Search Results (3,599)

Accurate bathymetric information for inland lakes is essential for water resource management, ecological monitoring, and environmental research. However, the accuracy and robustness of remote sensing-based bathymetric retrieval are often constrained by the complex optical properties of inland waters and the limited representation of conventional inversion features. To address these challenges, this study systematically compared the performance of a multiband logarithmic ratio model and three machine learning models, including Random Forest (RF), XGBoost, and AdaBoost, for inland lake bathymetric retrieval. Furthermore, a synergistic retrieval framework integrating chlorophyll-a concentration (Chla) and a Water Optical Index (WOI) was proposed. The results show that: (1) The overall accuracy of the Random Forest, XGBoost, and AdaBoost models constructed with the integration of chlorophyll-a concentration and WOI ($R^2=0.93$, $0.93$, and $0.91$; MAE $=0.06$ m, $0.07$ m, and $0.12$ m; RMSE $=0.14$ m, $0.14$ m, and $0.16$ m) outperforms that of models using only multispectral band information ($R^2=0.93$, $0.91$, and $0.82$; MAE $=0.06$ m, $0.07$ m, and $0.14$ m; RMSE $=0.14$ m, $0.16$ m, and $0.22$ m). Moreover, all these machine learning models significantly outperform the traditional numerical model ($R^2=0.27$; MAE $=0.29$ m; RMSE $=0.45$ m), with the Random Forest model achieving the best overall performance. This indicates that the proposed method offers higher applicability and retrieval accuracy in complex inland lake environments. (2) The optimal Random Forest model integrating chlorophyll-a concentration and WOI achieved high-precision bathymetric inversion for inland lakes ($R^2=0.93$, MAE $=0.06$ m, RMSE $=0.14$ m). Based on the three-dimensional bathymetry derived from this model, the estimated lake storage capacity was $1072.11\times {10}^4$ m${}^3$, compared with a measured volume of $1094.27\times {10}^4$ m${}^3$, yielding a relative error of $-2.03\%$. This result provides reliable and highly accurate data to support water resource management. Full article

The adoption of lithium-ion batteries (LIBs) as secondary rechargeable batteries across many industries, including consumer electronics, electromobility, industrial tools, and electrical energy storage, is on the rise. As lithium-ion batteries approach the end of their life, there is a need to assess them for the possibility of a secondary application or reuse for a less demanding application. The extra connections of individual cells, BMS, temperature sensors, and other components to form a compact battery pack pose a challenge for second-life assessment, which usually prefers to separate individual cells for testing before discarding very bad cells for recycling and grading cells with substantive capacity based on their remaining capacity. This is a high cost for the second-life assessment. This work seeks to investigate an approach that avoids dismantling the battery pack into individual modules, cells, and BMS by including a BMS feature that allows the capacity and power ratings to be rescaled onboard after its first use. A set of cells with different chemistries was used in this work: a nickel–cobalt–aluminium oxide cathode with a silicon-doped graphite anode (NCA-GS), a nickel–cobalt–aluminium oxide cathode and graphite, and a lithium–nickel–manganese–cobalt oxide (NMC) cathode with a graphite anode (NMC-G) with various ageing states and behaviours. Their internal resistance and capacity at the beginning and end of life were compared. The scaling factor was obtained by finding the square root of the ratio of the internal resistance at EOL to that at BOL. With the current obtained by multiplying the cycling current rate by the rescaling factor, the surface temperature profile of the aged cells during cycling became the same as the temperature at the beginning of life. The relaxation voltage after discharge to 0% SOC and charge to 100% SOC was used to set the low and high cut-off voltages, respectively. This contributed significantly to reduced ageing and to a lower temperature rise in the spent cells. This set the stage for rescaling or derating battery systems without separating the individual cells, which is a huge cost for second-life use of lithium-ion batteries. BMS can be designed with configurable voltage and current limits, so that when repurposed for a second life, only a simple configuration or firmware update may be necessary. Full article

