The Zr/Hf-ZrC1−x/HfC1−x rods were prepared by the carbon diffusion in situ reaction. The effects of different carbonization temperatures and carbon sources on the microstructures and the ablative behavior of the rods were investigated. The results show that due to the infinite solution of HfC and ZrC, a two-layer structure was formed in the Zr-Hf alloy rods. The outer layer was ZrC/HfC ceramic layer. The inner was composed of Zr/Hf-ZrC1−x/HfC1−x mixing layer decorated with some isolated ZrC1−x/HfC1−x grains. The thickness of the ceramic layer increased with the increase of carbonization temperature. When C/C-ZrC-SiC was used as the carbon source, the thickness of the ceramic layer was obviously higher than that of graphite used as a carbon source. After ablation, a molten ZrO2-HfO2 outer layer was formed on the rod surface, which acted as an oxide compensation to the substrate surface. The ZrC xO y/HfC xO y layer with a low oxygen diffusion coefficient was formed inside the rod. Meanwhile, ZrO2, HfO2, and their solid solution particles were sintered and densified, which reduced the oxygen permeability of the oxide layer and enhanced ablation resistance.
In order to better characterize the plastic flow behavior of GH4169 superalloy, isothermal compression tests of GH4169 superalloy at different temperatures and strain rates were carried out using Gleeble 1500 thermal simulator. The back propagation artificial neural network (BP-ANN) constitutive model of GH4169 superalloy was established based on true stress–strain data, and the relationship between the prediction stability of the constitutive model and the model parameters was further investigated. The prediction results show that the BP-ANN model outputs were highly influenced by the model parameters. To address this issue, genetic algorithm (GA) was used to optimize the BP-ANN constitutive model, and the GA-BP-ANN integrated constitutive model was presented. The optimization results show that the GA-BP-ANN integrated constitutive model greatly enhances the prediction stability and improves the generalization ability of GH4169 superalloy’s BP-ANN constitutive model.
In order to improve the strength of C/C composites and 304 SS brazed joint, two substrates were brazed by adding metal interlayers (Ni, Mo, Ni/Mo) to BNi-2 or AgCuTi filler metals. The objective of this study was to investigate the microstructure, joint mechanism, and mechanical properties of the brazed joints. The findings revealed that the microstructure of the BNi-2+Ni/Mo joint consisted of Cr3C2, Ni(s, s), Cr xNi y+MoNi4, Mo, MoNi4+Cr xM y, and Ni(s, s) + Cr-Fe. The interfacial microstructure of the AgCuTi+Ni/Mo joint in the control experiment consisted of TiC, Ag(s, s) + Cu(s, s), Ni, Ag(s, s)+Cu(s, s)+MoTi, Mo, and MoTi+Cu(s, s)+Ag(s, s). Finite element simulations demonstrated that the Ni/Mo composite interlayer effectively alleviated residual stresses in the C/C substrates. The average shear strength of the BNi-2+Ni/Mo brazed joints at room temperature was found to be 2.57 MPa, while the average shear strength of the AgCuTi+Ni, Mo, and Ni/Mo joints were 10.91 MPa, 23.81 MPa, and 26.77 MPa, respectively.
Electrochemical impedance spectroscopy (EIS) and potentiometric polarization (Tafel) tests were utilized to investigate the corrosion protection efficiency of epoxy (EP) composite coatings reinforced with aluminum powder additives deposited on carbon steel substrate. Different aluminum powders including pure aluminum (Al) and aluminum composites powders containing alumina (Al2O3) and carbon nanotubes (CNTs) were used as an additive filler. Various aluminum composite powders containing 2 wt.% of each CNTs and Al2O3 nanoparticle were synthesized using ball milling and then added into EP coating at concentration of 1 wt.%. It was found that the incorporation of formulated additive fillers improves the corrosion resistance of neat EP coating owing to enhanced barrier properties of EP composite coatings. It was also found that the barrier property of Al/CNT/Al2O3 additive is more significant than other additives owing to reduced particle size and certain shapes of particles as it further reduces the transport paths for penetration of corrosive environment through the coating and greatly prevents possible reactions at metal substrate/coating interface. Moreover, EP-Al/CNT/Al2O3 maintained one-time constant characteristic and showed the highest impedence and stability over the whole exposure time. In addition, the presence of these additives strengthens the coating, leading to further improvement of barrier property of the coating.
