Search Results (413)

The non-uniform distribution of outlet parameters in a Radial Wave Rotor Combustor (RWRC) significantly impacts downstream component performance. This study aims to investigate the spatial-temporal characteristics of temperature and pressure at the RWRC outlet. Three-dimensional unsteady Reynolds-Averaged Navier–Stokes (RANS) simulations were coupled with a User-Defined Function (UDF) to efficiently model the combustion process. The Shear-Stress Transport (SST) k-ω turbulence model was employed. Quantitative metrics including Relative Standard Deviation (RSD) and Christiansen Uniformity Coefficient (CUC) were introduced to evaluate the non-uniformity. The results reveal significant temporal fluctuations and spatial non-uniformity in both temperature and pressure. At 3000 r/min, the average temperature fluctuation amplitude and uniformity coefficient are 0.38 and 0.9, respectively, while the pressure fluctuation amplitude reaches 0.44. Crucially, temperature distribution expands circumferentially with increasing speed, whereas pressure distribution remains locally concentrated and is less sensitive to speed variations. This study provides a quantitative assessment of outlet non-uniformity in RWRC, highlighting the distinct behaviors between temperature and pressure distributions. The findings offer critical insights for the design and optimization of wave rotors and their integration with downstream components. Full article

Current heat transfer coefficient models for scCO₂-MQL exhibit critical limitations because they neglect the Mach disk phenomenon and the effects of radial velocity distribution in the scCO₂ jets. These theoretical deficiencies result in significant deviations in the thermal predictions, limiting the application potential of scCO₂-MQL technology in γ-TiAl machining applications. This study establishes a modified heat transfer coefficient model incorporating Mach disk and radial velocity distribution correction factors to characterise complex jet flow behaviour. Based on the modified heat transfer coefficient model, comprehensive simulation and experimental investigations were conducted to analyse cutting forces, cutting temperatures, stress distributions, and serrated chip formation during scCO₂-MQL machining of γ-TiAl alloys. Results demonstrate that the modified model achieves superior predictive accuracy, with average relative error reductions of 21.8% for cutting force predictions and 37.3% for temperature predictions compared to conventional models. The developed modified heat transfer coefficient model establishes a foundation for the widespread application of scCO₂-MQL cutting of γ-TiAl alloys. Full article

The accurate motion of roller-bearing-supported rings is critically influenced by shape and positional tolerances, which are often underestimated in conventional modeling approaches. The aim of this study is to develop and validate a multibody dynamic framework capable of quantifying the impact of roundness and positional errors on the motion accuracy of roller-bearing-supported rings. Shape errors are modeled using Fourier series and incorporated into a high-fidelity multibody simulation environment. Experimental validation using laser triangulation reveals a maximum runout error of 72.9 μm, compared to a numerically predicted value of 88.6 μm, resulting in a quantified numerical overestimation of 21.5%. Parametric studies investigated the effects of harmonic order, error amplitude, and combined error scenarios on key performance metrics, including trajectory runout and initial offset displacement. Results reveal that the trajectory errors range between 0.29 mm and 0.63 mm for shape error orders and can escalate to 2.84 mm for high amplitude errors, demonstrating the critical role of error order and amplitude. Furthermore, combined simulations show that bearing position errors exert a more pronounced effect on radial accuracy than shape deviations alone. The proposed approach enables precision design evaluation and tolerance optimization in high-accuracy applications, including robotics, aerospace mechanisms, and optical alignment systems. Full article

In this study, the prediction of four radiological risk parameters of thermal waters in Türkiye (dose contribution (D_E) from radon release in thermal water to air for workers and visitors, the annual effective dose from radon ingestion (D_ing) and the annual effective dose to the stomach from radon ingestion (D_sto)) from three physicochemical properties of thermal waters (electrical conductivity (EC), pH and temperature (T)) was investigated using multilayer perceptron (MLP) and radial basis function (RBF) artificial neural networks (ANNs). To achieve this, two separate MLPANN and RBFANN models were constructed using data from the literature. The MLPANN and RBFANN models were verified using performance metrics (relative absolute error (RAE), root mean square error (RMSE), mean absolute error (MAE), and ratio of RMSE to data standard deviation (RSR)). The comparison of performance metrics shows that MLPANN models achieved approximately 54% lower error metrics than RBF models. The performance of the developed models was further examined using rank analysis, Taylor and Scaled Percentage Error (SPE) plots. Rank analysis and Taylor and SPE graphs showed that MLPANN models predicted the values of four radiological risk parameters of thermal waters more correctly than RBFANN models. This study demonstrates that MLPANNs significantly outperformed RBFANNs in predicting the radiological risks of thermal waters in Türkiye. Full article

