Search Results (2,835)

The phenomenon known as non-wetting phase (nwp) entrapment, and the multiphase fluid flow within porous media that gives rise to it, is important in several areas such as contaminant transport and subsequent remediation, subsurface energy storage, oil recovery, carbon dioxide sequestration, and pore structural characterisation. The aim of this review was to survey the various different modelling and simulation approaches used to predict the pore-scale processes involved in the entrapment of nwp in disordered porous media, and the impact of pore structural features on the level of entrapment. The various modelling and simulation approaches considered included empirical models, pore network models (PNMs), percolation models, models derived directly from imaging data, and thermodynamic and statistical mechanical techniques. Dynamic flow simulations within models derived from images have validated the quasi-static idealisation for low capillary number, often used with PNMs. Modelling using this approximation has demonstrated the importance of pore connectivity and macroscopic heterogeneities in the spatial distribution of pore sizes in determining entrapment. Dynamic simulations in image-derived models have also shown the need for proper representation of menisci configurations in the complex void spaces of mixed-wetting systems in order to accurately predict entrapment, something that is not always currently possible. Full article

To address the issues of insufficient detector target size and high system complexity in infrared bionic compound-eye systems, this paper designs a miniaturized cooled medium-wave infrared curved bionic compound-eye optical system specifically for large target surface detectors and develops a proof-of-concept prototype for verification. The system comprises three components: (1) a curved multi-aperture array, which consists of 61 sub-apertures with an entrance pupil diameter of 5 mm and a focal length of 10 mm; (2) a cooled planar detector; and (3) a relay imaging system, which adopts secondary imaging technology and achieves the matching between the array and detector with only six infrared lenses. The fill factor is introduced to analyze light energy utilization efficiency, providing a theoretical basis for improving the system’s signal-to-noise ratio and spatial information collection capability; meanwhile, the focal length distribution and pupil matching are analyzed to ensure the system’s optical performance. The system operates within the 3.7–4.8 μm wavelength band, with a total focal length of 3.08 mm, F-number of 2, and field of view reaching 108°. Simulations demonstrate that all sub-aperture imaging channels have MTF values greater than 0.47 at 33.3 lp/mm, with distortion less than 3%. Imaging test results verify that the system possesses excellent imaging performance. Full article

The atmospheric pressure plasma jet (APPJ) is a popular type of cold atmospheric plasma (CAP). APPJs based on a pulsed atmospheric arc (PAA) are widely spread in industrial processing. A plasma jet of this type, PlasmaBrush PB3 (PB3), is a subject of diverse research activities. The characteristic feature of PB3 is the generation of a low-current (300 mA), high-voltage (1500 V) pulsed (54 kHz) atmospheric arc. A gas flow vortex is used to stabilize the arc and to sustain the circular motion of the cathodic arc foot. During long periods of operation, nozzles acting as arc discharge cathodes erode. Part of the eroded material is emitted as nanoparticles (NPs). These NPs are not wanted in many processing applications. Knowledge of the number, type, and size distribution of emitted NPs is essential to minimize their emissions. In this study, NPs in the size range of 6 to 220 nm, emitted from four different nozzles operated with PB3, are investigated. The differences between the nozzles are in the eroded surface material (copper, tungsten, and nickel), the diameter of the nozzle orifice, the length of the discharge channel, and the position of the cathodic arc foot. Significant differences in the particle size distribution (PSD) and particle mass distribution (PMD) of emitted NPs are observed depending on the type and condition of the nozzle and their operating time. Monomodal and bimodal PMD models are used to approximate emissions from the nozzles with tungsten and copper cores, respectively. The skew-normal distribution function is deemed suitable. The results of this study can be used to control NP emissions, both to avoid them and to utilize them intentionally. Full article

Building archetypes are essential for advancing architectural theory and energy modeling, providing a foundation for scalable assessments of building performance and sustainability worldwide. In Saudi Arabia, educational buildings, especially those in public universities, are predominantly constructed using standardized and repetitive design templates, such as courtyard and prototype models, which have significant implications for energy efficiency, indoor environmental quality, and sustainability outcomes. Despite their prevalence, there is a notable lack of systematic research on the classification and distribution of these archetypes within the Saudi context, particularly regarding their impact on energy consumption and sustainable campus planning. This study addresses this gap by systematically collecting and analyzing data from 29 public universities across Saudi Arabia, employing GIS mapping to document building characteristics including age, region, urban context, masterplan typology, and architectural design. A cumulative weighting factor was applied to quantify the representativeness of archetypes, while chi-square tests and effect size metrics assessed the statistical concentration and significance of observed patterns. The results reveal a pronounced dominance of a small number of archetypes, especially standardized courtyard and identical design models, across the national stock, with the top 10% of archetype ranks accounting for the majority of buildings. This high degree of standardization enables efficient modeling, benchmarking, and targeted energy interventions, while also highlighting the need for greater contextual adaptation in future campus planning. While this study does not directly simulate building energy performance, it establishes a national-scale typological foundation that can support future simulation, benchmarking, and policy design. The developed GIS-based framework primarily serves managerial and planning objectives, offering a standardized reference for facility management, retrofitting prioritization, and strategic energy-efficiency planning in Saudi public universities. Full article