When an external alternating field reaches a threshold value, high-temperature superconductors (HTS) that are carrying direct current can exhibit dynamic resistance phenomenon. This phenomenon, often observed in tape applications, can be effectively studied using finite element methods (FEM). However, due to differences in production processes, HTS tapes have varying parameters, including magnetic-dependent critical current. This can pose a significant challenge when comparing dynamic resistance differences among HTS tapes. Due to the capability of machine learning to conveniently handle the nonlinear characteristics of superconductors and adapt to multivariate function fitting, this paper employs machine learning for fitting the critical current characteristics of tapes and applies it to calculate dynamic resistance in the FEM model. By employing machine learning to handle the critical current characteristics of various tapes, the FEM model showcases both feasibility and accuracy in the results.
L-ascorbic acid (AA, also known as vitamin C) and dopamine (DA) play important roles in human life activities. When their concentrations are abnormal, they will cause diseases. Therefore, it is of great interest to develop an effective strategy to detect AA and DA levels. Here, anodic aluminum oxide (AAO) films were used as templates to fabricate indium-tin (InSn) alloy nanowires (NWs) by vacuum mechanical injection method, and then Pt nanoparticles were coated on the surface of the InSn NWs by means of the “in-situ discharge reduction” method. Subsequently, the composites were exposed in air for heat treatment to synthesize PtO2/indium-tin oxide (ITO) NWs. Finally, PtO2/ITO NWs were reduced under H2 atmosphere to obtain Pt/ITO NWs. The results show that the diameter of the InSn NWs is ∼40 nm and Pt nanoparticles with 2–5 nm are uniformly coated on the surface of the ITO NWs. Additionally, the performance of electrochemical detection of AA and DA on the Pt/ITO NWs electrode is tested by the cyclic voltammetry and differential pulse stripping voltammetry. The Pt/ITO NWs electrode has low detection limits in the detection of AA (66.7 µM) and DA (1 µM), which reveals the good electrochemical detection of AA and DA.
To improve the smart manufacturing capabilities of strip hot rolling, based on digital twin (DT) and cyber-physical system (CPS), this paper proposes a data-driven approach for diagnosing hot-rolled strip crown. Since the hot rolling process features heredity, nonlinearity and strong coupling, the diagnosis of strip crown is an imbalanced problem with ill-defined decision boundaries. Conventional regression methods tend to learn more information from the majority class, which ignore the strip with unqualified crown. To address this challenge, a hybrid multi-stage ensemble model (HMSEN) is presented to classify strip crown. Initially, a novel data-resampling method that combines adaptive synthetic sampling (ADASYN) with repeated edited nearest neighbor (RENN) is proposed to assign more attention to unqualified crown. Subsequently, using the reinforced data, a multi-stage ensemble model is built to enhance the classification performance. Furthermore, the best-performing HMSEN is identified by exploring various combinations of base classifiers. The experimental results demonstrated the proposed novel resampling method outperforms comparison methods on crown dataset. Significantly, the proposed HMSEN outperforms not only the existing regression models but also the mechanism model. Therefore, HMSEN is the most robust and effective model to intelligently diagnose hot-rolled strip crown with unbalanced data.
