Search Results (7,043)

This paper presents a day-ahead forecasting approach for discharge profiles of a 0.5 MW battery energy storage system connected to the power grid, utilizing historical daily discharge profiles collected over one year to capture key operational patterns and variability. Two forecasting techniques are employed: a Kalman filter for dynamic state estimation and Holt’s exponential smoothing method enhanced with adaptive alpha to capture trend changes more responsively. These methods are applied to generate next-day discharge forecasts, aiming to support better battery scheduling, improve grid interaction, and enhance overall energy management. The accuracy and robustness of the forecasts are evaluated against real operational data. The results confirm that combining model-based and statistical techniques offers a reliable and flexible solution for short-term battery discharge prediction in real-world grid applications. Full article

Fatigue damage of yawed wind turbine components can be caused by repeated long-term unsteady asymmetric inflow loads across the rotor swept area, necessitating fatigue load analysis to ensure the in-operation safety of wind turbines. This study investigates the impact of geometric nonlinearity on the fatigue loads of wind turbine components. The geometrically exact beam theory (GEBT), implemented in BeamDyn of OpenFAST, is employed to model full geometric nonlinearity. For comparison, ElastoDyn in OpenFAST, which uses the generalized Euler–Bernoulli beam theory for straight isotropic beams, is also utilized. Aeroelastic simulations were conducted for the national renewable energy laboratory (NREL 5 MW) and international energy agency (IEA) 15 MW wind turbines. Fatigue loads, quantified by the damage equivalent load (DEL) based on Palmgren–Miner’s rule, were analyzed for critical components, including blade out-of-plane (OOP) moments, low-speed shaft (LSS) torque, LSS bending moment (LSSBM), and tower base bending moment (TBBM). Results indicate that geometric nonlinearity significantly influences fatigue damage in critical turbine components, with significant differences observed between BeamDyn and ElastoDyn simulations. Full article

This study aimed to implement an effective power prediction method to support the optimal management of the 30 MW Nagréongo solar photovoltaic (PV) plant in Burkina Faso. Initially, the performance of the PV plant was assessed by an external consultant based on data recorded in 2023 and 2024, revealing efficiency with a performance ratio (PR) of 73.73% in 2023, which improved to 77.43% in 2024. To forecast the plant’s power output, several deep learning models—namely LSTM, a GRU, LSTM-GRU, and an RNN—were applied using historical power data recorded at five-minute intervals during the 2024 periods of January–February; March–April; and July–August. All the deep learning models achieved accurate short-term forecasting for the 30 MW Nagréongo PV plant, with the seasonal performance shaped by the Sahelian weather regimes. The GRU performed best during the dry season (nRMSE ≈ 4%) and LSTM excelled in the hot months (nRMSE ≈ 2%), while the hybrid LSTM-GRU model proved most robust under rainy-season variability. Overall, the forecasting errors remained within 2–5% of plant capacity, demonstrating the suitability of these architectures for grid integration and operational planning in Sahel PV systems. Full article

The increasing integration of photovoltaic (PV) power systems poses challenges for nighttime voltage regulation because long high-voltage (HV) and ultra-high-voltage (UHV) underground cables generate capacitive reactive power that elevates the grid voltage. Conventional compensators based on passive inductors and capacitors are bulky, costly, and inflexible, rendering them unsuitable for substation use. This study proposes an optimization-based strategy that leverages the existing inverter infrastructure of PV plants to provide nighttime reactive power compensation without additional hardware. A genetic algorithm (GA) determines the optimal number and spatial deployment of inverters to minimize line losses. Field validation at a 120 MW PV plant with 1292 inverters shows that the strategy reduces reverse reactive power from 0.84 MVAr to 0.00214 MVAr and line losses from 1.8235 kW to 0.386 kW using only 55 inverters, achieving near-zero additional capital expenditure (CAPEX). This method enhances the voltage stability and system efficiency while reducing the investment and maintenance costs. Full article