Precise estimate of antenna location is essential for high-quality three-dimensional (3D) radar imaging, especially under sparse sampling schemes. In scenarios involving synchronized scanning and rotational motion, small deviations in the radar’s transmitting position can lead to significant phase errors, thereby degrading image fidelity or even causing image failure. To address this challenge, we propose a novel trajectory estimation method based on microwave three-point ranging. The method utilizes three fixed microwave-reflective calibration spheres positioned outside the imaging scene. By measuring the one-dimensional radial distances between the radar and each of the three spheres, and geometrically constructing three intersecting spheres in space, the radar’s spatial position can be uniquely determined at each sampling moment. This external reference-based localization scheme significantly reduces positioning errors without requiring precise synchronization control between scanning and rotation. Furthermore, the proposed approach enhances the robustness and flexibility of sparse sampling strategies in near-field radar imaging. Beyond ground-based setups, the method also holds promise for drone-borne 3D imaging applications, enabling accurate localization of onboard radar systems during flight. Simulation results and error analysis demonstrate that the proposed method improves trajectory accuracy and supports high-fidelity 3D reconstruction under non-ideal sampling conditions. Full article

Composite pressure vessels have attracted significant attention in recent years owing to their lightweight characteristics and superior mechanical performance. However, analyzing composite layers remains challenging due to complex filament-winding (FW) pattern structures and the associated high computational costs. This study introduces a homogenization method to achieve cross-scale modeling of carbon fiber-reinforced plastic (CFRP) layers, accounting for both lay-up sequence and in-plane FW diamond-shaped form. The stacking sequence in an FW Type IV composite pressure vessel is numerically investigated through ply modeling and cross-scale homogenization. The composite tank structure, featuring a polyamide PA66 liner, is designed for a working pressure of 70 MPa and comprises 12 helical winding layers and 17 hoop winding layers. An FW cross-undulation representative volume element (RVE) is developed based on actual in-plane mesostructures, suggesting an equivalent laminate RVE effective elastic modulus. Furthermore, six different lay-up sequences are numerically compared using ply models and fully and partially homogenized models. The structural displacements in both radial and axial directions are validated across all modeling approaches. The partial homogenization method successfully captures the detailed fiber-direction stress distribution in the innermost two hoop or helical layers. By applying the Hashin tensile failure criterion, the burst pressure of the composite tank is evaluated, revealing 7.56% deviation between the partial homogenization model and the ply model. Fatigue life analysis of the Type IV composite pressure vessel is conducted using ABAQUS^® coupled with FE-SAFE, incorporating an S-N curve for polyamide PA66. The results indicate that the fatigue cycles of the liner exhibit only 0.28% variation across different stacking sequences, demonstrating that homogenization has a negligible impact on liner lifecycle predictions. The proposed cross-scale modeling framework offers an effective approach for multiscale simulation of FW composite pressure vessels, balancing computational efficiency with accuracy. Full article

As a core component of large marine engines, the compressor delivers robust and efficient power for propulsion. This study focuses on assessing and quantifying the uncertainty in the aerodynamic performance of a transonic rotor under various operating conditions, with the aim of investigating the impact of blade manufacturing variability on performance. Monte Carlo simulation (MCS) and sensitivity analysis were initially employed to identify parameters that significantly influence airfoil performance. Subsequently, a non-intrusive polynomial chaos (NIPC) uncertainty quantification model was developed to compare the effects of tip clearance deviation and surface geometry deviation on rotor performance. The study then analyzes how the geometric deviation at the different spanwise sections affects aerodynamic performance. The results reveal that geometric deviations have a more profound influence on aerodynamic performance than blade tip clearance. The impact of geometric deviations on average pressure ratio and efficiency of the transonic compressor rotor intensifies as the air mass flow rate approaches the near-stall point, while it decreases near the choking point. Interestingly, fluctuations in pressure ratio exhibit the opposite trend. Regarding spatial distribution, deviations in the upper half of the blade span (near the tip) exert a more dramatic influence on mass flow rate and pressure ratio fluctuation. A conceivable reason is that the inlet airflow velocity increases along the radial direction of the blade, and manufacturing variations in the same magnitude produce more notable relative geometric deviations in the upper half of the blade span. Centered on the machining tolerance guidelines for transonic compressor rotors, this work recommends stricter profile tolerance requirements for the upper half of the blade span. Full article