AlCl3-NaCl-KCl low-temperature molten salt system with anhydrous SnCl2 was used to study the preparation of Al-Sn alloy by electrodeposition. The morphology and composition of the alloy were analyzed by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD); The corrosion resistance, wear resistance and antifriction of the alloy were tested and analyzed respectively by polarization curve method and wear and friction experiment; The hardnesses of the alloy and the film substrate adhesion were characterized respectively by Vickers hardness tester and automatic scratch tester for coating adhesion. The results showed that when the SnCl2 content in the electrolyte was 0.04–0.08 g, a medium tin-aluminum alloy with tin content of 10%–18% could be prepared. The optimum deposition temperature was 160–200 °C, the deposition time was 40–50 min, and the current density was 40–50 mA/cm2. With the increase of tin content in the coating, its corrosion resistance gradually became worse and the friction and wear resistance showed a trend of increasing first and then decreasing. When the SnCl2 content was 0.06 g, the tin content in the coating was 14 wt%, the friction and wear resistance were the best. With the increase of the deposition temperature, the film substrate adhesion and hardness of the alloy coating showed a trend of increasing first and then decreasing. When the deposition temperature was 200 °C, the best adhesion and hardness were obtained.
In this paper, the inhibition ability of tetrasodium pyrophosphate (TSPP), sodium tripolyphosphate (STPP) and sodium hexametaphosphate (SHMP) to scheelite, fluorite and calcite was predicted by performance calculation and further verified by micro-flotation test. The results of hydrophile lipophilic balance (HLB) calculation, group electronegative calculation and micro-flotation test indicated that the inhibition ability of phosphate to the three minerals increases with the increase of the number of phosphate groups and the order of inhibition ability of the three inorganic phosphates was SHMP > STPP > TSPP. STPP had great potential for flotation separation of scheelite from fluorite and calcite. The order of inhibition ability of STPP against the three calcium-bearing minerals is calcite>fluorite>scheelite. The results of contact angle measurement, adsorption amount measurement, X-ray photoelectron spectroscopy (XPS) analysis and atomic force microscope (AFM) imaging presented that the adsorption of STPP on the fluorite and calcite surface was much larger than that on the scheelite surface. The weak adsorption of STPP on the scheelite hardly influenced the collection of sodium oleate (NaOL). STPP could complex with Ca2+ on the surface of fluorite and calcite, and hinder the subsequent adsorption of NaOL. The results can provide guiding significance for the flotation of scheelite and the screening of inhibitors for calcium-bearing gangue minerals.
In this study, catalytic wet oxidation technology was used to remove organic substances from Bayer liquid. First, under the optimal conditions without a catalyst (13.98 g/L of O2 addition, oxidation temperature of 220 °C, and oxidation time of 100 min), the removal efficiencies of total organic carbon, sodium humate, and sodium oxalate were 86.59%, 92.96%, and 71.36%, respectively. The mechanism of a free radical chain reaction of wet oxidation removal of organic substances was studied. Then, under the optimal conditions using CuO as a catalyst (13.98 g/L of O2 addition, the catalytic temperature of 250 °, the catalytic time of 100 min, and the catalyst dose of 6% of the ore added mass), the total organic carbon removal efficiency was 98.36%, and sodium humate and sodium oxalate can basically be removed completely. The catalysis of CuO was mainly reflected in two aspects: the copper hydroxyl complex ([Cu(II)(OH) x]2−x) formed by the dissolution of CuO was catalyzed based on the complex reaction mechanism, and the dissolved CuO catalyzed the free radical chain reaction. The catalytic wet oxidation technology exhibited high organic substance removal efficiency, especially for removing sodium oxalate, which could negatively affect the alumina products.
The vacuum electro-osmosis method enables integrated treatment of heavy metal-contaminated sediments by simultaneously removing water and pollutants. This study focuses on the dredged sediments from Tai Lake and investigates the performance of five electrode materials (electrokinetic geo-synthetics, graphite, aluminum, iron, and copper) in the vacuum electro-osmotic treatment process through a self-designed test system. Multiple aspects, including drainage volume, settlement, current, effective potential, pollutant removal efficiency, and energy consumption, were analyzed. The results indicate that using copper as an electrode material has the best dewatering effect but poorer copper pollutant removal efficiency. On the other hand, using electrokinetic geo-synthetics as an electrode material demonstrates the best copper pollutant removal efficiency, with dewatering effect second only to copper, highlighting the superiority of electrokinetic geo-synthetics material in integrated dewatering and remediation treatment. When using metal as an electrode material, the anode electrode corrosion is more severe, which significantly affects various parameters of the vacuum electro-osmotic process and the treatment outcomes. The introduction of vacuum pressure alters the conventional trend of continuous decay in effective potential during the traditional electro-osmotic process. It causes a rebound in effective potential during the later stages of treatment, and the magnitude of this rebound is influenced by the electrode material’s ability to accommodate deformation.
