Search Results (914)

Wind power has gained attention as a vital renewable energy source capable of reducing emissions and serving as an effective alternative to fossil fuels. Floating wind farms could significantly enhance the energy capacities of Mediterranean countries. However, location selection for offshore wind farms (OWFs) is a challenge for renewable energy policy and marine spatial planning (MSP). To address these issues, this study considers the marine space of Greece to propose a GIS-based multi-criteria decision-making (MCDM) framework employing the Analytic Hierarchy Process (AHP) to identify suitable sites for OWFs. The approach assesses 19 exclusion criteria encompassing legislative, environmental, safety, and technical constraints to determine the eligible areas. Subsequently, 10 evaluation criteria are weighted to determine the selected areas’ level of suitability. The study considers baseline conditions (1981–2010) and future climate scenarios based on RCP 4.5 and RCP 8.5 for two horizons (2011–2040 and 2041–2070), integrating projected wind velocities and sea level rise to evaluate potential shifts in suitable areas. Results indicate the central and southeastern Aegean Sea as the most suitable areas for OWF deployment. Climate projections indicate a modest increase in suitable areas. The findings serve as input for climate-resilient MSP seeking to promote sustainable energy development. Full article

In the earthquakes that occurred in the Pazarcık (Mw = 7.7) and Elbistan (Mw = 7.6) districts of Kahramanmaraş Province on 6 February 2023, many buildings collapsed in the Hayrullah neighborhood of the Onikişubat district. In this study, we investigated whether there was a soil amplification effect on the damage occurring in the Hayrullah neighborhood of the Onikişubat district of Kahramanmaraş Province. Firstly, borehole, SPT, MASW (multi-channel surface wave analysis), microtremor, electrical resistivity tomography (ERT), and vertical electrical sounding (VES) tests were carried out in the field to determine the engineering properties and behavior of soil. Laboratory tests were also conducted using samples obtained from bore holes and field tests. Then, an idealized soil profile was created using the laboratory and field test results, and site dynamic soil behavior analyses were performed on the extracted profile. According to The Turkish Building Code (TBC 2018), the earthquake level DD-2 design spectra of the project site were determined and the average design spectrum was created. Considering the seismicity of the project site and TBC (2018) criteria (according to site-specific faulting, distance, and average shear wave velocity), 11 earthquake ground motion sets were selected and harmonized with DD-2 spectra in short, medium, and long periods. Using scaled motions, the soil profile was excited with 22 different earthquake scenarios and the results were obtained for the equivalent and non-linear models. The analysis showed that the soft soil conditions in the area amplified ground shaking by up to 2.8 times, especially for longer periods (1.0–2.5 s). This level of amplification was consistent with the damage observed in mid- to high-rise buildings, highlighting the important role of local site effects in the structural losses seen during the Kahramanmaraş earthquakes. Full article

A computational fluid dynamics (CFD) numerical simulation methodology was implemented to model transient heating processes in steel industry reheating furnaces, targeting combustion efficiency optimization and carbon emission reduction. The effects of oxygen concentration (O₂%) and different fuel types on the flow and heat transfer characteristics were investigated under both oxygen-enriched combustion and MILD oxy-fuel combustion. The results indicate that MILD oxy-fuel combustion promotes flue gas entrainment via high-velocity oxygen jets, leading to a substantial improvement in the uniformity of the furnace temperature field. The effect is most obvious at O₂% = 31%. MILD oxy-fuel combustion significantly reduces NOx emissions, achieving levels that are one to two orders of magnitude lower than those under oxygen-enriched combustion. Under MILD conditions, the oxygen mass fraction in flue gas remains below 0.001 when O₂% ≤ 81%, indicating effective dilution. In contrast, oxygen-enriched combustion leads to a sharp rise in flame temperature with an increasing oxygen concentration, resulting in a significant increase in NOx emissions. Elevating the oxygen concentration enhances both thermal efficiency and the energy-saving rate for both combustion modes; however, the rate of improvement diminishes when O₂% exceeds 51%. Based on these findings, MILD oxy-fuel combustion using mixed gas or natural gas is recommended for reheating furnaces operating at O₂% = 51–71%, while coke oven gas is not. Full article