This paper presents the design, implementation, and experimental validation of a portable photovoltaic charging station with IoT-based monitoring for autonomous low-power applications. The system integrates a 120 W photovoltaic module, LiFePO₄ battery storage, MPPT regulation, DC/AC conversion, and an ESP32-S3-based acquisition unit connected to a cloud platform for real-time telemetry. Electrical and environmental variables were recorded to evaluate energy balance, conversion losses, State of Charge evolution, and load compatibility under different seasonal operating conditions. Field tests showed that under high-irradiance summer conditions, the prototype supplied multiple laptop loads for approximately 4.5 h with stable operation. In contrast, winter trials revealed a structural energy deficit equivalent to 120% of the initial 24 Ah storage capacity, mainly due to reduced irradiance and cumulative conversion losses ranging from 15% to 25%. Based on the experimental data and deterministic energy-balance modelling, an optimized configuration using a 100 Ah LiFePO₄ battery bank and MPPT regulation was assessed through deterministic energy-balance modelling, thus reducing the required State of Charge to 28.8% under the analyzed operating profile. The results demonstrate the feasibility of a low-cost, IoT-enabled photovoltaic platform for renewable energy harvesting, autonomous power supply, and real-time performance assessment. Full article

To address heat accumulation, localized hot spots, and non-uniform temperature distribution in large-capacity lithium iron phosphate energy storage battery modules under high ambient temperature and high-rate charge/discharge conditions, this study proposes a fin-enhanced phase change material (PCM)-air hybrid thermal management structure for a 100 Ah prismatic lithium iron phosphate battery and a 2P18S energy storage battery module. First, the battery thermal model is validated using single-cell experimental data reported in the literature. Subsequently, a three-dimensional transient fluid–solid coupled heat transfer model is established by considering transient battery heat generation, PCM solid–liquid phase change, air-side flow and heat transfer, and temperature-dependent thermophysical properties. User-defined functions are employed to implement the transient heat source and temperature-dependent material properties. Under identical boundary conditions, the thermal management performances of three configurations, namely Fin-Air, PCM-Air, and Fin-PCM-Air, are compared. The effects of ambient temperature (20 °C, 25 °C, and 30 °C) and inlet air velocity (1 m/s, 2 m/s, and 3 m/s) on the maximum module temperature, temperature uniformity, PCM liquid fraction evolution, and flow field distribution are quantitatively analyzed. The results show that, compared with the Fin–Air system without PCM and the PCM-Air system without fins, the Fin-PCM-Air configuration reduces the maximum module temperature by 1.57% and 0.25%, respectively, at an ambient temperature of 30 °C and an inlet air velocity of 3 m/s. After four charge–discharge cycles, the peak maximum temperature of the module is approximately 38.56 °C, and the peak maximum temperature difference remains below 3.6 K, indicating good temperature uniformity and latent heat buffering capability. In addition, the air velocity trade-off analysis indicates that increasing the inlet air velocity can improve cooling performance but also increases the air-channel pressure drop and fan power consumption. Therefore, the Fin-PCM-Air structure is more suitable for high-thermal-load conditions, and its practical application should comprehensively consider cooling benefits, additional mass, manufacturing cost, and long-term reliability. This study provides a reference for the design and engineering application of hybrid thermal management structures for large-capacity energy storage battery modules. Full article

In the present work, oil-in-water (O/W) cosmetic emulsions containing nanolignin (NL) at 0.35, 1, and 2% w/w were developed using a single multifunctional nanoadditive concept, whereby NL simultaneously acts as an antioxidant, rheology modifier, and color/sunscreen booster. Nanolignin was characterized by FTIR, DLS, and SEM, confirming its chemical structure and nanoscale particle size. The emulsions were evaluated in terms of pH and viscosity stability, rheological behavior, colorimetric CIELAB parameters, DPPH radical scavenging activity, and in vitro sun protection factor (SPF). Incorporation of NL led to a slight pH decrease relative to the blank formulation, while maintaining values within the acceptable cosmetic range (pH 4–6), and yielded emulsions with excellent pH and viscosity stability over 28 days of storage. Increasing the NL concentration modified the rheological profile and viscosity, as well as the L*, a*, and b* color coordinates, enabling tunable visual appearance and texture. All formulations exhibited high antioxidant capacity; notably, the NL_1% emulsion displayed higher radical scavenging activity than the NL_2% system, underscoring a non-linear structure–property relationship. SPF values ranged between 14.09 ± 0.875 and 22.29 ± 1.719, demonstrating that nanolignin can enhance photoprotective performance. Overall, this study highlights the potential of nanolignin as a single multifunctional nanoadditive for designing stable, antioxidant, and photoprotective cosmetic O/W emulsions with adjustable rheology and color. Full article

