Search Results (1,533)

Hydrodynamic cavitation usually occurs in marine and ocean engineering and hydraulic systems and may lead to destructive effects such as an enhanced drag force, noise, vibration, surface damage, and reduced efficiency. Previous studies employed several passive and active control strategies to manage unstable cavitation and its adverse effects. This study reviews various passive and active control strategies for managing diverse cavitation stages, such as partial, cloud, and tip vortex. Regarding the passive methods, different control factors, including the sweep angle of the foil, roughness, bio-inspired riblets, V-shaped grooves, J grooves, obstacles, surface roughness, blunt trailing edge, slits, various vortex generators, and triangular slots, are discussed. Regarding the active methods, various injection methods including air, water, polymer, and synthetic jet and piezoelectric actuators are reviewed. It can be concluded that unstable cavitation can be controlled by both the active and passive approaches independently. However, in the severe conditions of cavitation and higher angles of attack, the passive control methods can only alleviate some re-entrant jets propagating in the downward direction, and proper control of the cavity structure cannot be achieved. In addition, active control methods mostly require supplementary energy and, consequently, lead to higher expenses. Combined passive active control technologies are suggested by the author, using the strengths of both methods to suppress cavitation and control the cavitation instability for a broad range of cavitating flows efficiently in future works. Full article

To address low energy utilization efficiency and severe exergy destruction from direct discharge of high-temperature turbine exhaust, this study proposes a supercritical CO₂ Brayton cogeneration system with a series-connected hot water heat exchanger for stepwise waste heat recovery. Based on finite-time thermodynamics, a physical model that provides a more realistic framework by incorporating finite temperature difference heat transfer, irreversible compression, and expansion losses is established. Aiming to maximize exergy output rate under the constraint of fixed total thermal conductance, the decision variables, including working fluid mass flow rate, pressure ratio, and thermal conductance distribution ratio, are optimized. Optimization yields a 16.06% increase in exergy output rate compared with the baseline design. The optimal parameter combination is a mass flow rate of 79 kg/s and a pressure ratio of 5.64, with thermal conductance allocation increased for the regenerator and cooler, while decreased for the heater. The obtained results could provide theoretical guidance for enhancing energy efficiency and sustainability in S-CO₂ cogeneration systems, with potential applications in industrial waste heat recovery and power generation. Full article

The introduction of Maritime Autonomous Surface Ships (MASS) and the accelerating digitalization of ports require precise and dynamic analysis of traffic conditions. However, conventional marine traffic analyses have been limited to low-resolution grids and static density visualizations without fully integrating vessel direction and speed. To address this limitation, this study proposes a traffic flow visualization model that incorporates dynamic maritime traffic structure. The model integrates density, dominant direction, and average speed into a single symbol, thereby complementing the limitations of static analyses. In addition, high-resolution grids of approximately 90 m were applied to enable detailed analysis. AIS data collected between 2022–2023 from the coastal waters of Mokpo, South Korea, were preprocessed, aggregated into grid cells, and analyzed to estimate representative directions (at 10° intervals) as well as average speeds. These results were visualized through color, thickness, length, and direction of arrows. The analysis showed high-density, low-speed traffic patterns and starboard-passage behavior in port approaches and narrow channels, while irregular directions with low density were observed in non-standard routes. The proposed model provides a visual representation of dynamic traffic structures that cannot be revealed by density maps alone, thus offering practical applicability for MASS route planning, VTS operation support, and risk assessment. Full article

Sediment erosion under turbulent wave action is a highly dynamic process shaped by the interaction between wave properties and sediment characteristics. Despite extensive empirical research, the underlying mechanisms of wave-induced erosion remain insufficiently understood, particularly regarding the threshold energy required for particle mobilization and the factors governing displacement patterns. This study employed a custom-built wave flume and a 3D-printed sampler to examine sediment behavior under controlled wave conditions. Rounded glass beads, chosen to eliminate the influence of particle shape, were used as sediment analogs with a similar specific gravity to natural sand. Ten experiments were conducted to systematically assess the effects of particle size, particle number, input voltage (wave power), and water depth on sediment response. The results revealed that (1) only a fraction of particles were mobilized, with the remainder forming stable interlocking structures; (2) the number of displaced particles increased with particle size, particle count, and water depth; (3) a threshold wave power is required to initiate erosion, though buoyancy under shallow conditions reduces this threshold; and (4) wave steepness, rather than voltage or wave height alone, provided the strongest predictor of sediment displacement. These findings highlight the central role of wave steepness in erosion modeling and call for its integration into predictive frameworks. The study concludes with methodological limitations and proposes future research directions, including expanded soil types, large-scale flume testing, and advanced flow field measurements. Full article

