Search Results (367)

An investigation was conducted into the effectiveness of heat shields in an aero-engine compressor casing to slow down thermal time constants. The investigation used a combination of experimental measurements from a full-size compressor casing rig, combined with numerical analysis using CFD and thermal modelling. Experiments were performed on a compressor casing both with and without heat shielding in order to determine the heat shield effectiveness. Temperature measurements were taken throughout the casing in order to determine the thermal time constants. The experimental data was then used to validate a thermal model and CFD simulations of the compressor casing. The modelling allowed the heat transfer coefficients in the compressor casing to be determined from the experimentally measured time constants. It was found that the heat shields gave an increase in thermal time constant at each measured location. With a doubling in the time constant at some locations compared to the unshielded case. It was also found that the heat shields need to be fully sealed, as leakage flows significantly reduce their effectiveness. Full article

Comprehensive monitoring of gas extraction parameters is crucial for the safe production of coal mines. However, it is a challenge to collect the overall gas drainage network parameters with limited sensors due to technical and econoincorporating mic constraints. To address this issue, a nonlinear model for gas confluence structure is construed for the conservation of mass, energy, and gas state properties. Considering exogenous variables such as frictional loss correction coefficient (α) and air leakage resistance coefficient (β), as well as the iterative structure of drainage networks, a hybrid PSO–Newton algorithm framework is designed. This framework realizes iterative solutions for multi confluence structures by combining global optimization (PSO) and local nonlinear solving (Newton’s method). A case study using historical monitoring data from the 11,306 working face of S Coal Mine was conducted to evaluate the proposed algorithm at both branch and drill field scale. The results show that key parameters such as gas flow velocity, concentration, and density align with actual observation trends, with most deviations within 10%, verifying the accuracy and effectiveness of the algorithm. A deviation comparison between the standalone Newton’s method and the PSO–Newton algorithm further demonstrates the stability of the latter. By enabling the derivation of comprehensive network parameters from limited monitoring data, this study provides strong support for the intelligent management of coal mine gas extraction. Full article

To accurately investigate the loss characteristics of fuel cell vehicles (FCVs) under actual operating conditions and enhance their power performance and economic efficiency, this study establishes a numerical model of the proton exchange membrane fuel cell (PEMFC) stack based on real-world data from the second-generation Mirai. The stack model incorporates leakage current losses and imposes a limit on maximum current density. Besides, this study analyzes the effects of operating parameters (PEM water content, hydrogen partial pressure, current density, oxygen partial pressure, and operating temperature) on stack power output, efficiency, and eco-performance coefficient (ECOP). Furthermore, Non-Dominated Sequential Genetic Algorithm (NSGA-II) is employed to optimize the PEMFC stack performance, yielding the optimal operating parameter set for FCV operation. Further simulations are conducted on dynamic performance characteristics of the second-generation Mirai under two typical driving cycles, evaluating the power performance and economy of the FCV before and after optimization. Results demonstrate that the established PEMFC stack model accurately analyzes the output performance of an actual FCV when compared with real-world performance test data from the second-generation Mirai. Through optimization, output power increases by 7.4%, efficiency improves by 1.95%, and ECOP rises by 3.84%, providing guidance for enhancing vehicle power performance and improving overall vehicle economy. This study provides a practical framework for enhancing the power performance and overall energy sustainability of fuel cell vehicles, contributing to the advancement of sustainable transportation. Full article