Measuring the long-term trend of PM2.5 mass-concentration in urban environments is essential as it has a direct impact on human health. PM2.5 levels depend not only on the intensity of local emission sources and on imported pollution, but also on meteorological conditions (e.g., anticyclonic versus windy conditions), which leads to yearly variations in mean PM2.5 values. Two datasets available for Paris, France, are considered: measurements from Airparif air quality agency network and from the Pollutrack network of mobile car-based sensors. Also, meteorological parameters coming from ERA5 analysis (ECMWF) are considered. Annual values are calculated using three different statistical methods, which yield different results. For the 2013–2024 period, a clear relationship between wind speed and PM2.5 mass-concentration levels is established. The results show a linear decrease in both concentration and standard deviation for wind speeds in the 0–6 m·s⁻¹ range, followed by nearly stable values for wind speed above 6 m·s⁻¹. This behavior is explained by the dispersive effect of strong winds on air pollution. Under such conditions, which occur about 10% of the time in Paris, the contribution of persistent background sources can be isolated. Using the 6 m·s⁻¹ threshold, the average annual linear decrease in emissions from local sources is estimated at 4.1 and 4.3% per year for the Airparif and Pollutrack data, respectively. Since 2023, the annual background value attributed to emission has been close to 5 µg·m⁻³, in agreement with WHO recommendations. This approach could be used to monitor the effects of regulations on traffic and heating emissions and could be applied to other cities for estimating background pollution levels. Finally, future studies should therefore prioritize number concentrations and size distributions, rather than mass-concentrations. Full article

In the Huang-Huai-Hai region, a high kernel moisture content remains a primary constraint for the mechanical harvesting of maize kernels. Recent studies have largely focused on the relationships among ear traits, meteorological factors, and kernel dehydration. However, the regulatory mechanisms underlying the influence of kernel microstructure and starch granule size distribution on dehydration characteristics remain unclear. In this study, the fast-dehydrating variety Jingnongke 728 (JNK728) and the slow-dehydrating variety Zhengdan 958 (ZD958) were selected as experimental materials to compare the varietal differences in kernel microstructure and starch granule size distribution, and to investigate their roles in regulating kernel dehydration characteristics. The results showed that JNK728 had a significantly higher kernel dehydration rate (KDR). Compared with ZD958, JNK728 exhibited average increases of 15.22% in the pre-physiological maturity dehydration rate (pre-KDR) and 97.72% in the post-physiological maturity dehydration rate (post-KDR). The higher accumulations of kernel total starch content and amylopectin content were also observed in JNK728. Kernels of JNK728 were characterized by thinner pericarp at 35 days after pollination (DAP), lower vitreousness and a higher proportion of floury endosperm. Additionally, JNK728 displayed more uniformly sized starch granules with smooth surfaces, wider intergranular spaces, and looser starch packing. Moreover, the volume, number, and surface area of large starch granules (≥10 μm) in JNK728, increased by 2.91%, 10.94%, and 4.95%, respectively. These findings enhance the understanding of the regulatory role of kernel microstructure and starch granule size distribution in dehydration characteristics, offering theoretical guidance for the development of mechanical maize kernel harvesting technologies in the Huang-Huai-Hai region. Full article

The pomegranate cultivar Barski slatki, the most widely cultivated on the Eastern Adriatic coast, was evaluated over one growing season across four growing areas to assess its pomological and chemical properties and antioxidant activity. Results showed that location significantly influenced fruit weight, volume, number of arils per fruit, and both total and individual aril weight, with the Kaštela (CRO) site producing the largest fruits and highest aril yields. Climatic factors, such as precipitation during bud differentiation, flowering, and early fruit development, were found to impact fruit set, aril number, and fruit size. Aril and juice yields, however, remained relatively stable across sites. Notable differences were observed in total soluble solids, titratable acidity, pH, total phenolic content, and anthocyanin profiles. Location with higher rainfall occurring during fruit growth favored enhanced phenolic accumulation. Although total anthocyanin content remained consistent among locations, significant variation occurred in aril coloration and composition of individual anthocyanins. In conclusion, microclimatic factors, particularly rainfall distribution, temperature, and altitude, play a decisive role in shaping the physical, chemical, and visual attributes of ‘Barski slatki’. Despite being cultivated under similar Mediterranean conditions, the observed differences across sites highlight the strong adaptability of this cultivar to diverse agroecological environments, while maintaining stable quality. Full article