Upcycling biomass waste into value-added battery materials is crucial for sustainable energy storage. Here, we transform coffee grounds into high-performance hard carbon (HC) anodes for sodium-ion batteries (SIBs) via a synergistic pre-oxidation and acetylene chemical vapor deposition (CVD) strategy, which effectively reduces open pores and promotes structural stabilization. The resulting material exhibits features consistent with a closed-pore architecture. Pre-oxidation incorporates oxygen-containing functional groups that template accessible pores and expand the interlayer spacing during carbonization. Subsequent CVD covers surface pores and contributes to the stabilization of the pore structure. The optimized HC (COF300&1300@C) exhibits a balanced set of structural features, including a low specific surface area (2.1 m² g⁻¹), expanded interlayer distance (0.391 nm), and a well-regulated pore system with reduced surface area and controlled pore size. As a result, it delivers a reversible capacity of 298 mAh g⁻¹ with an ICE of 70%, and remarkable cycling stability (97% capacity retention after 500 cycles at 1C). This study elucidates the synergistic mechanism of pre-oxidation and CVD in reducing open pores and stabilizing the pore architecture, thereby yielding characteristics indicative of closed-pore behavior, and providing a novel and efficient approach for designing high-performance biomass-derived hard carbons for energy storage. Full article

The pore-throat structure is a key factor in the exploration and development of tight sandstone reservoirs. In the present study, 14 tight sandstone samples from the Chang 8 member of the Ordos Basin were analyzed using high-pressure mercury intrusion, cast thin section analysis, scanning electron microscopy and cathodoluminescence imaging techniques. Fractal dimensions, obtained from the slopes of log(S_W) versus log(P_c) double-logarithmic plots, were applied to quantitatively characterize pore-throat structures and classify reservoirs through multifractal analysis, and discuss the diagenetic controlling factors affecting the pore-throat structure of different reservoir types. The results showed that the Chang 14 tight sandstones are characterized as two segments fractal features, which indicated that these samples have complex pore-throat structure and consist of two types of spaces: mesopore-throat spaces and micropore-throat spaces. The mesopore-throat system shows a higher fractal dimension (D1: 2.74–2.99), indicating greater heterogeneity and irregularity, while the micropore-throat system exhibits a lower dimension (D2: 2.28–2.61). D1 exhibits a negative correlation with the porosity and permeability of mesopores, while D2 shows a weak positive correlation with the properties of micropores. The total fractal dimension (D) is weakly correlated with overall reservoir properties, confirming that reservoir storage and flow capacity are primarily governed by the mesopore system rather than the micropore system. By analyzing the contribution of pore throats to sample physical properties, the results indicate that the 14 samples can be classified into two types based on 35% porosity contribution and 60% permeability contribution thresholds. Type 1, reservoirs dominated by microporous throat space (D values ranging from 2.603 to 2.644); Type 2, reservoirs dominated by mesoporous throat space (D values ranging from 2.544 to 2.598). Type 1 is characterized by primary intergranular pores, residual intergranular pores and intergranular dissolution pores, which enhance connectivity and reduce network complexity, thereby improving fluid permeability. In contrast, Type 2 consists mainly of intragranular dissolution pores, intergranular gap pores and micro-dissolution pores in clay minerals, which significantly inhibit fluid mobility. Diagenesis, including compaction, dissolution and cementation, exerts a significant control on the fractal characteristics and pore-throat structure evolution. The fractal characteristics exhibited in the pore-throat structure could provide a desirable analytical method, distinguishing from classification based on scale or size, for the evaluation and classification of tight sandstone reservoirs. Full article