Objective: In the isokinetic literature, relatively limited attention has been paid to muscles of the wrist. Therefore, the objective of this study was to present an isokinetic profile of these muscles comprising the flexors (F); extensors (E); and ulnar (U) and radial (R) deviators. Method: The dominant-side F, E, U and R in 40 healthy participants (20 women and 20 men) were tested concentrically (Con) and eccentrically (Ecc) using a single speed of 90°/s. Results: Men were significantly stronger than women in both the Con and Ecc tests, as indicated by both the absolute (Nm) and the bodyweight-normalized (Nm/kgbw) representations. However, the bodyweight-normalized women/men strength ratio (78.6 ± 8.0%) was significantly higher than the absolute strength ratio (64.1 ± 6.6%). For both the Con and Ecc tests, and irrespective of the representation (absolute or normalized), the U was the strongest muscle group, followed successively by the F, R and E. This rank order was highly significant statistically. The eccentric/concentric strength ratios, E/C_F and E/C_U, were significantly higher in men than in women, with no remarkable inter-sex differences for E/C_E and for E/C_R. A correlational analysis, which included all pairs of basic isokinetic outcome parameters (e.g., the PM of F_con), was performed with respect to ‘sex’ using a nonparametric bootstrap procedure, revealing that men had significantly higher overall correlation coefficients compared to women. Conclusions: The consistency of the main findings with respect to both the sex of the participants and the various strength ratios supports the use of the current protocol. The observed strength order (U > F > R > E) may assist clinicians in setting preliminary return-to-function targets after wrist rehabilitation. Full article

Low-level wind shear (LLWS) is a critical issue in aviation meteorology, posing serious risks to flight safety—especially at plateau airports with high elevation and complex terrain. This study investigates a convective wind shear event at Xining Airport on 29 May 2021. Multi-source observations—including the Doppler Wind Lidar (DWL), the Doppler weather radar (DWR), reanalysis datasets, and automated weather observation systems (AWOS)—were integrated to examine the event’s fine-scale structure and temporal evolution. High-resolution simulations were conducted using the Large Eddy Simulation (LES) framework within the Weather Research and Forecasting (WRF) model. Results indicate that the formation of this wind shear was jointly triggered by convective downdrafts and the gust front. A northwesterly flow with peak wind speeds of 18 m/s intruded eastward across the runway, generating multiple radial velocity couplets on the eastern side, closely associated with mesoscale convergence and divergence. A vertical shear layer developed around 700 m above ground level, and the critical wind shear during aircraft go-around was linked to two convergence zones east of the runway. The event lasted about 30 min, producing abrupt changes in wind direction and vertical velocity, potentially causing flight path deviation and landing offset. Analysis of horizontal, vertical, and glide-path wind fields reveals the spatiotemporal evolution of the wind shear and its impact on aviation safety. The WRF-LES accurately captured key features such as wind shifts, speed surges, and vertical disturbances, with strong agreement to observations. The integration of multi-source observations with WRF-LES improves the accuracy and timeliness of wind shear detection and warning, providing valuable scientific support for enhancing safety at plateau airports. Full article