In order to study the problem of obvious wall thinning in the wellbore caused by proppant backflow and sand production under throttling conditions in tight gas wells. Based on the gas-phase control equation, particle motion equation, and erosion model, the wellbore erosion model is established. The distribution law of pressure, temperature, and velocity trace fields under throttling conditions is analyzed, and the influences of different throttling pressures, particle diameters, and particle mass flows on wellbore erosion are analyzed. The flow field at the nozzle changes drastically, and there is an obvious pressure drop, temperature drop, and velocity rise. When the surrounding gas is completely mixed, the physical quantity gradually stabilizes. The erosion shape of the wellbore outlet wall has a point-like distribution. The closer to the throttle valve outlet, the more intense the erosion point distribution is. Increasing the inlet pressure and particle mass flow rate will increase the maximum erosion rate, and increasing the particle diameter will reduce the maximum erosion rate. The particle mass flow rate has the greatest impact on the maximum erosion rate, followed by the particle diameter. The erosion trend was predicted using multiple regression model fitting of the linear interaction term. The research results can provide a reference for the application of downhole throttling technology and wellbore integrity in tight gas exploitation. Full article

On 22 May 2012, a magnitude Mw 5.6 earthquake struck the Pernik region of western Bulgaria, causing structural damage in nearby cities, including Sofia. This study assesses the seismic response of a six-story reinforced concrete building in central Sofia, utilizing real accelerogram data recorded at the basement (SGL1) and sixth floor (SGL2) levels during the earthquake. Using the Kanai–Yoshizawa (KY) model, the study estimates inter-story motion and assesses amplification effects across the structure. Analysis of peak ground acceleration (PGA), velocity (PGV), displacement (PGD), and spectral ratios reveals significant dynamic amplification of peak ground acceleration and displacement on the sixth floor, indicating flexible and dynamic behavior, as well as potential resonance effects. The analysis combines three spectral techniques—Horizontal-to-Vertical Spectral Ratio (H/V), Floor Spectral Ratio (FSR), and the Random Decrement Method (RDM)—to determine the building’s dynamic characteristics, including natural frequency and damping ratio. The results indicate a dominant vibration frequency of approximately 2.2 Hz and damping ratios ranging from 3.6% to 6.5%, which is consistent with the typical damping ratios of mid-rise concrete buildings. The findings underscore the significance of soil–structure interaction (SSI), particularly in sedimentary basins like the Sofia Graben, where localized geological effects influence seismic amplification. By integrating accelerometric data with advanced spectral techniques, this research can enhance ongoing site-specific monitoring and seismic design practices, contributing to the refinement of earthquake engineering methodologies for mitigating seismic risk in earthquake-prone urban areas. Full article

This study presents a detailed analysis of the combustion dynamics of stoichiometric H₂–air and CH₄–air mixtures in a 20 L closed vessel over an initial temperature range of 298–423 K. We integrate experimental pressure–time P(t) measurements with numerical analysis to extract laminar burning velocity (LBV) and deflagration index (K_G) values, and we assess three independent kinetic mechanisms (KiBo_MU, University of San Diego, Lund University) via simulations. For H₂–air, LBV increases from 0.50 m/s at 298 K to 0.94 m/s at 423 K (temperature exponent α ≈ 1.79), while for CH₄–air, LBV rises from 0.36 m/s to 0.96 m/s (α ≈ 2.82). In contrast, the deflagration index K_G decreases by ca. 20% for H₂–air and ca. 30% for CH₄–air over the same temperature span. The maximum explosion pressure (P_max) and peak pressure rise rate ((dP/dt)_max) also exhibit systematic increases with temperature. A comparison with model predictions shows agreement within experiments, providing data for safety modeling and kinetic mechanism validation in H₂- and CH₄-based energy systems. Full article

Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to ensure healthy and favorable conditions for human life but also to the need for the rational use of energy resources. This area is becoming particularly relevant in the context of global challenges related to climate change, rising energy costs and increased environmental requirements. Practice shows that any technical solutions to ensure comfortable temperature, humidity and air exchange in rooms should be closely linked to the concept of energy efficiency. This allows one not only to reduce operating costs but also to significantly reduce greenhouse gas emissions, thereby contributing to sustainable development and environmental safety. In this connection, this study presents a parametric assessment of the influence of climatic and geometric factors on the aerodynamic characteristics of the air cavity, which affect the heat exchange process in the ventilated layer of curtain wall systems. The assessment was carried out using a combined analytical calculation method that provides averaged thermophysical parameters, such as mean air velocity ($V_s$), average internal surface temperature ($t_{in.s}^{av}$), and convective heat transfer coefficient (${\alpha }_s$) within the air cavity. This study resulted in empirical average values, demonstrating that the air velocity within the cavity significantly depends on atmospheric pressure and façade height difference. For instance, a 10-fold increase in façade height leads to a 4.4-fold increase in air velocity. Furthermore, a three-fold variation in local resistance coefficients results in up to a two-fold change in airflow velocity. The cavity thickness, depending on atmospheric pressure, was also found to affect airflow velocity by up to 25%. Similar patterns were observed under ambient temperatures of +20 °C, +30 °C, and +40 °C. The analysis confirmed that airflow velocity is directly affected by cavity height, while the impact of solar radiation is negligible. However, based on the outcomes of the analytical model, it was concluded that the method does not adequately account for the effects of solar radiation and vertical temperature gradients on airflow within ventilated façades. This highlights the need for further full-scale experimental investigations under hot climate conditions in South Kazakhstan. The findings are expected to be applicable internationally to regions with comparable climatic characteristics. Ultimately, a correct understanding of thermophysical processes in such structures will support the advancement of trends such as Lightweight Design, Functionally Graded Design, and Value Engineering in the development of curtain wall systems, through the optimized selection of façade configurations, accounting for temperature loads under specific climatic and design conditions. Full article

