties and temperature-dependent properties under supercritical conditions. Unlike previous approaches employing distillation curves as a secondary objective, the present formulation adopted supercritical density distribution and pseudo-critical temperature (T_pc) as optimization targets. The formulated surrogate fuels were evaluated in a regenerative cooling channel model surrounding a combustor, and their flow and heat transfer characteristics were compared with those of literature-based surrogate fuels. The results show that differences in T_pc and density variation trends significantly influence buoyancy-induced asymmetric flow structures and the onset of heat transfer deterioration. Surrogate fuels with lower T_pc exhibit earlier density reduction and earlier development of asymmetric flow, whereas fuels with higher T_pc demonstrate relatively mitigated wall temperature rise. The results of the present study suggest that surrogate fuel formulation based on supercritical thermophysical properties can have a significant influence on the predicted heat transfer behavior in regenerative cooling channels under the operating conditions considered. Full article

As a world-renowned tourist and gaming city, Macau’s jewelry industry has formed significant spatial clustering driven by the integration of the tourism and gaming industries. However, existing research has not thoroughly explored the coupling mechanism between the agglomeration of this high-value industry and tourism potential circulation characteristics. Meanwhile, the industry confronts practical challenges, including an unbalanced layout between high-end and local brands, intense competition in core areas, and distinct service coverage blind spots in non-core areas. To fill these research gaps, this study takes the Macau Special Administrative Region as the research scope, integrates POI kernel density estimation, Voronoi diagram analysis, and space syntax to construct a three-dimensional analytical framework encompassing agglomeration intensity, service scope, and tourism flow matching, and systematically investigates the spatial clustering pattern of jewelry stores and its coupling mechanism with tourism potential circulation. The study reveals the following findings: (1) Jewelry stores exhibit a dual-segment, four-core clustering pattern. Among these, 38 high-end brands are concentrated in casino complexes and their surrounding areas, 34 comprehensive brands are evenly distributed across core and residential areas, and 300 local brands are mainly scattered in residential areas of the Macau Peninsula. (2) The service scope of jewelry stores is negatively correlated with agglomeration density. The Voronoi diagram area in core areas is 62% smaller than that in non-core areas, accompanied by a high degree of overlap—35% for high-end brands—and intense competition. In contrast, non-core areas have coverage blind spots accounting for 18% of Macau’s total land area. (3) Under a 300 m walking radius, high-integration paths identified by space syntax demonstrate an 85% matching degree with tourist routes, and the four core areas form differentiated coupling types. This study is the first to quantify the differentiated coupling mechanism between multi-level jewelry brands and tourism potential circulation. It further improves the GIS analysis framework for the coupling between commercial agglomeration and tourist behavior. The revealed negative correlation between service scope and agglomeration density, and the adaptive principle between brand spatial layout and regional functional attributes, provide universal references for similar business formats in tourist cities, including cultural and creative retail and characteristic catering. In practice, this research optimizes the spatial layout of Macau’s jewelry industry and increases the coverage rate of service blind spots to over 85%. It also provides scientific support for tourism route planning and the coordinated development of tourism and commerce in high-density tourist destinations. Full article

Long-distance coal gangue slurry transportation pipelines are critical components of underground coal mine green backfilling systems, yet blockage failures severely threaten their safe and efficient operation. Existing distributed acoustic sensing (DAS)-based monitoring methods for such pipelines suffer from three key limitations: insufficient fixed-point quantitative accuracy, lack of verified blockage-specific characteristic indicators, and limited quantitative severity assessment capability. To address these gaps, this paper proposes a novel feature-level fusion monitoring method integrating DAS, fiber Bragg grating (FBG), and piezoelectric accelerometers for accurate blockage identification and quantitative evaluation in coal gangue slurry pipelines. A slurry pipeline circulation test platform with gradient blockage simulation (0% to 76.42%) and a synchronous multi-sensor monitoring system were developed. Through multi-domain signal analysis, three blockage-correlated characteristic frequencies were identified and cross-validated by synchronous multi-sensor data: 1.5 Hz (system background vibration), 26 Hz (blockage-induced fluid–structure resonance, verified by the Euler–Bernoulli beam theory with a theoretical value of 25.7 Hz), and 174 Hz (transient flow impact). The DAS phase change rate exhibited a unimodal nonlinear response to blockage degree, with the peak occurring at 40.94% blockage. On this basis, a sine-fitting quantitative inversion model was developed, achieving a high goodness of fit (R² = 0.985), and leave-one-out cross-validation confirmed its excellent robustness with a mean relative prediction error of 3.77%. Finally, a collaborative monitoring framework was built to fully leverage the complementary advantages of each sensor, realizing full-process blockage monitoring covering global blockage localization, precise quantitative severity calibration, and high-frequency transient risk early warning. The proposed method provides a robust experimental and technical foundation for real-time early warning, precise localization, and quantitative diagnosis of long-distance slurry pipeline blockages and holds important engineering application value for the safe and efficient operation of underground coal mine green backfilling systems. Full article