The growing volatility and complexity of global food supply chains have intensified the need for integrated analytical frameworks capable of supporting anticipatory and data-driven decision-making. This article examines how logistics sector observatories can function as strategic intelligence infrastructures for identifying structural tensions and supporting resilience in cold-chain logistics systems. The article introduces the concept of logistics sector observatories as strategic intelligence infrastructures and examines its empirical relevance through a longitudinal analysis of the Spanish cold-chain logistics sector. Empirically, the research draws on a multi-source dataset constructed through the ALDEFE Observatory in collaboration with industry stakeholders over the core study period 2021–2025, encompassing storage capacity, consumption dynamics, energy costs, international logistics indices, and macroeconomic variables. Complementary energy benchmark data for 2019–2025 are used to contextualize electricity cost volatility. Methodologically, the study combines qualitative insights from stakeholder interviews with exploratory quantitative longitudinal analysis. The results suggest severe structural tensions driven by the interaction between rigid capacity constraints and energy cost volatility. The analysis identifies a pattern of persistently high storage occupancy despite substantial energy-price fluctuations. This finding is consistent with the structural inelasticity of cold-chain demand, which reduces operational slack and affects system resilience. Beyond operational resilience, the study highlights the potential contribution of sector observatories to the energy sustainability transition through future sector-level indicators related to energy intensity, refrigeration efficiency, and carbon performance. The study contributes a sector-level, data-driven perspective on visibility, coordination, and anticipatory governance in complex logistics environments. Full article

This study presents the design, development, and evaluation of an integrated solar-powered seed sowing and fertilizer-watering system to enhance planting efficiency, improve resource utilization, and reduce labor in small-scale agriculture. The prototype features a 600-watt photovoltaic panel, DC motors, and a manual mechanical dispensing mechanism, enabling automated seed placement, water distribution, and fertilizer application in off-grid farm environments. Development was guided by a product-based design approach using locally sourced materials to ensure cost-effectiveness, maintainability, and accessibility for rural users. Field simulations and performance trials assessed charging efficiency, seed sowing accuracy, irrigation flow rate, and fertilizer dispensing precision. Results showed high consistency in operational performance, including up to 99% seed placement accuracy, efficient water delivery, and reliable fertilizer timing, with solar energy providing adequate power storage during periods of peak irradiance. Expert evaluations using a standardized instrument demonstrated strong agreement on the system’s usability, material availability, ergonomic features, modularity, and overall functional design. Findings indicate that the system can minimize manual labor, reduce operational costs, and offer a practical transition toward clean-energy–assisted mechanization in agriculture. The study concludes that integrating renewable energy into essential farm operations can contribute to sustainable productivity and recommends future enhancements through sensor integration, increased battery capacity, and adaptive control mechanisms to support wider agricultural adoption. Full article

The operational reliability of wind-powered electric vehicle charging systems (WPECS) depends not only on average wind resources but also on their temporal variability and continuity. This paper proposes a reliability engineering approach for assessing WPECS performance using long-term meteorological data and translating wind resource variability into practical engineering indicators. The proposed methodology adapts classical reliability concepts, including operational availability, deficit frequency, and redundancy sizing, to systems where unavailability is driven mainly by energy source variability rather than component failures. Four indicators are introduced: the Operational Availability Index (OAI), Deficit Event Frequency (DEF), Seasonal Load Factor (SLF), and Operational Continuity Index (OCI). The minimum required energy storage capacity (E_red) is also estimated. The method was applied to 15 meteorological stations in Poland using data from 2001 to 2024. The results revealed substantial spatial differences in WPECS reliability. Four locations achieved high operational availability (OAI_L2 ≥ 0.83) with low storage requirements (<25 MWh), whereas other locations required large or practically infeasible storage capacities. A negative trend in wind resource availability was observed at most stations, indicating a gradual decline in reliability. The results indicate that temporal continuity of wind availability, rather than average energy level alone, is the dominant factor governing operational feasibility and storage requirements of WPECS. The proposed approach supports site selection, storage sizing, and operational planning of WPECS. Full article