This work aimed to quantify axial deformations of a human premolar during occlusion with its antagonist and to compare them with the same premolar restored with a ceramic crown. The deformations were put under stress using a mechanical press with a force ranging from 1 to 100 Newtons. These deformations were quantified using the optical interferometry technique with a laser source (633 nm, 0.95 mW). Using a CMOS camera, interference fringes were obtained, stored, and subsequently processed. The premolars were restored with Cerasmart GC ceramic, using the CAD-CAM system. The average deformations of healthy premolars were found to be in a range of 0.69 to 1.74 µm, while the restored ones were deformed in a range of 0.53 to 1.10 µm. The results of this work showed that the Cerasmart ceramic material had similar properties to those of the natural tooth for small forces. However, for higher forces, the ceramics increased the coronal stiffness of the tooth. This modified the optimal combination of stiffness, strength, and resilience between the enamel and dentin, causing a decrease in the tooth’s ability to dissipate energy; therefore, the tooth could receive more stress. The observed mechanical properties lead to the conclusion that the Cerasmart material can be indicated for the restoration of anterior and premolar teeth in most cases where a fixed prosthesis is required. Full article

With the rapid expansion of offshore wind power, efficient installation methods for 10 MW offshore wind turbines (OWTs) are increasingly being required. Conventional approaches using installation vessels, heavy-lift barges, and mooring systems incur high costs, long schedules, and weather-related constraints, particularly in harsh seas such as the West Sea and Jeju. This study investigates an anchor-free installation method for jack-up-type OWTs employing tugboats instead of specialized vessels. Environmental loads were estimated with MOSES and AQWA, and frequency-domain analyses were performed to evaluate wave responses and towline tensions. Results showed that maximum tensions remained below both the Safe Working Load of towlines and the Effective Bollard Pull of tugboats during all spudcan lowering stages. Even under conservative OPLIM conditions, feasibility was confirmed. The findings indicate that the proposed tug-assisted method ensures adequate station-keeping capability while reducing cost, construction time, and weather dependency, presenting a practical alternative for large-scale OWT installation. Full article

As the demand for chitin grows, new chitin sources with unique physicochemical properties are required. Abundant biofouling species, such as amphipods and hydroids, have chitinous skeletal systems that can be utilized for chitin production. However, little is known about these chitin sources. This study investigated the viability of amphipods (Jassa sp.) and hydroids (Coryne sp.) obtained from aquaculture biofouling assemblages as novel sources of chitin. Chitin was extracted from these sources and characterized in terms of its degree of acetylation (DA), crystallinity index (CrI), molecular weight (MW), thermal stability, and surface morphology. Physiochemical characteristics where then compared against commercially available shrimp chitin. Results show that a 32.75% chitin yield can be obtained from hydroids. The percentage DA for amphipod (AC) and hydroid (HC) chitin is 58.4–59.2% and 64.8–66.7%, respectively. AC is characterized as α-chitin with a low molecular weight (MW), while HC is medium-MW β-chitin. This finding is significant because it shows hydroids to be a new source of rare β-chitin. In addition, AC has higher thermal stability than HC. AC and HC greatly differ in terms of surface morphology. Therefore, the chitin biomaterials extracted from amphipods and hydroids have different but favorable properties that can be used for diverse applications. Full article