Federated learning (FL) enables privacy-preserving adaptation of large language models (LLMs) across distributed clients. However, deploying FL in edge environments remains challenging because of the high communication overhead of full-model updates. Recent advances in parameter-efficient fine-tuning (PEFT), particularly low-rank adaptation (LoRA), have substantially reduced update sizes by injecting lightweight trainable matrices into pretrained transformers, thereby making FL with LLMs more feasible. In this paper, we propose LoRaC-GA, a communication-aware optimization framework that dynamically determines the optimal number of clients to participate in each round under a fixed bandwidth constraint. We formulated a max-min objective to jointly maximize the model accuracy and communication efficiency and solved the resulting non-convex problem using a genetic algorithm (GA). To further reduce the overhead, we integrated a structured peer-to-peer collaboration protocol with ${log}_{2}K$ complexity, enabling scalable communication without full connectivity. The simulation results demonstrate that LoRaC-GA adaptively selects the optimal client count, achieving competitive accuracy while significantly reducing the communication cost. The proposed framework is well-suited for bandwidth-constrained edge deployments involving large-scale LLMs. Full article

This paper analyzes a discrete-time single-server retrial queue with preemptive service, Bernoulli arrivals, and adaptive retrial times, tailored to telecommunications systems. In call centers, the model captures caller retries and priority interruptions, while in cellular networks, it represents user channel access attempts with preemption for emergency calls. Using a Markov chain framework, we derive the stationary distribution, establish a stability condition, and compute performance metrics, including the mean number of retrying callers or users and orbit size probabilities. The model incorporates a novel retrial time adaptation probability, reflecting dynamic retry behaviors in telecommunications. Numerical results demonstrate the impact of arrival rates, preemption probabilities, and retrial adaptations on system performance, offering insights for optimizing call center staffing and cellular network protocols. Applications to slotted ALOHA and TDMA systems highlight the model’s practical relevance. Full article

Background: In healthcare institutions, radiologists play an essential role in patients’ care, enabling them to begin treatment and start their recoveries. However, data on the characteristics and distribution of the radiology workforce in Saudi Arabia are limited. Therefore, this study aimed to conduct a comprehensive analysis of the radiology workforce in SA based on national data and identify key distributional and specialty trends relevant to workforce planning and radiology service delivery. Methods: The following data were obtained from the Saudi Commission for Health Specialties (SCFHS) Registry: total number of registered radiologists, age, subspecialty, professional classification, place of qualification, and geographical location. Descriptive statistics were used for data analysis. Additionally, the findings were compared with those of published international benchmarks. Results: There were 5150 radiologists registered with SCFHS in SA, which corresponded to 147 radiologists per 1,000,000 inhabitants. The mean age was 40.8 years (standard deviation [SD] 9.8), with 60% of them being aged 30–44 years. Most of the radiologists specialised in general diagnostic radiology (83.7%), with few of them specialising in interventional radiology (1.8%), paediatric radiology (1.1%), and breast imaging (0.9%). The workforce mainly comprised consultants (35.0%), followed by registrars (29.7%) and senior registrars (22.7%). Two-thirds (65.0%) of the radiologists had obtained their qualifications abroad. More than half of the radiologists resided in three provinces: Riyadh (29%), Mecca (23%), and the Eastern Region (15%), while several provinces had fewer than 2% of the available workforce. Conclusions: The radiology workforce in SA is relatively young and has a higher density than the average in the European Union. Further, most of the radiologists are professionally classified as consultants or registrars. However, there is a clear imbalance in their geographic distribution, which is consistent with the population sizes of the respective cities. Targeted training expansion and reduced reliance on foreign-trained professionals are warranted to meet future service demands in line with the Vision 2030 objectives. Full article