Managed aquifer recharge (MAR) is increasingly being realized as an important approach to improve water security in arid and semi-arid environments where there is a low amount of surface water and high climatic variability. This paper introduces a unified approach to the process of locating appropriate MAR locations and estimating recharge potential in Central Kazakhstan through a multi-criteria analysis using geographic information systems (GIS) and hydrogeological field exploration, water balance modelling. Remote sensing datasets and evapotranspiration (ET) analyses were conducted for the 2014–2024 period, while field investigations, infiltration tests, and hydrochemical sampling were performed during the 2025 field campaign. The suitability testing was preliminarily performed in the Google Earth Engine (GEE; Google LLC, Mountain View, CA, USA) environment as a weighted overlay test with the combination of terrain, vegetation, hydrological, and land cover parameters. According to the suitability map obtained and patterns of activity in agricultural activities, eleven candidate sites were identified, out of which eight were found to be suitable after hydrochemical analysis. The Nesterov and Boldyrev techniques of field-based infiltration tests produced a range of 0.05 to 1.42 m/day of hydraulic conductivity. Water balance analysis shows that the total amount of water that could potentially be added to groundwater recharge is about 40.2 million m³/year and that the effective amount of water could be recharged is about 11.0 million m³/year, which is limited by the infiltration processes. This means that about 27 percent of the available water is added into ground water recharge, which is a significant boost to the original estimates. The assessment of the storage capacity of the aquifers indicates that at all locations, the pore space is much greater than the recharge volumes that have been calculated and, therefore, storage is not a limiting factor in the implementation of MAR. It is estimated that the potential MAR rates range between 174 and 5282 m³/day depending on local hydrogeological conditions. The suggested method offers a powerful and generalizable site selection and measurement framework of MAR in arid areas with limited data. The findings highlight the significance of combining remote sensing, field measurements, and process-based modeling to aid sustainable groundwater management and climate adaptation strategies. Full article

This study presents a novel iterative dual-loop methodology for the technical sizing of DC-coupled PV-BESS systems. The method was implemented for a commercial broiler farm characterized by a highly variable electricity demand profile (annual consumption: 7.6 MWh; coefficient of variation: 53%). The methodology introduces two original energy utilization indicators—the photovoltaic-to-converter matching factor (W_{PV_S}) and the photovoltaic-to-BESS matching factor (W_{PV_B})—enabling purely technical optimization independent of economic conditions. Minimization of the radius of curvature of the WPVB characteristic curve is applied as a rigorous mathematical criterion for determining the optimal BESS capacity. Simulation results indicate that the optimal configuration consists of a 9.7 kWp photovoltaic system, a 7 kW DC converter, and a 15 kWh battery storage system. The integration of an optimally sized energy storage system increased the self-consumption coverage ratio from 38% to 59% and improved the photovoltaic energy utilization factor from 35% to 54%. Additional economic analysis demonstrates that the PV-only subsystem achieves a simple payback period ranging from 8 to 18 years, depending on the selected pricing scenario. Consequently, the technically optimal configuration identified using the proposed methodology represents a practically feasible investment for broiler production facilities operating under Polish net-billing conditions. The proposed methodology provides a reproducible, economically independent framework for the design of DC-coupled PV-BESS systems in agricultural prosumer facilities, addressing a critical gap in the optimization literature and offering practical sizing guidelines applicable to similarly high-variability load profiles. Full article