The purpose of this work is to investigate the effect of porosity on free vibration and buckling behaviours of non-uniform cross-section functionally graded porous beams. The material properties are considered varied along the thickness direction while the cross-section is non-uniform along the length of the beam. Three different patterns including symmetric, non-symmetric and uniform have been considered as the porosity distribution. The classical beam theory and Hamilton’s principle are used to derive the governing equations of the problem and the derived formulations are solved using differential quadrature method. The obtained results were validated via both well-known and analytical reported solutions. The optimal discretization setting was determined via mesh independency study. Detailed parametric analyses are presented to get an insight into the effects of different mechanical parameters including porosity coefficient, slenderness ratio and varying cross-section on the fundamental frequency and critical buckling load. The results show that an increase in material porosity leads to a significant reduction in beam buckling capacity. However, the free vibration behaviour of beams completely depends on their porosity pattern. In addition, the symmetric distribution pattern has the best performance in the terms of beam buckling capacity and fundamental frequency.
Crack failures frequently occur in aero-engine blades which can trigger a cascade of accidents. Previous studies have primarily focused on crack-induced nonlinear vibration, and the contact state of the crack surfaces during crack breathing is often neglected. However, it is important to consider the contact behavior of the crack surfaces as it is responsible for generating nonlinear vibrations. To further investigate the mechanism behind crack-induced nonlinear vibrations, a novel dynamic contact breathing crack model (DCBCM) for rotating blades is proposed based on the self-programmed incompatible hexahedral element (SNCHE). The breathing effect is simulated using spring elements. The proposed DCBCM is validated by the contact finite element model. Moreover, the effects of crack parameters (depth and location) and load parameters (aerodynamic amplitude and aerodynamic frequency) on the dynamic contact characteristics are investigated. Furthermore, a breathing crack quantification indicator (BCQI) is proposed to represent the nonlinear level of breathing crack. The results indicate that the crack may close from the sides of the blade toward the center of the crack front during crack breathing. Besides, the BCQI increases with the increase of crack depth, aerodynamic amplitude, and rotational speed; while decreases as the crack moves closer to the blade tip.
Microseismic monitoring is vital for identification and analysis of precursory characteristics of rockmass failure and collapse, which is of great significance for geological hazard early warning and management. By conducting a quantitative analysis of multiple microseismic parameters based on previous insights from laboratory acoustic emission experiments, we investigate the precursory characteristics of large-scale rockmass collapse associated with the large blast in Shizhuyuan Mine on 21 June, 2012. Both the b-value and spatial fractal dimension exhibit a decreasing trend, and the sharp decrease of b-value and the continuous decline of fractal dimension serve as two discernible precursors of rockmass failure. Besides, the variations in the energy index and cumulative apparent volume reflect the dynamics of stress and strain, respectively. The combination of a decrease of energy index against an increase of cumulative apparent volume also indicates the unstable state of rockmass, and this process may repeat before the final rockmass collapse. This case study demonstrates the significance of microseismic monitoring in providing valuable information for early warning and management of rockmass collapse. This work also provides insights for the safety monitoring of various geological engineering activities involving blasting operations.