Fluid mechanics in disordered structures gives rise to rich multiscale dynamics through the interplay of topology, symmetry breaking, and fluid–structure interactions. Heterogeneous networks encode mechanical responses, regulate flow organization, and shape energy dissipation, enabling memory effects and emergent collective behaviors across both natural and engineered systems. These principles operate across vast scales: from seamounts with characteristic scales of $L\approx {10}^3\mathrm{m}$ and Froude numbers $Fr\approx {10}^{-2}–{10}^{-1}$ generating deep-ocean turbulent mixing, to marine tidal turbines operating at Reynolds numbers $Re\approx {10}^7–{10}^8$ and Euler numbers $Eu\approx {10}^{-1}–{10}^0$, where inertial forces dominate flow dynamics. Although the dominant physical forces may vary across scales—for example, planetary rotation and stratification in large-scale oceanic flows versus viscous or interfacial effects in microscale systems—the comparison of dimensionless parameters provides a useful framework for discussing similarities in flow organization and scaling behavior. Empirical observations, network-based descriptions, and multiscale simulations collectively demonstrate how topological features constrain symmetry, organize transport pathways, and support predictive reconstruction and inverse design. These principles underpin applications ranging from engineered systems that exploit broken symmetries to rectify chaotic transport, to biological architectures where flows mediate information transfer, locomotion, and structural self-organization. In this Review, we synthesize recent advances to propose a unifying physical paradigm: fluid flows actively interact with disorder, reorganize dissipation, and convert structural asymmetry into functional mechanical performance across scales. Full article

Metal hydrides store hydrogen in the solid state with high density and inherent safety, and their thermodynamic characteristics are typically described by the pressure–composition–isotherm (PCI) curve. In the plateau pressure region of the PCI curve, the equilibrium pressure remains nearly constant over a wide hydrogen concentration range, making conventional pressure-based methods unsuitable for quantifying the hydrogen amount in metal hydride vessels. This study proposes a strain-based method to quantify the hydrogen amount in a metal hydride vessel by measuring the strain induced on the metal hydride vessel surface due to the volumetric change of the metal hydride during hydrogen adsorption and desorption. The installation of strain gauges on the metal hydride vessel was verified using argon pressurization tests. The metal hydride was activated prior to controlled hydrogen desorption experiments aimed at quantifying the amount of hydrogen remaining in the vessel. A correlation between strain and hydrogen amount was obtained from experiments conducted at discrete measurement points. The hydrogen amount estimated using the strain-based method was further evaluated through continuous time-series desorption tests and showed good agreement with the results obtained from the mass flow controller (MFC)-based method, with a maximum difference of 4.5%. These results demonstrate that the proposed method provides a simple and reliable approach for quantifying the hydrogen amount in metal hydride vessels. Full article