Background/Objectives: Aortic stenosis (AS) leads to progressive left ventricular (LV) pressure overload, adverse myocardial remodeling, and eventual functional decline. While traditional parameters such as left ventricular ejection fraction (LVEF) may remain preserved until advanced stages, they are insufficiently sensitive to early dysfunction. Global longitudinal strain (GLS) offers improved detection but remains load-dependent. In contrast, non-invasive myocardial work (MW)—derived from pressure-strain loops—offers a more load-independent assessment of myocardial function. This systematic review and meta-analysis aimed to evaluate the effects of transcatheter aortic valve implantation (TAVI) on MW indices in patients with severe AS. Methods: We performed a systematic review and meta-analysis of studies reporting non-invasive myocardial work parameters before and after TAVI (PROSPERO ID: CRD420250517138). Databases were searched through 31 March 2025. Pooled mean differences in global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) were calculated using random-effects models. Sensitivity analyses and meta-regression were conducted to explore heterogeneity and the influence of baseline characteristics. Results: Eleven studies encompassing 1493 patients were included. TAVI was associated with a significant reduction in GWI (−236.67 mmHg% [95% CI: −373.82 to −99.52]; I² = 97.0%; p = 0.002) and GCW (−243.71 mmHg% [95% CI: −407.38 to −80.03]; I² = 97.4%; p = 0.006). No significant changes were observed in GWW or GWE. Meta-regression showed age and baseline LVEF significantly influenced GWE changes, but not other parameters. Conclusions: TAVI leads to a significant reduction in GWI and GCW, reflecting decreased myocardial workload and afterload relief. These findings support the utility of MW indices as valuable tools for assessing myocardial adaptation post-TAVI and potentially guiding clinical decision-making. Full article

To address the complex operating conditions and challenging dynamic characteristics of bearings in the main shaft transmission system of wind turbines, this study investigates a specific wind turbine model. By comprehensively considering factors such as main shaft structure, cumulative damage, and stochastic wind loads, we adopt a modular analysis framework integrating the wind field, aerodynamics, the structural response, and fatigue life prediction to establish a method for predicting the fatigue life of main shaft bearings under stochastic wind conditions. To verify this method, the fixed-end main shaft bearing of a 4.5 MW wind turbine was selected as a case study. The research results show the following: (1) Increases in both average wind speed and turbulence intensity significantly shorten the fatigue life of the bearing. (2) Higher turbulence intensity amplifies the dispersion of the speed and load of rolling elements, thereby increasing the probability of extreme operating conditions and exerting an adverse impact on fatigue life. (3) The average wind speed has a significant influence on the overall fatigue life: within a specific range, the fatigue failure probability of the main bearing increases as the average wind speed decreases. (4) The impact of wind speed fluctuations on the hub center load is much greater than that caused by rotational speed changes. (5) In addition, the modular design method adopted in this study calculates that the fatigue life of the fixed-end bearing is 28.8 years, with an overall error of only 0.8 years compared to the 29.6-year fatigue life obtained using Romax simulation software. This research provides important theoretical references and engineering value for improving the operational reliability of wind turbines and enhancing the accuracy of bearing fatigue life prediction. Full article

MXenes, a rapidly emerging family of two-dimensional transition metal carbides and nitrides, have attracted considerable attention in recent years for their potential in next-generation energy storage technologies. In solid-state batteries (SSBs), they combine metallic-level conductivity (>10³ S cm⁻¹), adjustable surface terminations, and mechanical resilience, which makes them suitable for diverse functions within the cell architecture. Current studies have shown that MXene-based anodes can deliver reversible lithium storage with Coulombic efficiencies approaching ~98% over 500 cycles, while their use as conductive additives in cathodes significantly improves electron transport and rate capability. As interfacial layers or structural scaffolds, MXenes effectively buffer volume fluctuations and suppress lithium dendrite growth, contributing to extended cycle life. In solid polymer and composite electrolytes, MXene fillers have been reported to increase Li⁺ conductivity to the 10⁻³–10⁻² S cm⁻¹ range and enhance Li⁺ transference numbers (up to ~0.76), thereby improving both ionic transport and mechanical stability. Beyond established Ti-based systems, double transition metal MXenes (e.g., Mo₂TiC₂, Mo₂Ti₂C₃) and hybrid heterostructures offer expanded opportunities for tailoring interfacial chemistry and optimizing energy density. Despite these advances, large-scale deployment remains constrained by high synthesis costs (often exceeding USD 200–400 kg⁻¹ for Ti₃C₂T_x at lab scale), restacking effects, and stability concerns, highlighting the need for greener etching processes, robust quality control, and integration with existing gigafactory production lines. Addressing these challenges will be crucial for enabling MXene-based SSBs to transition from laboratory prototypes to commercially viable, safe, and high-performance energy storage systems. Beyond summarizing performance, this review elucidates the mechanistic roles of MXenes in SSBs—linking lithiophilicity, field homogenization, and interphase formation to dendrite suppression at Li|SSE interfaces, and termination-assisted salt dissociation, segmental-motion facilitation, and MWS polarization to enhanced electrolyte conductivity—thereby providing a clear design rationale for practical implementation. Full article