At present, research on the long-term stability of multi-cavern coordinated injection–production operations for salt cavern compressed air energy storage (CAES) remains limited. Large-capacity energy storage utilizing multiple interconnected salt caverns has become an inevitable development trend for modern CAES power stations, highlighting the necessity and importance of stability evaluation and design optimization for underground salt cavern storage clusters. Based on the Anning 350 MW CAES demonstration project, this paper takes the abandoned salt caverns of the project as research objects. A three-dimensional geological and cavern model is established using the FLAC3D numerical simulation method, and stability analysis is carried out under static conditions and three long-term gas injection and production scenarios (the pressure conditions are provided by ground-based equipment). The characteristics of the plastic zone, displacement, stress distribution, and volume shrinkage of the caverns are systematically investigated. The results show that under static conditions, the internal pressure significantly controls the development of the plastic zone, and the caverns are generally stable at pressures above 4 MPa. During long-term operation, the plastic zones of each cavern gradually expand, displacements accumulate continuously, and stresses tend to stabilize after an initial accumulation period. After 30 years of operation, no through-going plastic zones appear in any cavern, and all volume shrinkage rates are below 30%. Among the three cases, Case 1 exhibits the best stability, while enhanced monitoring is required for local high-stress regions in Case 3. This study verifies that the salt cavern development for the Anning CAES project is safe and controllable during long-term operation. The layout spacing of caverns is reasonably designed and fully satisfies the stability requirements of salt cavern CAES power stations. The research results can provide a technical guarantee for the construction of the first CAES power station in Yunnan Province and also offer a reliable reference for the design and construction of similar multi-cavity salt cavern CAES projects. Full article

Hydrogen (H₂) is becoming a meaningful way to store energy for long-term use and support thorough decarbonization in systems that use renewable energy. Underground hydrogen storage (UHS) has strategic benefits over above-ground systems because it can hold large volumes, is contained by geology, and is cheap to operate in cycles. This review compares four key geological formations for underground hydrogen storage (UHS): salt caverns, lined rock caverns, depleted hydrocarbon reservoirs, and saline aquifers. Each system is evaluated based on storage mechanisms, efficiency, safety, technological maturity, and economic feasibility. This review also introduces a unified cross-media evaluation framework, a TRL-risk matrix, a technology development roadmap, and novel insights into AI-based monitoring, offering prescriptive guidance for large-scale UHS implementation. Salt caverns have high injectivity, maintain their purity, and undergo 6 to 12 cycles per year at pressures of 60 to 180 bar; however, they are only found in certain places. Lined rock caverns can be built anywhere, but sealing and economic issues make them difficult to use. Depleted hydrocarbon reservoirs with TWh-scale capacity and already built infrastructure. Saline aquifers, on the other hand, have the most potential in the world but need enhanced management of microbiological responses and cushion gas optimization. A synthesis of current studies highlights key research gaps in cyclic geomechanics, hydrogen–rock–microbe interactions, and liner performance for high-pressure storage. The review concludes with techno-economic and safety considerations and identifies future directions for deploying geological UHS as a critical component of a net-zero hydrogen economy. Full article

The increasing integration of renewable energy introduces uncertainty in microgrid operation, making effective energy management more challenging. Rolling-horizon optimization is used to address this challenge by enabling periodic decision updates; however, most existing approaches rely on fixed optimization horizons and predetermined update frequencies. When prediction accuracy decay (PAD) is considered in adaptive rolling-horizon approaches, it is represented using a fixed decay value, not an online indicator that compares forecasted and actual renewable generation during operation. This leads to suboptimal re-optimization timing, unnecessary computational effort, excessive battery switching, or delayed corrective actions. To address these limitations, this paper proposes a PAD-driven adaptive rolling horizon (ARH) approach, in which re-optimization is triggered using an online PAD indicator computed from the percentage deviation between forecasted and realized renewable generation data. Re-optimization is activated when the PAD indicator exceeds a predefined threshold, enabling adaptive scheduling updates according to real-time forecasting degradation. The problem is formulated as a robust mixed-integer linear programming (MILP) model of a high renewable penetration microgrid, including battery degradation and switching penalties. The energy self-sufficiency ratio (SSR) is used as a key sustainability performance indicator to assess the extent to which local renewable generation and storage satisfy microgrid demand. The proposed approach is first compared with a fixed rolling-horizon approach using a fixed re-optimization interval of 1 h, where the results show a profit improvement of 10.5%. A sensitivity analysis tested the proposed approach under bounded renewable forecast uncertainty levels up to ±15 and different battery capacities. The results indicate that performance is strongly influenced by forecast accuracy and battery capacity, with higher economic gains under low uncertainty and more conservative operation under high uncertainty. Full article