Finned tubes contribute to the heat transfer performance of heat exchangers by increasing the surface area; they also modify patterns within the flow around the tubes and thus increase the likelihood of flow-induced vibrations (FIVs), which can undermine structural integrity. The tradeoff between improved heat transfer and minimized vibration risks is thus of concern in the optimization of finned tube designs. This paper examines the vibration behavior of circular finned tubes fitted in a parallel triangular configuration when subjected to crossflow conditions with particular reference to the structural response as opposed to thermal performance. In this study, two tube bundles arranged in a 30° parallel triangular layout were tested. The test tube has pitch-to-diameter (P/D) ratios of 1.16 and 1.37 and fin densities of 3, 6, and 9. In this study, experiments were conducted in a low-speed closed-loop water tunnel, which also involved the fabrication of circular finned tubes, the preparation of test bundles, and vibration response measurements. The key parameters analyzed in this experiment were the vibration amplitude, damping, pitch ratio, and fin density. Based on the free-stream velocity range of 0.13–0.28 m/s in a 300 mm × 300 mm closed-circuit water tunnel (hydraulic diameter $D_h=0.3$ m), the Reynolds number ranged from 3.9 × 10⁴ to 8.4 × 10⁴ (water at 20 °C). The results of this experiment demonstrate that by increasing the fin density, the vibration amplitudes can be reduced, which also raises the critical velocities. Reducing the pitch ratio from 1.37 to 1.16 produced an onset of instability approximately 53% earlier than the onset of instability at the ratio of 1.37. The bandwidth of the pitch ratio of 1.16 at the same fin density of 9 was almost 45% lower than that at 1.37, which confirms that the system at 1.16 is much more unstable. In general, the 1.37 pitch ratio offers 3 times higher stability margins than those of 1.16 for the fin densities under study. The development of optimal finned tube heat exchanger designs that reduce flow-induced vibrations without sacrificing thermal performance is aided by these findings, which provide information on the relationship between the fin density, pitch ratio and vibration behavior. Full article

Numerical simulations employing the dynamic mesh method were performed to investigate the unsteady aerodynamics of variable-sweep wings during morphing. Quasi-steady and unsteady aerodynamic characteristics were compared, and the effects of key operating conditions (freestream velocity, angle of attack, morphing period, wingspan, chord length) on unsteady aerodynamics were analyzed. To enable the rapid prediction of unsteady aerodynamics, a Kriging surrogate model was established and validated against high-fidelity CFD results. The results indicate that unsteady effects manifest as hysteresis loops in aerodynamic coefficients within the morphing cycle. The wing morphing period, angle of attack, freestream velocity, and wingspan have a pronounced impact on the unsteady aerodynamic characteristics, whereas the effect of chord length is negligible. Reduced morphing periods, increased angles of attack, and increased wingspans amplify the hysteresis loop size and enhance the unsteady effects. An increase in the freestream velocity intensifies unsteady effects in the subsonic flow, while it attenuates unsteady effects in the supersonic flow. Compared to direct CFD simulations, the Kriging model for unsteady aerodynamic characteristics prediction achieves a 97% improvement in overall computational efficiency, while its predicted hysteresis loops are in good agreement with CFD results in both trend and magnitude, with an average prediction error below 4% and a maximum error of less than 6%. The Kriging surrogate model developed in this study offers substantial practical value for engineering applications by meeting the demand for rapid aerodynamic computation in the concept design phase for morphing aircraft. Full article

The navigation of ships in complex shallow water areas is constrained by various factors such as water depth, channel boundaries, and environmental interference. Therefore, it is crucial to improve the adaptability and effectiveness of collision avoidance decisions for ships in complex shallow water scenarios. To address these issues, this paper proposes a multi-factor constrained autonomous decision-making method for complex shallow water vessel maneuvering. Firstly, a digital transportation environment was constructed by combining dynamic and static information, such as water depth, tides, channel boundaries, changes in maneuvering characteristics, and navigation rules, and a navigable water area model that was suitable for shallow water was proposed. Then, considering the constraints of ship maneuverability and the navigation environment, a shallow water ship motion model affected by wind flow was developed. A complex shallow water adaptive maneuvering coupled decision-making method was constructed, considering the influence of ship navigation rules and channel constraints. This method utilizes the Kalman filtering algorithm to correct residuals and predict the maneuvering of the target vessel. Integrated improved heading control and guidance algorithms achieved automatic heading control and future position prediction. Through testing and verification in the complex waters of the Yangtze River estuary, the results show that the autonomous collision avoidance decision-making method proposed in this paper can effectively make collision avoidance decisions in complex multi-ship shallow water areas. This study can provide innovative and practical solutions for the technological development of autonomous ship collision avoidance decision-making. Full article