Rubber materials undergo continuous wear in high-pressure seal applications. To address the risk of adhesive wear and consequent leakage of rubber seals operating under reciprocating sliding in high-pressure hydrogen storage and refueling systems, this study employed high-pressure hydrogen tribology testing. Ball-on-disk reciprocating tests were conducted using a 316L stainless-steel ball against silica-filled nitrile butadiene rubber (NBR), and the friction response and wear-morphology evolution were compared under ambient air, 1 MPa hydrogen (H₂), 50 MPa H₂, 50 MPa nitrogen (N₂), and grease-coated conditions. Under dry sliding, the coefficient of friction (COF) of NBR in air and hydrogen ranged from 1.34 to 1.44, whereas it decreased markedly to 0.942 in 50 MPa N₂. The wear volume under the four dry conditions was concentrated in the range of ~0.292–0.320 mm³. After grease coating, the steady-state COF in air and at 50 MPa H₂ dropped to 0.099 and 0.105, respectively, and the wear features changed from ridge-like wear patterns/tear pits to regular, smooth indentations with slight running marks. The results demonstrate that a lubricating film can effectively separate direct metal–rubber contact and suppress stick–slip, enabling a low-friction, low-wear, and highly stable interface in high-pressure hydrogen, and providing a practical engineering route for reliable operation of rubber seals in hydrogen service. Full article

The emulsification of a molten fusible metal alloy in a liquid epoxy matrix with its subsequent curing is a novel way to create a highly concentrated phase-change material. However, numerous challenges have arisen. The high interfacial tension between the molten metal and epoxy resin and the difference in their viscosities hinder the stretching and breaking of metal droplets during stirring. Further, the high density of metal droplets and lack of suitable surfactants lead to their rapid coalescence and sedimentation in the non-cross-linked resin. Finally, the high differences in the thermal expansion coefficients of the metal alloy and cross-linked epoxy polymer may cause cracking of the resulting phase-change material. This work overcomes the above problems by using nanosilica-induced physical gelation to thicken the epoxy medium containing Wood’s metal, stabilize their interfacial boundary, and immobilize the molten metal droplets through the creation of a gel-like network with a yield stress. In turn, the yield stress and the subsequent low-temperature curing with diethylenetriamine prevent delamination and cracking, while the transformation of the epoxy resin as a physical gel into a cross-linked polymer gel ensures form stability. The stabilization mechanism is shown to combine Pickering-like interfacial anchoring of hydrophilic silica at the metal/epoxy boundary with bulk gelation of the epoxy phase, enabling high metal loadings. As a result, epoxy shape-stable phase-change materials containing up to 80 wt% of Wood’s metal were produced. Wood’s metal forms fine dispersed droplets in epoxy medium with an average size of 2–5 µm, which can store thermal energy with an efficiency of up to 120.8 J/cm³. Wood’s metal plasticizes the epoxy matrix and decreases its glass transition temperature because of interactions with the epoxy resin and its hardener. However, the reinforcing effect of the metal particles compensates for this adverse effect, increasing Young’s modulus of the cured phase-change system up to 825 MPa. These form-stable, high-energy-density composites are promising for thermal energy storage in building envelopes, radiation-protective shielding, or industrial heat management systems where leakage-free operation and mechanical integrity are critical. Full article

Coal mine ventilation systems face coupled and systemic risks characterized by structural interconnection and disaster chain propagation. In order to accurately quantify and evaluate this overall system risk, this study presents a new method of risk assessment of the coal mine ventilation system based on fuzzy polymorphic Bayesian networks. This method effectively addresses the shortcomings of traditional assessment approaches in the probabilistic quantification of risk. A Bayesian network with 44 nodes was established from five dimensions: ventilation power, ventilation network, ventilation facilities, human and management factors, and work environment. The risk states were divided into multiple states based on the As Low As Reasonably Practicable (ALARP) metric. The probabilities of evaluation-type root nodes were calculated using fuzzy evaluation, and the subjective bias was corrected by introducing a reliability coefficient. The concept of distance compensation is proposed to flexibly calculate the probabilities of quantitative-type root nodes. Through the verification of the ventilation system of H Coal Mine in Shanxi, China, it is concluded that the high risk of the ventilation system is 18%, and the high-risk probability of the ventilation system caused by the external air leakage of the mine is the largest. The evaluation results are consistent with real-world conditions. The results can provide a reference for improving the safety of the ventilation systems. Full article