In slab continuous casting, achieving uniform cooling in the secondary cooling zone is essential for ensuring both surface integrity and internal quality. To optimize the process for ship plate steel, a solidification heat transfer model was developed, incorporating radiation, water film evaporation, spray impingement, and roll contact. The influence of secondary cooling water flow on slab temperature distribution was systematically investigated from multiple perspectives. The results show that a weak cooling strategy is crucial for maintaining higher surface temperatures and aligning the solidification endpoint with the soft reduction zone. Along the casting direction, a “strong-to-weak” cooling pattern effectively prevents abrupt temperature fluctuations, while reducing the inner-to-outer arc water ratio from 1.0 to 0.74 mitigates transverse thermal gradients. In addition, shutting off selected nozzles in the later stage of secondary cooling at medium and low casting speeds increases the slab corner temperature in the straightening zone by approximately 50 °C, thereby avoiding brittle temperature ranges. Overall, the proposed multi-dimensional uniform cooling strategy reduces temperature fluctuations and significantly improves slab quality, demonstrating strong potential for industrial application. Full article

Rapid sand filtration is a critical step in the water treatment process, as its effectiveness directly impacts the supply of safe drinking water. However, optimising filtration processes in water treatment plants (WTPs) presents a significant challenge due to the varying operational parameters and conditions. This study applies explainable machine learning to enhance insights into predicting direct filtration operations at the Ålesund WTP in Norway. Three baseline models (Multiple Linear Regression, Support Vector Regression, and K-Nearest Neighbour (KNN)) and three ensemble models (Random Forest (RF), Extra Trees (ET), and XGBoost) were optimised using the GridSearchCV algorithm and implemented on seven filter units to predict their filtered water turbidity. The results indicate that ML models can reliably predict filtered water turbidity in WTPs, with Extra Trees models achieving the highest predictive performance (R² = 0.92). ET, RF, and KNN ranked as the three top-performing models using Alternative Technique for Order of Preference by Similarity to Ideal Solution (A-TOPSIS) ranking for the suite of algorithms used. The feature importance analysis ranked the filter runtime, flow rate, and bed level. SHAP interpretation of the best model provided actionable insights, revealing how operational adjustments during the ripening stage can help mitigate filter breakthroughs. These findings offer valuable guidance for plant operators and highlight the benefits of explainable machine learning in water quality management. Full article

The subject of the research was a prototype two-row sprayer, equipped with a centrifugal fan and directed air-jet emission system, dedicated to the chemical protection of berry plantations, and, in particular, blackcurrants. The prototype was set up with two configurations: “offset”, in which the opposing air streams were “offset” by 0.5 m, and “face-to-face”, when they were positioned opposite each other. The field experiments were carried out on a blackcurrant plantation (Tisel cv.; bush spacing of 4.0 × 0.5 m; height 1.2 m; width 2.5 m). The spray deposition within the crop canopies as well as spray drift to the air and to the ground were assessed using the fluorescence method in order to compare the quality of treatments performed with the two-row sprayer and a conventional axial fan sprayer with radial air discharge system. Spray applications were performed at spray volume 300 L∙ha⁻¹ and working speed 6 km h⁻¹ by both sprayers. The plantation was sprayed with 0.25% water solution of a fluorescent tracer BF7G. The in-canopy spray deposit and spray drift were evaluated using artificial targets made of filter paper. Although directed air-jet sprayer in two configurations (“offset” and “face-to-face”) and conventional one produced similar deposits within the bushes, the spray loss from the directed air-jet sprayer was considerably lower (25.1–32.2%) than that from the conventional sprayer (76.9–81.8%) generating considerably greater airflow volume. Lower PPP losses mean lower environmental impact, which is in line with integrated plant protection. The research responds to numerous inquiries from sprayer manufacturers and blackcurrant growers regarding the most appropriate configuration of the air flow outlet planes. The results obtained will contribute to increasing the efficiency of spraying and facilitate the implementation of the European Green Deal and the achievement of the target of a 50% reduction in the use of plant protection products after 2030 in the EU. Full article

This study investigates the impact of vibration frequency on the performance of a 10-cell open-cathode direct methanol fuel cell (OC-DMFC) stack. Experiments were conducted using three different vibration frequencies (15, 30, and 60 Hz) and compared against a baseline condition without vibration. Performance was evaluated under varying methanol–water fuel flow rates (1, 5, 25, and 50 mL·min⁻¹) while maintaining constant operating conditions: methanol temperature at 70 °C, methanol concentration at 1 M, and cathode air flow velocity at 4.8 m·s⁻¹. The optimal performance was observed at a fuel flow rate of 5 mL·min⁻¹, where the maximum power density reached 26.05 mW·cm⁻² under 15 Hz vibration—representing a 14% increase compared to the non-vibrated condition. These findings demonstrate that low-frequency vibration can enhance fuel cell performance by improving mass transport characteristics. Full article