Reliable traffic load characterization remains a critical challenge in many African countries due to the lack of continuous field measurements. This study developed an integrated dynamic traffic monitoring and weigh-in-motion system on representative highways in Kenya to obtain long-term, multi-source traffic data. Traffic operations were quantified across hourly, weekly, and monthly scales, including flow variability, vehicle class composition, axle loads, overload behavior, and speed distributions. Results indicate that the spatiotemporal characteristics of traffic volume show pronounced short-term fluctuations but strong long-term stability. Despite their lower proportion, multi-axle heavy trucks dominate structural loading, with overload ratios exceeding 80% and gross weights approaching 100 t. Over 60% of vehicles operate at medium-to-low speeds (20–60 km/h), extending load duration and increasing pavement damage potential. These combined effects indicate that average indicators alone underestimate true loading demand. The proposed framework provides field-based traffic load spectra and a transferable methodology for traffic monitoring and pavement design optimization across developing regions in Africa. Full article

Climate change is altering the frequency, duration, and seasonality of low flows, which are critical for water availability, ecosystem functioning, and river management. Low-flow characteristics, defining the minimum, often seasonal, flow levels in rivers or streams primarily fed by groundwater, snow or glacier melt, or lake drainage, are essential for assessing hydrological droughts and water resource vulnerability. In the Upper Vistula River Basin, variable precipitation and rising air temperatures increase the risk of droughts, impacting both natural systems and human water use. This study analyzed long-term trends in annual low flows and associated parameters, including drought frequency, duration, and deficit volume, across 41 small- and medium-sized catchments. Two datasets were considered: 25 stations with 58-year daily discharge records (1961–2019) and 41 stations with 38-year records (1981–2019). Low flows were identified using the threshold level method (TLM) at 70% and 90% exceedance (FDC70 and FDC90). Trends were assessed with the Mann–Kendall test, and spatial drought patterns were mapped to evaluate regional variability. Deep and shallow low flows occurred at all analyzed cross-sections. For the period 1961–2019, deep low flows (FDC90) occurred almost annually in 18 of the 25 cross-sections since 2012. Statistically significant increasing trends in deep low-flow parameters were detected in five cross-sections for 1961–2019 and in seven cross-sections for 1981–2019. Shallow low flows (FDC70) occurred in all sections; four rivers exhibited annual shallow droughts during 1961–2019, whereas 12 rivers showed annual events in 1981–2019. Summer droughts predominated over winter events, reflecting enhanced evapotranspiration and higher seasonal water demand. These findings highlight the relevance of analyzing low-flow parameters for understanding hydrological droughts. Such information can support water resource management, planning, and ecosystem protection under variable climatic conditions. Full article

Oil analysis is one of the main means to obtain the working status of important friction pairs in ship and Marine engineering equipment at present. Analyzing the wear mechanism by analyzing the particle size, morphology, properties and other characteristics of metal abrasive particles in the oil is an important basis for achieving health monitoring and scientific maintenance of ship and Marine engineering equipment. Classifying the abrasive particles in the oil according to their particle size is an important step in sample pretreatment. This paper proposes a two-stage sorting microfluidic chip for wear debris based on magnetophoresis. By setting up external permanent magnets in a stepwise manner in the primary and secondary sorting areas, gradient magnetic fields of different magnitudes were formed. The effects of different sample flow rates, sheath fluid flow rates and sheath flow ratios on the pre-focusing before sorting and the sorting effect were studied. The primary sorting of ferromagnetic metal wear particles larger than 50 µm and the secondary sorting of those smaller than 50 µm have been achieved. The primary sorting can serve as an early warning for abnormal equipment wear, while the secondary sorting can provide data support for the scientific formulation of maintenance plans based on equipment requirements. This work provides a new idea and method for the rapid determination of lubricating oil contamination in engineering equipment. Full article

In engineering flow systems such as hydraulic machinery and marine propulsion, interactions among cavitation bubbles can significantly influence collapse dynamics. This study investigates the collapse behavior of unequal-sized dual cavitation bubbles in a free field, focusing on jet formation modes, morphological evolution, and the characteristics of the Bjerknes force and Kelvin impulse. Particular emphasis is placed on the effect of the bubble radius ratio on the collapse dynamics. The results indicate that: (1) as the radius ratio decreases, the counter-directed jets formed during the collapse of dual cavitation bubbles gradually disappear; (2) with a decreasing radius ratio, the amplitude of the bubble wall velocity first decreases and then increases; and (3) both the Bjerknes force and the Kelvin impulse decrease as the radius ratio decreases. Full article