The present study was motivated by the need to enhance indoor air quality and reduce airborne disease transmission in dense urban environments where high-rise residential buildings face challenges in achieving effective natural ventilation. The problem lies in the lack of scalable and convenient tools to optimize natural ventilation rate, particularly in urban settings with varying building heights. To address this, the scientific technique developed with an innovative metric, the urbanized natural ventilation effectiveness factor (uNVeF), integrates regression analysis of wind direction, velocity, air change rate per hour (ACH), window configurations, and building height to quantify ventilation efficiency. By employing a field measurement methodology, the measurements were conducted across 25 window-opening scenarios in a 13.9 m² residential unit on the 35/F of a Hong Kong public housing building, supplemented by the Hellman Exponential Law with a site-specific friction coefficient (0.2907, R² = 0.9232) to estimate the lower floor natural ventilation rate. The results confirm compliance with Hong Kong’s statutory 1.5 ACH requirement (Practice Note for Authorized Persons, Registered Structural Engineers, and Registered Geotechnical Engineers) and achieving a peak ACH at a uNVeF of 0.953 with 75% window opening. The results also revealed that lower floors can maintain 1.5 ACH with adjusted window configurations. Using the Wells–Riley model, the estimation results indicated significant airborne disease infection risk reductions of 96.1% at 35/F and 93.4% at 1/F compared to the 1.5 ACH baseline which demonstrates a strong correlation between ACH, uNVeF and infection risks. The uNVeF framework offers a practical approach to optimize natural ventilation and provides actionable guidelines, together with future research on the scope of validity to refine this technique for residents and developers. The implications in the building industry include setting up sustainable design standards, enhancing public health resilience, supporting policy frameworks for energy-efficient urban planning, and potentially driving innovation in high-rise residential construction and retrofitting globally. Full article

To compensate for the instability of renewable energy sources during China’s energy transition, large thermal power plants must provide critical operational flexibility, primarily through deep peaking. To investigate the combustion performance and wear and tear of a 600 MW pulverized coal boiler under deep peaking, the gas–solid flow characteristics and distributions of flue gas temperature, wall heat flux, and wall wear rate in a 600 MW tangentially fired pulverized coal boiler under variable loads (353 MW, 431 MW, 519 MW, and 600 MW) are investigated in this study employing computational fluid dynamics numerical simulation method. Results demonstrate that increasing the boiler load significantly amplifies gas velocity, wall heat flux, and wall wear rate. The maximum gas velocity in the furnace rises from 20.9 m·s⁻¹ (353 MW) to 37.6 m·s⁻¹ (600 MW), with tangential airflow forming a low-velocity central zone and high-velocity peripheral regions. Meanwhile, the tangential circle diameter expands by ~15% as the load increases. The flue gas temperature distribution exhibits a “low-high-low” profile along the furnace height. As the load increases from 353 MW to 600 MW, the primary combustion zone’s peak temperature rises from 1750 K to 1980 K, accompanied by a ~30% expansion in the coverage area of the high-temperature zone. Wall heat flux correlates strongly with temperature distribution, peaking at 2.29 × 10⁵ W·m⁻² (353 MW) and 2.75 × 10⁵ W·m⁻² (600 MW) in the primary combustion zone. Wear analysis highlights severe erosion in the economizer due to elevated flue gas velocities, with wall wear rates escalating from 3.29 × 10⁻⁷ kg·m⁻²·s⁻¹ (353 MW) to 1.23 × 10⁻⁵ kg·m⁻²·s⁻¹ (600 MW), representing a 40-fold increase under full-load conditions. Mitigation strategies, including ash removal optimization, anti-wear covers, and thermal spray coatings, are proposed to enhance operational safety. This work provides critical insights into flow field optimization and wear management for large-scale coal-fired boilers under flexible load operation. Full article