Background/Objectives: Scapholunate ligament injuries represent one of the most challenging diagnostic problems in wrist surgery, with conventional radiographs often appearing normal despite significant ligamentous disruption. The optimal stress radiographic views for detecting these injuries remain incompletely defined. To systematically evaluate and compare the diagnostic utility of eight different stress radiographic views in detecting isolated scapholunate ligament disruption using a cadaveric model. Methods: Nine fresh-frozen cadaveric wrists underwent complete scapholunate ligament transection while preserving secondary stabilizers. Eight radiographic positions were evaluated: posteroanterior (PA) neutral, PA wrist extension, PA wrist flexion, PA radial deviation, PA ulnar deviation, anteroposterior (AP) clenched fist, AP neutral, and lateral neutral. Scapholunate gap measurements were obtained using calibrated digital software with 20 mm reference markers. Statistical analysis employed repeated-measures ANOVA with post hoc comparisons. Results: PA wrist extension demonstrated the greatest scapholunate gap widening (2.68 ± 0.84 mm, p = 0.006), followed by AP clenched fist views (2.32 ± 1.07 mm, p = 0.036). PA wrist flexion showed significant gap reduction (0.47 ± 0.44 mm, p < 0.001). Twenty-two percent of specimens demonstrated scapholunate angles exceeding 70° on lateral radiographs. Inter-specimen variability was observed, with gap measurements ranging from 1.2 to 4.8 mm across different positions. Conclusions: PA wrist extension and AP clenched fist views demonstrate superior diagnostic utility for detecting scapholunate ligament injuries compared to neutral radiographs. These stress radiographic techniques offer accessible, cost-effective alternatives to advanced imaging modalities for early detection of scapholunate ligament pathology in clinical practice. Full article

This paper presents a heuristic methodology for the optimal expansion of unbalanced three-phase distribution systems in rural areas, simultaneously addressing feeder routing and conductor sizing to minimize the total annualized cost—defined as the sum of investments in conductors and operational energy losses. The planning strategy explores two radial topological models: the Minimum Spanning Tree (MST) and the Steiner Tree (ST). The latter incorporates auxiliary nodes to reduce the total line length. For each topology, an initial conductor sizing is performed based on three-phase power flow calculations using Broyden’s method, capturing the unbalanced nature of the rural networks. These initial solutions are refined via four metaheuristic algorithms—the Chu–Beasley Genetic Algorithm (CBGA), Particle Swarm Optimization (PSO), the Sine–Cosine Algorithm (SCA), and the Grey Wolf Optimizer (GWO)—under a master–slave optimization framework. Numerical experiments on 15-, 25- and 50-node rural test systems show that the ST combined with GWO consistently achieves the lowest total costs—reducing expenditures by up to 70.63% compared to MST configurations—and exhibits superior robustness across all performance metrics, including best-, average-, and worst-case solutions, as well as standard deviation. Beyond its technical contributions, the proposed methodology supports the United Nations Sustainable Development Goals by promoting universal energy access (SDG 7), fostering cost-effective rural infrastructure (SDG 9), and contributing to reductions in urban–rural inequalities in electricity access (SDG 10). All simulations were implemented in MATLAB 2024a, demonstrating the practical viability and scalability of the method for planning rural distribution networks under unbalanced load conditions. Full article

Distribution System Operators (DSOs) increasingly need planning tools that coordinate utility-influenced assets—such as electric-vehicle charging stations (EVCS) and voltage-support resources—with customer-sited distributed generation (DG). We present a Nash-equilibrium-based Iterative Best Response Algorithm (IBRA-NE) for joint planning of DG and EVCS in radial distribution networks. The framework supports two applicability modes: (i) a DSO-plannable mode that co-optimizes EVCS siting/sizing and utility-controlled reactive support (DG operated as VAR resources or functionally equivalent devices), and (ii) a customer-sited mode that treats DG locations as fixed while optimizing DG reactive set-points/sizes and EVCS siting. The objective minimizes network losses and voltage deviation while incorporating deployment costs and EV charging service penalties, subject to standard operating limits. A backward/forward sweep (BFS) load flow with Monte Carlo simulation (MCS) captures load and generation uncertainty; a Bus Voltage Deviation Index (BVDI) helps identify weak buses. On the EEU 114-bus system, the method reduces base-case losses by up to 57.9% and improves minimum bus voltage from 0.757 p.u. to 0.931 p.u.; performance remains robust under a 20% load increase. The framework explicitly accommodates regulatory contexts where DG siting is customer-driven by treating DG locations as fixed in such cases while optimizing EVCS siting and sizing under DSO planning authority. A mixed scenario with 5 DGs and 3 EVCS demonstrates coordinated benefits and convergence properties relative to PSO, GWO, RFO, and ARFO. Additionally, the proposed algorithm is also tested on the IEEE 69-bus system and results in acceptable performance. The results indicate that game-theoretic coordination, applied in a manner consistent with regulatory roles, provides a practical pathway for DSOs to plan EV infrastructure and reactive support in networks with uncertain DER behavior. Full article