Reinforced soil retaining walls (RSWs) for railways are key subgrade structures that bear cyclic loads from trains, and their long-term durability directly affects railway operation safety. The mechanical behavior of RSWs under cyclic loading has been extensively investigated in previous studies, primarily focusing on seismic conditions or conventional structural configurations. While these works have established fundamental understanding of load transfer mechanisms and deformation patterns, research on their responses to long-term train-induced vibrations, particularly for concrete-block-panel-wrapped RSWs, an improved structure based on traditional concrete-block-panel RSWs, remains limited. To investigate the dynamic responses of the concrete-block-panel-wrapped RSW, a model test was conducted under cyclic loading conditions where the amplitude was 30 kPa and the frequency was 10 Hz. The model size was 3.0 m in length, 1.0 m in width, and 1.8 m in height, incorporating six layers of geogrid. Each layer of geogrid was 2.0 m in length with a vertical spacing of 0.3 m or 0.15 m. The results indicate that as the number of load cycles increases, deformation, acceleration, static and dynamic stresses, and geogrid strain also increase and gradually stabilize, exhibiting only marginal increments thereafter. The maximum horizontal displacement reaches 0.08% of the wall height (H), with horizontal displacement increasing uniformly along the height of the wall. The vertical acceleration in the non-reinforced soil zone is lower than that in the reinforced soil zone. The horizontal dynamic stress acting on the back of the panel remains minimal and is uniformly distributed along the height of the wall. The maximum geogrid strain was found to be 0.88%, corresponding to a tensile stress amounting to 20.33% of its ultimate tensile strength. The predicted failure surface approximates a bilinear configuration, consisting of one line parallel to the wall face at a distance of 0.3H from the back of the soil bags and another line inclined at an angle equal to the soil’s internal friction angle (φ) relative to the horizontal plane. This study has important reference significance for the application of concrete-block-panel-wrapped RSWs in railways. Full article

This study compares the mapping accuracy of a non-RTK ultra-lightweight drone (DJI Mini2) with two survey-grade RTK-enabled drones (DJI Mavic3E and Phantom4) in three different sites. Flight parameters and weather conditions were the same on each site. The outputs were orthomosaics and digital surface models, whose accuracies were inspected by descriptive statistics and variance analysis tools. The data of the ultralight drone on the first site could not be processed due to strong wind, but its results for the second site (11 hectares) were comparable to those of survey-grade drones, i.e., the range and average of checkpoint errors for Mini2 were 0.17 m and 0.04 m, respectively, while those were 0.10 m and 0.02 m for Phantom4 and Mavic3E. In the third site (34 hectares), survey-grade drones produced accurate results with a checkpoint error range of 0.26 m, while that was 0.87 m for the ultralight drone, implying lower accuracy results. The results obtained suggest that ultralight drones under certain circumstances can produce reliable mapping products depending on weather conditions, the number and distribution of ground control points, and area size. Their biggest drawback is their vulnerability to wind, and in calm weather conditions, due to non-RTK error accumulation, their mapping accuracy degenerates as the area size increases. Full article

The concrete pouring process is difficult to observe inside formwork. With increasingly complex formwork systems and denser reinforcement layouts, honeycomb defects and surface pores are prone to form at beam–column joint core locations. The modeling of pouring processes that were performed earlier is insufficient and there is relatively little research on simulating concrete void defects at typical joints. Therefore, a refined numerical model based on the three-dimensional particle flow method was established to simulate the flow of fresh concrete within formwork and predict concrete voids after pouring. The feasibility of the particle flow method was verified through numerical simulations of slump flow and J-ring tests. Several groups of joint models were set up based on different influencing factors, and the developed particle flow model was used for pouring simulations to investigate the influence of various factors on concrete void formation. The results show that the void volume and distribution patterns obtained from experiments and simulations are basically consistent. The numerical model can accurately simulate the working performance of self-compacting concrete and predict the size and location distribution of pouring defects. Based on both experimental and numerical studies, the following suggestions are proposed to avoid potential void defects in practical concrete pouring projects: reasonably select the number and diameter of joint longitudinal bars; appropriately increase the spacing of column stirrups; appropriately reduce the maximum coarse aggregate particle size; and choose concrete with better fluidity and filling ability. Full article

The evolution characteristics of multi-source-fatigue-crack propagation in the subsurface of a high-speed wheel’s tread and its influence on tread peeling life are the basis for accurately evaluating wheel service lifetime. This study explores the influence of morphology distribution and the size of cracks in the tread on peeling life. The results show that the crack propagation mode in the wheel is mainly mode II and mode III composite propagation caused by shear stress. A fatigue crack inside the wheel with an angle of 45° represents the most dangerous situation. The maximum value of the von Mises stress inside the wheel increases with the increase in the number of multi-source cracks. The equivalent stress intensity factor (SIF) for multi-source cracks is higher than for a single crack. Also, mode III propagation has higher sensitivity to the number of cracks. The existence of multi-source cracks also increases the initial driving force ΔK_eq of crack propagation. The results are useful for the evaluation of the service life of high-speed wheels. Full article

In this work we present strategies for parallelization of algorithms for representing integers as a sum of positive integers using OpenMP (Open Multi-Processing). We consider different types of algorithms—a non-recursive algorithm, a recursive algorithm and its modifications to introduce restrictions on the number and size of the summands. Different strategies for their parallelization are presented. In order to evaluate the efficiency of the strategies, we consider both the execution times and the distribution of work among threads in the presented implementations. Full article