4,4′-substituted-2,2′-((hexahydro-1H-benzo[d]imidazole-1,3(2H)-diyl)bis(methylene))bisphenols (1a–d) and 2,6-bis{[3-(2-hydroxy-5-substitutedbenzyl)octahydro-1H-benzimidazol-1-yl]methyl}-4-substitutedphenols (2a–b) were synthesized via microwave (MW) irradiation of aminal (2R,7R,11S,16S)-1,8,10,17-tetraazapentacyclo[8.8.1.1.^8,170.^2,70.^11,16]icosane 2 with p-substituted phenols. Microwave (MW) irradiation improved reaction rates and yields at 80 °C. Compounds 1a–d were racemic, and 2a–b were diastereomeric. NMR spectra revealed key signals for the perhydrobenzimidazole fragment, aromatic rings, and aminal carbons. Differences in the ¹³C NMR spectra highlighted structural variations, such as distinct carbonyl and methoxyl signals in 2d. MW irradiation at higher temperatures (100–120 °C) reduced yields of 1, especially for phenols with methyl (Me) and methoxy (OMe) groups, suggesting a shift toward the formation of compound 2. Additionally, higher temperatures led to polymerization byproducts, emphasizing the impact of MW energy on reaction pathways. These results provide valuable insights for designing molecules with potential applications in materials science and medicinal chemistry. Full article

Microgrids are becoming an innovative piece of modern energy systems as they provide locally sourced and resilient energy opportunities and enable efficient energy sourcing. However, microgrid operations can be greatly affected by sudden environmental changes, deviating demand, and unexpected outages. In particular, extreme climatic events expose the vulnerability of microgrid infrastructure and resilience, often leading to increased risk of system-wide outages. Thus, successful microgrid operation relies on timely and accurate outage predictions. This research proposes a data-driven machine learning framework for the optimized operation of a microgrid and predictive outage detection using a Recurrent Neural Network–Long Short-Term Memory (RNN-LSTM) architecture that reflects inherent temporal modeling methods. A time-aware embedding and masking strategy is employed to handle categorical and sparse temporal features, while mutual information-based feature selection ensures only the most relevant and interpretable inputs are retained for prediction. Moreover, the model addresses the challenges of experiencing rapid power fluctuations by looking at long-term learning dependency aspects within historical and real-time data observation streams. Two datasets are utilized: a locally developed real-time dataset collected from a 5 MW microgrid of Maple Cement Factory in Mianwali and a 15-year national power outage dataset obtained from Kaggle. Both datasets went through intensive preprocessing, normalization, and tokenization to transform raw readings into machine-readable sequences. The suggested approach attained an accuracy of 86.52% on the real-time dataset and 84.19% on the Kaggle dataset, outperforming conventional models in detecting sequential outage patterns. It also achieved a precision of 86%, a recall of 86.20%, and an F1-score of 86.12%, surpassing the performance of other models such as CNN, XGBoost, SVM, and various static classifiers. In contrast to these traditional approaches, the RNN-LSTM’s ability to leverage temporal context makes it a more effective and intelligent choice for real-time outage prediction and microgrid optimization. Full article