This study investigates groundwater salinization in a section of a coastal aquifer in Rio Grande do Norte, Brazil, using frequency-domain electromagnetic (FDEM) measurements. With the global expansion of shrimp farming in ecologically sensitive coastal regions, there is an urgent need to assess associated risks and promote sustainable management practices. A key concern is the prolonged flooding of shrimp ponds, which accelerates saltwater infiltration into surrounding areas. To better delineate salinization plumes, we analyzed direct groundwater salinity measurements from 14 wells combined with 315 subsurface apparent conductivity measurements obtained using the FDEM method. Correlating these datasets improved the accuracy of salinity mapping, as evidenced by reduced variance in kriging interpolation. By integrating hydrogeological, hydrogeochemical, and geophysical approaches, this study provides a comprehensive characterization of groundwater salinity in the study area. Hydrogeological investigations delineated aquifer properties and flow dynamics; hydrogeochemical analyses identified salinity levels and water quality indicators; and geophysical surveys provided spatially extensive conductivity measurements essential for detecting and mapping saline intrusions. The combined insights from these methodologies enable a more precise assessment of salinity sources and support the development of more effective groundwater management strategies. Our findings demonstrate the effectiveness of integrating geophysical surveys with hydrogeological and hydrogeochemical data, confirming that shrimp farm ponds are a significant source of groundwater contamination. This combined methodology offers a low-impact, cost-effective approach that can be applied to other coastal regions facing similar environmental challenges. Full article

Electrified powertrains in the transportation sector have increased significantly in recent years, thanks to the need for decarbonization of the on-the-road transport means. However, management of powertrains still deserves particular attention to assess necessary improvements for reducing electric consumption and increasing the mileage of the vehicles. In this regard, electric motor cooling is essential for maintaining optimal performance and longevity. In fact, as electric motors operate, they generate heat due to electric and magnetic phenomena as well as mechanical friction. If not properly managed, this heat can lead to decreased efficiency, accelerated wear, or even failure of critical components. Effective cooling systems ensure that the motor runs within its ideal temperature range, reducing the occurrence of the mentioned concerns. This improves operational reliability and, at the same time, contributes to energy savings and reduced maintenance costs over the components’ life. In this study, the cooling of the rotor of a 130-kW electric motor via refrigerating fluid circulating inside the shaft has been investigated. Two configurations of fluid passages have been considered: a direct-through flow crossing the shaft along its axis and a hollow shaft with recirculating flow, with three types of rotating helical configurations at different pitches. The benefits when using nanofluids as a cooling medium have also been evaluated to enhance the heat transfer coefficient and decrease temperature values. Compared with the baseline configuration using standard fluids (water), the proposed solution employing nanofluids demonstrates effectiveness in terms of heat transfer coefficients (up to 28% higher than pure water), with limited impact on pressure losses, thus reducing rotor temperature by up to 30 K with respect to the baseline. This study opens the possibility of integrating the cooling of the rotor with whole electric motor cooling for electric and hybrid powertrains. Full article

The direct deposition of highly concentrated polyelectrolyte complexes based on poly(ethyleneimine) (PEI) and poly(sodium methacrylate) (PMANa) onto inorganic sand microparticles (F100 and F200) resulted in the formation of versatile core-shell composites with fast removal properties in dynamic conditions toward anionic charged pollutants. Herein, in situ-generated nonstoichiometric PEI/PMANa polyelectrolyte complexes were directly precipitated as a soft organic shell onto solid sand microparticles at a 5% mass ratio (organic/inorganic part = 5%, w/w%). The sorption of an anionic model pollutant (Indigo Carmine (IC)) onto the composite particles in dynamic conditions depended on the inorganic core size, the flow rate, the bed type (fixed or fluidized) and the initial dye concentration. The maximum sorption capacity, after 10 cycles of sorption/desorption of IC onto F100@P5% and F200@P5%, was between 16 and 18 mg IC/mL composite. The newly synthesized core-shell composites could immobilize IC at a high flow rate (8 mL/min), either from concentrated (C_IC = 60 mg/L) or very diluted (C_IC = 0.2 mg/L) IC aqueous solution, demonstrating that this type of material could be promising in water treatment or efficient in solid-phase extraction (concentration factor of 2000). Full article