This study presents an analysis of the Infrastructure Leakage Index (ILI) variability for two District Metered Areas (DMAs) in the Silesian Region (Poland), based on 2024 data. The objective of the study was to evaluate whether high-frequency AMI data can be used to reliably identify and remove distorted measurement periods, thereby improving the credibility of the annual ILI value for each individual DMA. ILI_T values were calculated for daily, weekly, and monthly intervals using synchronized hourly data from an Advanced Metering Infrastructure (AMI) system and water network monitoring platforms. A key methodological advantage was the use of fully synchronous inflow–outflow–consumption data, enabling diagnostic reconstruction of hourly water balances and validation of the representativeness of data segments used for ILI_T estimation. The study applied statistical measures of variability (standard deviation, variance, coefficient of variation) and graphical methods (histograms, boxplots) to evaluate ILI_T behavior across time resolutions. Rather than comparing leakage performance between DMAs—which is performed exclusively using normalized indicators such as ILI—the analysis examined how hourly diagnostic information explains short-term distortions in the ILI and how filtering such periods affects the stability of the annual value for each DMAs. The results confirm that ILI_T interpretation is highly dependent on temporal resolution. Daily data is more responsive to anomalies and operational events, while monthly data provides more stable values suitable for benchmarking. The findings demonstrate that daily and hourly data should be used diagnostically to detect non-representative periods, whereas monthly aggregation provides the most robust basis for reporting and inter-DMA comparison. Overall, the study proposes a practical procedure for ILI validation using AMI data and demonstrates its application on two real DMAs. Full article

To address three core deficiencies of the existing research on ZnO varistors (incomplete full-lifecycle datasets, insufficient characterization robustness due to the lack of multi-parameter complementarity, and disconnected remaining life prediction and failure threshold determination), this study proposes a comprehensive technical solution for ZnO varistor remaining life prediction. An 8/20 μs impulse current accelerated deterioration experiment was designed to construct a full-lifecycle dataset (441 sets of data) covering nine same-batch ZnO varistors from their initial state to complete failure. Five core electrical parameters (varistor voltage U_1mA, nonlinear coefficient α, leakage current I_L, parallel resistance R_p, parallel capacitance C_p) were fused, and principal component analysis (PCA) was adopted for dimensionality reduction to form a high-robustness characterization feature (correlation coefficient with deterioration degree = 0.96). A combined model of Particle Swarm Optimization-Support Vector Regression (PSO-SVR) and Isolation Forest (iForest) was established to realize “quantitative prediction–qualitative threshold” collaboration. Experimental results show that the PSO-SVR model achieves high-precision remaining life prediction (test set R² = 0.9726, MSE = 0.00142) and the iForest model accurately identifies the failure threshold (AUC = 0.984, accuracy = 95.9%). The combined model reaches an overall accuracy of 99.89%, effectively solving the core deficiencies of the existing research and providing key technical support for SPD-condition monitoring and operation and maintenance decisions in energy systems. Full article

As a critical sealing component in aero-engines, the segmented annular seal is prone to friction and wear during the running-in stage, which seriously impairs its sealing performance and service life. To address this issue, this study takes the three-petal segmented annular seal made of T482 graphite as the research object, adopting a combined method of high-speed ring-block friction and wear tests and thermal–fluid–solid coupling simulation to investigate its friction and wear mechanisms and optimize its structural design. The results show that the segmented annular seal undergoes more severe friction and wear in the low-speed running-in stage; the wear rate increases with the rise in loading force and decreases with the increase in rotational speed, and the variation trend of surface roughness is consistent with that of the friction coefficient. Frictional heat and wear-induced scratches intensify the deformation and leakage of the seal, thereby leading to the risk of seal failure. Optimizing the depth of radial dynamic pressure grooves can significantly improve the opening performance of the seal, while optimizing the width of axial grooves mainly affects the seal leakage. This research provides a theoretical basis for improving the service life and sealing performance of segmented annular seals in aero-engines. Full article