By integrating EarthCARE W-band doppler cloud radar observations with GPM Ku/Ka-band dual-frequency precipitation radar data, this study constructs a novel global “pseudo tripe-frequency” radar coincidence dataset comprising 2886 coincidence events (about one-third of the events detected precipitation), aiming to systematically investigating band-dependent responses to cloud and precipitation structure. Results demonstrate that the W-band is highly sensitive to high-altitude cloud particles and snowfall (reflectivity < 0 dBZ), yet it experiences substantial signal attenuation under heavy precipitation conditions, and with low-altitude reflectivity reductions exceeding 50 dBZ, its probability density distribution is more widespread, with low-altitude peaks increasing first, and then decreasing as precipitation increases. In contrast, the Ku and Ka-band radars maintain relatively stable detection capabilities, with attenuation differences generally within 15 dBZ, but its probability density distribution exhibits multiple peaks. As the precipitation rate increases, the peak value of the dual-frequency ratio (Ka/W) gradually rises from approximately 10 dBZ to 20 dBZ, and can even reach up to 60 dBZ under heavy rainfall conditions. Several cases analyses reveal clear contrasts: In stratiform precipitation regions, W-band radar reflectivity is higher above the melting layer than below, whereas the opposite pattern is observed in the Ku and Ka bands. Doppler velocities exceeding 5 m s⁻¹ and precipitation rates surpassing 30 mm h⁻¹ exhibit strong positive correlations in convection-dominated regimes. Furthermore, the dataset confirms the impact of ice–water cloud phase interactions and terrain-induced precipitation variability, underscoring the complementary strengths of multi-frequency radar observations for capturing diverse precipitation processes. Full article

Aiming at the problem of a full-width horizontal-axis roadheader being prone to diverge from the preset trajectory of the tunnel, a deviation correction control method based on particle swarm optimization–backpropagation (PSO-BP) neural network proportional–integral–derivative (PID) control is proposed. The track error model of the walking system and the transfer function model of the deviation correction control are established. The PSO-BP PID controller is designed; the beginning weights of BP are enhanced by the PSO, and the BP receives the optimal weights to instinctively adapt the PID parameters. An experiment on deviation correction control of the roadheader was carried out. The experimental results indicate that the maximum steady-state error of PSO-BP PID for deflection angle and angular velocity is reduced by 41.03% and 44.93%, respectively, compared with BP PID, and the average rise time for deflection angle and angular velocity is reduced by 75.76%. Full article

Double-suction centrifugal pumps are extensively employed in industrial applications owing to their high efficiency, low vibration, superior cavitation resistance, and operational durability. This study analyzes how impeller oblique cutting angles (0°, 6°, 9°, 12°) affect a double-suction pump at a fixed 4% trimming ratio and constant average post-trim diameter. Numerical simulations and tests reveal that under low-flow (0.7Q_d) and design-flow conditions, the flat-cut (0°) minimizes reflux ratio and maximizes efficiency by aligning blade outlet flow with the mainstream. Increasing oblique cutting angles disrupts this alignment, elevating reflux and reducing efficiency. Conversely, at high flow (1.3Q_d), the 12° bevel optimizes outlet flow, achieving peak efficiency. Pressure pulsation at the volute tongue (P11) peaks at the blade-passing frequency, with amplitudes significantly higher for 9°/12° bevels than for 0°/6°. The flat-cut suppresses wake vortices and static–rotor interaction, but oblique cutting angle choice critically influences shaft-frequency pulsation. Entropy analysis identifies the volute as the primary loss source. Larger oblique cutting angles intensify wall effects, increasing total entropy; pump chamber losses rise most sharply due to worsened outlet velocity non-uniformity and turbulent dissipation. The flat-cut yields minimal entropy at Q_d. These findings provide a basis for tailoring impeller trimming to specific operational requirements. Furthermore, the systematic analysis provides critical guidance for impeller trimming strategies in other double-suction pumps and pumps as turbines in micro hydropower plants. Full article