During the installation and operation of Pelton turbines, deviations of the jet centerline from the runner pitch circle can compromise turbine stability and efficiency. Utilizing design data from a Pelton turbine on China’s Dadu River, this study employs the SST k-ω and VOF models to investigate the flow characteristics, pressure pulsations, and force on the bucket surface under varying offset conditions. The results demonstrate that radial offset causes the jet to enter the bucket later when deflected outward and earlier when deflected inward. All forms of offset exert adverse effects on turbine performance, with axial offsets causing more severe impacts than radial ones. The maximum pressure pulsation amplitude reached 24%. Afterwards, the erosion of Pelton turbines with different grain sizes was investigated by erosion modeling. It was found that the erosion of large grain size is more serious than that of small grain size. This research provides valuable theoretical insights and an important guiding role for improving the operational stability of Pelton turbines. Full article

To address the inefficiencies of traditional numerical simulations and the high cost of experimental validation in the aerodynamic–stealth integrated design of S-shaped inlets for aero-engines, this study proposes a novel parameter prediction model based on a fuzzy C-means (FCM) clustering and nonlinear dynamic adaptive particle swarm optimization-enhanced radial basis function neural network (NDAPSO-RBFNN). The FCM algorithm is applied to reduce the feature dimensionality of aerodynamic parameters and determine the optimal hidden layer structure of the RBF network using clustering validity indices. Meanwhile, the NDAPSO algorithm introduces a three-stage adaptive inertia weight mechanism to balance global exploration and local exploitation effectively. Simulation results demonstrate that the proposed model significantly improves training efficiency and generalization capability. Specifically, the model achieves a root mean square error (RMSE) of $3.81\times {10}^{-8}$ on the training set and $8.26\times {10}^{-8}$ on the test set, demonstrating robust predictive accuracy. Furthermore, $98.3\%$ of the predicted values fall within the $y=x\pm 3\beta$ confidence interval ($\beta =1.2\times {10}^{-7}$). Compared with traditional PSO-RBF models, the number of iterations of NDAPSO-RBF network is lower, the single prediction time of NDAPSO-RBF network is shorter, and the number of calls to the standard deviation of the NDAPSO-RBF network is lower. These results indicate that the proposed model not only provides a reliable and efficient surrogate modeling method for complex inlet flow fields but also offers a promising approach for real-time multi-objective aerodynamic–stealth optimization in aerospace applications. Full article

Tourism ecological efficiency (TEE) is a significant indicator of the development level of green and intensive tourism. However, conventional directional and radial TEE measurement approaches overlook critical factors such as intermediate process influences and input–output slack variables, potentially leading to biased estimates. Urban areas are key to coordinating tourism across provinces, so accurately assessing the TEE is vital for sustainable regional tourism. This study uses an improved TEE measurement model to measure the TEE of the Guangdong–Fujian–Zhejiang (GFZ) coastal city clusters from 2010 to 2021. The improved TEE measurement model is a three-stage super-efficiency SBM approach. It then uses standard deviation ellipses and geographic detectors to analyze the TEE’s spatiotemporal characteristics and influencing factors. The findings indicate the following: (1) The three-stage super-efficiency SBM approach improves the accuracy and validity of measurement results by removing external environmental variables. (2) During the study period, the TEE values of the GFZ coastal city clusters were above average (except for Meizhou, where the efficiency improved). Temporally, the TEE values of 75% of the cities showed an increasing trend; spatially, the high-value areas increased significantly, the middle- and low-value areas decreased, and the center of gravity shifted to the north and south. (3) The years 2016–2021 saw an increase in external development factors and the use of external resources. The study’s findings can serve as scientific benchmarks for TEE measurement, as well as the low-carbon and environmentally friendly growth of tourism in urban agglomerations. Full article