Youth unemployment remains one of the most persistent and structurally sensitive challenges in emerging economies, particularly in environments characterized by macroeconomic volatility and frequent shocks. This study investigates the dynamics and forecasting performance of youth unemployment in Turkey by adopting a symmetry-based multivariate framework that explicitly contrasts equilibrium-oriented and asymmetric temporal behaviors. Using monthly data covering the period 2009–2024, youth unemployment is modeled jointly with key macroeconomic indicators, including economic growth, inflation, overall unemployment, labor force participation, migration, exchange rates, and consumer confidence. The empirical strategy integrates traditional econometric models and modern machine learning approaches under a unified and leakage-free evaluation protocol. Stationarity and long-run properties of the series are examined using unit root tests and the Bayer–Hanck cointegration approach, followed by long-run coefficient estimation via FMOLS and DOLS. Forecasting performance is then compared across VARIMA, Prophet, and deep learning models (RNN, LSTM, and GRU), including both vanilla and hyperparameter-tuned specifications. The results reveal a clear performance hierarchy. VARIMA models, particularly the VARIMA (p = 2, q = 0) specification, consistently outperform all alternatives by a wide margin, achieving exceptionally low forecast errors. This finding indicates that youth unemployment in Türkiye is predominantly governed by symmetric co-movements and long-run equilibrium relationships among macroeconomic variables. Prophet and GRU models capture short-term and regime-sensitive fluctuations more flexibly, reflecting asymmetric temporal responses, but at the cost of higher forecast dispersion. In contrast, RNN and LSTM models exhibit limited generalization capability and are prone to overfitting in the small-sample macroeconomic context. As a result, this study positions the estimation of youth unemployment as both an econometric challenge and a symmetry-based analytical problem, offering new methodological and conceptual insights consistent with a fresh perspective. Full article

High concentrations of tropospheric ozone (${\mathrm{O}}_3$) in urban areas pose a significant risk to human health. This study proposes an evaluation framework based on the XGBoost algorithm to predict ${\mathrm{O}}_3$ concentration, assessing the model’s capacity for seasonal extrapolation and spatial transferability. The experiment uses hourly air pollution data (${\mathrm{O}}_3$, NO, ${\mathrm{NO}}_2$, and NOx) and meteorological factors (temperature, relative humidity, barometric pressure, wind speed, and wind direction) from six monitoring stations in the Monterrey Metropolitan Area, Mexico (from 22 September 2022 to 21 September 2023). In the preprocessing phase, the datasets were extended via feature engineering, including cyclic variables, rolling windows, and lag features, to capture temporal dynamics. The prediction models were optimized using a random search, with time-series cross-validation to prevent data leakage. The models were evaluated across a concentration range of 0.001 to 0.122 ppm, demonstrating high predictive accuracy, with a coefficient of determination (${\mathrm{R}}^2$) of up to 0.96 and a root-mean-square error (RMSE) of 0.0034 ppm when predicting summer (${\mathrm{O}}_3$) concentrations without prior knowledge. Spatial generalization was robust in residential areas (${\mathrm{R}}^2$ > 0.90), but performance decreased in the industrial corridor (AQMS-NL03). We identified that this decrease is related to local complexity through the quantification of domain shift (Kolmogorov–Smirnov test) and Shapley additive explanations (SHAP) diagnostics, since the model effectively learns atmospheric inertia in stable areas but struggles with the stochastic effects of NOx titration driven by industrial emissions. These findings position the proposed approach as a reliable tool for “virtual detection” while highlighting the crucial role of environmental topology in model implementation. Full article

This paper proposes a novel framework for embedding the Fixed And Variable Area Discharge (FAVAD) equation into the software EPANET 2.2 for the simulation of water distribution networks (WDNs). This framework yields a realistic model of leakage outflows that accounts for the expansion of the leak area as a function of service pressure. Without altering the source code of EPANET, this is accomplished by using node emitters and by iteratively adjusting emitter coefficients in the Matlab^® (R2023a) environment to mimic the effects of the FAVAD equation along WDN pipes. An additional benefit consists of preventing backflow occurring under negative pressure conditions in EPANET 2.2. The application to two benchmark WDNs under various leakage configurations demonstrates the robustness and the numerical efficiency of the framework, as well as the impact and benefits of the FAVAD formulation. For instance, for pipes with higher elasticity, omitting the expansion of the leak area leads to an underestimation of the total leakage rate that exceeds 30% for one of the studied cases. Furthermore, the algorithm successfully prevents leakage backflow under both demand-driven and pressure-driven analyses. Full article