Annular flow is a common flow configuration encountered in fields such as food engineering, energy and power engineering, and petroleum engineering. The annular space formed by the inner and outer pipes exhibits unique characteristics, with the distinct curvatures of the inner and outer pipes rendering the annulus fundamentally different from a circular pipe. The complexity of the annular structure complicates the rapid calculation of turbulent statistics in engineering practice, as modeling these statistics necessitates a comprehensive understanding of their peak characteristics. However, current research lacks a thorough understanding of the peak characteristics of turbulent flows in annuli with varying diameter ratios (the ratio of the inner tube’s diameter to the outer tube’s diameter) between the inner and outer pipes. To gain a deeper insight into the turbulent peak characteristics within annular flows, this study employs numerical simulation methods to investigate the first- and second-order turbulent statistics under different diameter ratios resulting from varying curvatures of the inner and outer pipes. These statistics encompass velocity distribution, the position and magnitude of maximum velocity, turbulence intensity, turbulent kinetic energy, and Reynolds stress. The research findings indicate that the contour plots of velocity, turbulence intensity, and turbulent kinetic energy distributions under different diameter ratio conditions exhibit central symmetry. The peaks of the first-order statistical quantities are located in the mainstream region of the annulus, and their positions gradually shift closer to the center of the annulus as the diameter ratio increases. For the second-order statistical quantities, peaks are observed near both the inner and outer walls, and their positions move closer to the walls as the diameter ratio rises. The peak values of turbulent characteristics show significant variations across different diameter ratios. Both the inner and outer wall surfaces exhibit peaks in their second-order statistical quantities. For instance, the maximum value of Reynolds stress near the inner tube is 101.4% of that near the outer tube, and the distance from the wall where the maximum Reynolds stress occurs near the inner tube is 97.2% of the corresponding distance near the outer tube. This study is of great significance for optimizing the diameter combination of the inner and outer pipes in annular configurations and for evaluating turbulent statistics. Full article

In the present study, three-dimensional turbulent, subcritical open-channel flow (Fr = 0.19) through submerged rigid vegetation is numerically investigated using the ANSYS FLUENT solver (v. 22. 1). The Volume of Fluid (VOF) method is applied for free-surface tracking, while the standard k-ε turbulence model is employed for turbulence closure. Vegetation is modeled as vertical rigid cylinders fixed at the bottom of the channel. Regarding the arrangement of the stems, two cases are examined. In the first case, a linear arrangement of three equally spaced vegetative stems is located transversely at the center of the channel, while in the second case, a parallel arrangement of fifteen equidistant vegetative stems is located downstream of the channel center. In both cases, the vertical velocity profile within the submerged vegetation layer deviates significantly from that of the upper non-vegetated layer, which generally adheres to the logarithmic velocity distribution. In the second case, flow field repeatability is observed after the third stem series, particularly in terms of velocity profiles. Additionally, the structure of turbulence is noticeably affected in the vicinity of the stems, resulting in higher eddy viscosity values near each stem’s crest area. Furthermore, a localized drop in the free surface is recorded above the vegetated region, while a slight rise is observed upstream of each stem series, consistent with subcritical open-channel flow. Full article

The demand for large-scale, heavy-duty autonomous pavement-sweeping robots is rising due to urban growth, hygiene needs, and labor shortages. Ensuring their health and safe operation in dynamic outdoor environments is vital, as terrain unevenness and slope gradients can accelerate wear, increase maintenance costs, and pose safety risks. This study introduces an AI-driven condition monitoring (CM) framework designed to detect terrain unevenness and slope gradients in real time, distinguishing between safe and unsafe conditions. As system vibration levels and energy consumption vary with terrain unevenness and slope gradients, vibration and current data are collected for five CM classes identified: safe, moderately safe terrain, moderately safe slope, unsafe terrain, and unsafe slope. A simple-structured one-dimensional convolutional neural network (1D CNN) model is developed for fast and accurate prediction of the safe to unsafe classes for real-time application. An in-house developed large-scale autonomous pavement-sweeping robot, PANTHERA 2.0, is used for data collection and real-time experiments. The training dataset is generated by extracting representative vibration and heterogeneous slope data using three types of interoceptive sensors mounted in different zones of the robot. These sensors complement each other to enable accurate class prediction. The dataset includes angular velocity data from an IMU, vibration acceleration data from three vibration sensors, and current consumption data from three current sensors attached to the key motors. A CM-map framework is developed for real-time monitoring of the robot by fusing the predicted anomalous classes onto a 3D occupancy map of the workspace. The performance of the trained CM framework is evaluated through offline and real-time field trials using statistical measurement metrics, achieving an average class prediction accuracy of 92% and 90.8%, respectively. This demonstrates that the proposed CM framework enables maintenance teams to take timely and appropriate actions, including the adoption of suitable maintenance strategies. Full article