The optimal control of cooling water systems is of great significance for energy saving in chiller plants. Previously optimal control methods optimize the flow rate, temperature or temperature difference setpoints but cannot control pumps and cooling tower fans directly. This study proposes a direct optimal control method for pumps and fans based on derivative control strategy by decoupling water flow rate optimization and airflow rate optimization, which can make the total power of chillers, pumps and fans approach a minimum. Simulations for different conditions were performed for the validation and performance analysis of the optimal control strategy. The optimization algorithms and implementation methods of direct optimal control were developed and validated by experiment. The simulation results indicate that total power approaches a minimum when the derivative of total power with respect to water/air flow rate approaches zero. The power-saving rate of the studied chiller plant is 13.2% at a plant part-load ratio of 20% compared to the constant-speed pump/fan mode. The experimental results show that the direct control method, taking power frequency as a controlled variable, can make variable frequency drives regulate their output frequencies to be equal to the optimized power frequencies of pumps and fans in a timely manner. Full article

Mountain regions are increasingly affected by the interplay of climate change, infrastructure stress, and evolving socio-ecological systems, intensifying pressure on both water and energy systems. This systematic review investigates how recent scientific literature addresses the management and integration of water and energy systems in mountainous contexts. Following PRISMA guidelines, 88 peer-reviewed studies from 2022 to 2025 were selected through structured database queries and thematic screening. Two key imbalances emerge. First, a geographical imbalance is evident: while the majority of studies come from Asia, Europe shows a strong record of applied efforts, the Americas are moderately represented, and research from Africa remains scarce. Second, a thematic imbalance: water management research is conceptually and methodologically mature, while energy-focused studies remain limited in number and scope. Efforts toward integrated water–energy management are emerging but are mostly confined to pilot projects or modelling exercises, often lacking systemic framing and institutional support. From these findings, three priority directions are identified: advancing adaptive co-design approaches that link water supply, energy storage, ecological flows, and human demand; harmonizing methods, metrics and cross-regional benchmarks to enhance comparability and transferability; strengthening social and institutional pathways to foster resilient, adaptive water–energy systems in mountain environments. Full article

The integration of artificial intelligence (AI) and machine learning (ML) has revolutionised civil engineering, enhancing predictive accuracy, decision-making, and sustainability across domains such as structural health monitoring, geotechnical analysis, transportation systems, water management, and sustainable construction. This paper presents a detailed review of peer-reviewed publications from the past decade, employing bibliometric mapping and critical evaluation to analyse methodological advances, practical applications, and limitations. A novel taxonomy is introduced, classifying AI/ML approaches by civil engineering domain, learning paradigm, and adoption maturity to guide future development. Key applications include pavement condition assessment, slope stability prediction, traffic flow forecasting, smart water management, and flood forecasting, leveraging techniques such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Support Vector Machines (SVMs), and hybrid physics-informed neural networks (PINNs). The review highlights challenges, including limited high-quality datasets, absence of AI provisions in design codes, integration barriers with IoT-based infrastructure, and computational complexity. While explainable AI tools like SHAP and LIME improve interpretability, their practical feasibility in safety-critical contexts remains constrained. Ethical considerations, including bias in training datasets and regulatory compliance, are also addressed. Promising directions include federated learning for data privacy, transfer learning for data-scarce regions, digital twins, and adherence to FAIR data principles. This study underscores AI as a complementary tool, not a replacement, for traditional methods, fostering a data-driven, resilient, and sustainable built environment through interdisciplinary collaboration and transparent, explainable systems. Full article

Comprehension of spatio-temporal groundwater recharge (GWR) under climate change is imperative to enhance water resources availability and management. The main aim of this study is to examine climate change’s effects on spatio-temporal GWR. This study was done by ensembling five climate models and the physically-based WetSpass-M model to estimate GWR during baseline (1986 to 2015), mid-term (2031 to 2060), and long-term (2071 to 2100) periods for the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. In comparison to the Identification of unit Hydrographs and Component flows from Rainfall, Evaporation, and Streamflow (IHACRES)’s baseflow and direct runoff with corresponding WetSpass-M model outputs, the statistical indices showed good performance in simulating water balance components. Projected future temperature and rainfall will likely increase dramatically compared to the baseline period for RCP4.5 and RCP8.5. In comparison to the baseline period, the annual GWR had been projected to increase by 4.28 mm for RCP4.5 for the mid-term (MidT4.5), 15.27 mm for the long-term (LongT4.5), 2.38 mm for the mid-term (MidT8.5), and 13.11 mm for the long-term for RCP8.5 (LongT8.5), respectively. The seasonal GWR findings showed an increasing pattern during winter and spring, whereas it declined in autumn and summer. The mean monthly GWR for MidT4.5, LongT4.5, MidT8.5, and LongT8.5 will increase by 0.34, 1.26, 0.18, and 1.07 mm, respectively. The watershed’s downstream areas were receiving the lowest amount of GWR, and prone to drought. Therefore, this study advocates and recommends that stakeholders participate intensively in developing and implementing climate change resilience initiatives and water resources management strategies to offset the detrimental effects in the downstream areas. Full article