The International Agreement on the Carriage of Perishable Foodstuffs and on the Special Equipment to Be Used for Such Carriage (usually known as ATP Treaty) defines a standardized isothermal test for qualifying refrigerated containers, but its current protocol is lengthy, costly and lacks scientific justification. This paper presents a combined theoretical and experimental study aimed at optimizing this procedure. First, a heat-transfer framework based on transient conduction and thermal diffusivity is developed to estimate stabilization times using dimensionless criteria. Then, extensive experimental tests on ATP containers validate these predictions and reveal additional phenomena such as air leakage and chimney effects. Based on these findings, a revised protocol is proposed that reduces the test duration from more than 18 h to approximately 2 h while preserving the thermal stabilization conditions required by ATP. Experimental results show that the uncertainty in the determination of the global heat-transfer coefficient K is reduced from about 2–$2.3\%$ in the classical ATP procedure to roughly $0.7$–$1.0\%$ with the new protocol. In addition, the method suppresses secondary physical effects—such as chimney-driven air leakage and latent-heat losses due to water evaporation—thus improving the physical representativeness of the measured K value. The proposed accelerated protocol offers a scientifically grounded, cost-effective alternative for future ATP standards. Full article

Vertical axial-flow pumps with bidirectional passages are widely used in applications requiring flow reversal. However, their unique inlet geometry often leads to asymmetric impeller inflow conditions. This study investigates the internal flow behavior and pressure pulsation characteristics of a vertical bidirectional axial-flow pump under design, critical stall, and deep stall conditions using unsteady Reynolds-averaged Navier–Stokes simulations combined with Fast Fourier Transform and wavelet analysis. Results show that the pump reaches peak efficiency at the design point, with critical and deep stall occurring at 0.6 Q_des and 0.5 Q_des, respectively. The head at the deep stall condition shows a further drop of 7.51% compared to the critical stall condition. This progressive performance degradation is attributed to vortex-induced blockage: it initiates with the intensification of the tip leakage vortex and evolves into large-scale separation vortices covering the suction surface under deep stall—a mechanism distinctly influenced by the bidirectional inlet’s stagnant water zone. Inlet asymmetry, reflected by a normalized velocity coefficient (V_n) below 0.6 in the stagnant water zone under design flow, is partially mitigated during stall due to flow confinement. Pressure pulsations at the blade leading edge are dominated by the blade passing frequency (BPF), with amplitudes under critical stall about 3.2 times those at design conditions. At the impeller outlet, critical stall produces a mixed dominant frequency (shaft frequency and BPF), whereas deep stall yields the highest pulsation amplitude (BPF ≈ 4.8 × the design value) resulting from extreme passage blockage. These findings clarify how bidirectional-inlet-induced vortices modulate stall progression and provide theoretical guidance for enhancing the operational stability of such pumps under off-design conditions. Full article

During the mid-to-late stages of oilfield development, reservoir energy depletion and declining formation pressure coefficients are prevalent challenges. To address the issues of severe fluid loss and extended post-workover fluid recovery periods during conventional operations such as thermal wax removal and pump inspection in low-pressure, waxy wells within a specific block of the Xinjiang Oilfield, a dynamic loss analysis model for workover fluids was developed. Additionally, a wash pressure control valve was engineered to meet the requirements for squeeze killing under abnormal conditions, and an integrated anti-leakage tubing string was designed. This system effectively isolates the workover fluid from the reservoir during interventions, thereby significantly reducing fluid loss and enhancing operational safety. Field applications demonstrate that this technology reduces workover fluid loss by 96% during thermal wax removal and shortens the average post-workover fluid recovery period by 8.7 days after pump inspection. This technology enables rapid restoration of well productivity, lowers operational costs for thermal wax removal and pump inspection, and provides an effective solution for maintaining low-pressure, waxy wells. Full article