The increasing share of renewable energy sources in power grids demands greater load flexibility from thermal power plants. Circulating Fluidized Bed (CFB) combustion systems, while offering fuel flexibility and high thermal inertia, face challenges in maintaining hydrodynamic and thermal stability during load transitions. This study investigates partial flue gas recirculation (FGR) as a strategy to enhance short-term load flexibility in a 1 MW_th CFB pilot plant fired exclusively with solid recovered fuel. Two experimental test series were conducted. Under conventional operation, where fuel and fluidization air are reduced proportionally, load reductions to 86% and 80% led to operating regime shift. Particle entrainment from the riser to the freeboard and loop seal decreased, circulation weakened, and the temperature difference between bed and freeboard zone increased by 71 K. Grace diagram analysis confirmed that the system approached the boundary of the circulating regime. In contrast, the partial FGR strategy maintained total fluidization rates by replacing part of the combustion air with recirculated flue gas. This stabilized pressure conditions, sustained particle circulation, and limited the increase in the temperature difference to just 7 K. Heat extraction in the freeboard remained constant or improved, despite slightly lower flue gas temperatures. While partial FGR introduces a minor efficiency loss due to the reheating of recirculated gases, it significantly enhances combustion stability and enables low-load operation without compromising fluidization quality. These findings demonstrate the potential of partial FGR as a control strategy for flexible, waste-fueled CFB systems and supports its application in future low-carbon energy systems. Full article

This study examines the potential for improved and more sustainable wastewater treatment by integrating coagulation and disinfection using polyaluminum chloride (PACl) and sodium hypochlorite (NaClO) for secondary effluent. The impacts of this integrated approach on phosphorus removal, microbial inactivation, and disinfection by-product (DBP) formation were evaluated through bench- and pilot-scale experiments under both sequential and simultaneous dosing. The results show that simultaneous dosing of PACl and NaClO achieved high phosphorus removal (>90% at 6–9 mg/L PACl), while microbial inactivation targets were met with moderate chlorine doses (3–6 mg/L). Pilot-scale tests further revealed that PACl enhanced microbial inactivation under high-intensity mixing. Importantly, the integrated process reduced DBP formation substantially, with trihalomethanes (THMs) and haloacetic acids (HAAs) lowered by up to ~50% compared to sequential treatment. By minimizing the need for separate treatment units, shortening hydraulic retention time, and lowering overall chemical consumption, this integrated coagulation–disinfection strategy provides a compact, cost-effective, and sustainable alternative to conventional wastewater treatment. Full article

Background/Objectives: Cardiac allograft vasculopathy (CAV) remains a prevalent and serious long-term complication following orthotopic heart transplantation (OHT), contributing substantially to graft failure and patient mortality. Given the adverse prognostic impact of extensive coronary artery involvement, this study investigates whether myocardial work (MW) indices can serve as a non-invasive tool to detect OHT recipients with a high burden of coronary disease. Methods: In this prospective study, 55 OHT recipients underwent paired evaluations with coronary computed tomography angiography (CCTA) and transthoracic echocardiography (TTE) during routine follow-up. From the echocardiograms, global longitudinal strain (GLS) of the left ventricle (LV) and myocardial work (MW) indices were derived. Patients were classified into two groups according to CCTA findings: those without extensive coronary artery disease (disease affecting fewer than four coronary segments or none, OHT < 4) and those with extensive disease (disease of four or more coronary artery segments, OHT ≥ 4). Results: CCTA revealed extensive coronary disease in 38 OHT recipients, while 17 had involvement of fewer than four segments or none. Between-group comparisons showed significant differences in global wasted work (GWW, energy expended without generating forward flow) and global work efficiency (GWE, the percentage of constructive work relative to total work). Using the Youden Index, the optimal thresholds for identifying extensive disease were GWW > 88 mmHg% and GWE < 94%. Patients exceeding these thresholds had a markedly higher probability of having ≥ 4 affected segments, with ORs of 4.61 for pathological GWW and 3.68 for pathological GWE compared to those with normal values. Conclusions: GWW and GWE demonstrated the strongest performance for identifying OHT recipients with extensive coronary disease. If confirmed in larger cohorts, these indices could offer a practical, non-invasive approach for detecting extensive CAV. Full article