As mining progresses into deep strata, severe damage occurs at various long-life roadway intersections. To guide targeted repair and reinforcement operations, it is necessary to investigate the failure mechanism of surrounding rock at intersections in deep environments. Four categories and 16 types of intersections of connection type, interleaving type, bifurcation type, and rotary type (ring triangular column) are comprehensively summarized by investigating the maintenance of intersections in many mines. Three types of typical application forms of intersection points are proposed: a single large-scale intersection point, two intersection points for nested combined application, and an intersection point group for ring triangular rock column application. The failure of intersections on site is divided into three levels: local damage to the surrounding rock, damage to the triangular rock column, and overall damage. Three categories of 13 disaster-causing factors of external environmental factors, their structural attributes, and artificial design hidden hazards are proposed from the initiation and cause of the disaster, and the disaster-causing paths of various disaster-causing factors are described in detail. The refined intersection models under three application forms are established, and the secondary development of numerical software is carried out to introduce the distortion energy density index to analyze the energy of the surrounding rock. Studies have shown that the surrounding rock distortion energy peak at intersections is in the triangular rock column, and the increase coefficient is about 2.5. Meanwhile, the distortion energy of the surrounding rock also accumulates at the maximum section, and its increase coefficient is about 1.5. Therefore, it is proposed that the repair of the intersection should focus on the reinforcement of the triangular rock column and surrounding rock at the large cross-section, and a targeted plan is proposed for the repair of the intersections of the deep mine, focusing mainly on the reinforcement of the triangular rock column and the large cross-section. This study provides a reference for the analysis of failure factors, the introduction of numerical simulation indicators, and the repair support of deep intersections.
The excavation of deep underground engineering leads to a gradient stress within surrounding rocks in the radial direction of the tunnel. In this study, we investigated the mechanical response and fracture characteristics of rocks subjected to gradient stress under different axis stresses. During the experimental process, an acoustic emission (AE) system was used to capture the AE signals. The obtained results showed that the influence of axis stress on mechanical response of rock subjected to gradient stress is similar to the test results obtained by classical true triaxial compression tests. When the axis stress is below the critical strength, as the axis stress increases, the characteristic stress increases, resulting in an increase in rock strength. However, once the axis stress exceeds the critical strength, localized failure occurs during the application of the axis stress, leading to a decrease in rock strength. In this case, only part of the cracks coalesces to form oblique macro cracks that do not penetrate the entire rock specimen. The AE signals indicate that the proportion of shear cracks decreases as the axis stress increases. The axis stress significantly suppresses the formation of macro shear cracks resulting from the coalescence of micro tensile cracks.
Contour blasting techniques with pre-cutting areas are deemed as promising methods to improve the contour quality of tunnel with high in-situ stress. However, their performance under different in-situ stresses has not been well studied. In this paper, the performance of two typical contour blasting techniques, i. e., smooth blasting (SB) and pre-splitting blasting (PB) with pre-cutting (PC) areas (namely PCSB and PCPB) under different ground stress conditions is investigated by the road tunnel numerical model after calibration. The results show that under the coupled charge and 50 MPa in-situ stress, PCSB can form a better tunnel contour than PCPB. In addition, the performance of two techniques is investigated with different decoupled charge coefficients and in-situ stresses. It can be found that the contour quality under the PCSB and PCPB both gradually improves with increased in-situ stresses from 30 to 50 MPa. Moreover, adjusting decoupled charge coefficients of peripheral boreholes is feasible for the PCPB to form effective tunnel contour under different in-situ stresses. However, it is more appropriate to adjust decoupled charge coefficients of all boreholes for the PCSB to form eligible tunnel contours under different in-situ stresses. Empirical formulae are finally given to provide design guides of PCSB and PCPB to excavate different in-situ stresses of rock mass used in this paper.
The deterministic method is always adopted for the seismic resistance of loess tunnels. Considering the randomness of ground motions, the seismic fragility assessment of a shallowly buried circular tunnel in the loess region was carried out under pseudo-static conditions with seismic loading in the transversal direction. The displacements calculated by one-dimensional analysis were applied to obtain the seismic responses of the tunnel. Then the maximum damage index was output by a compiled Python program. The optimality of intensity measures was briefly discussed through the testing criteria of correlation, efficiency, practicality, and proficiency. Fragility curves were generated based on the fragility function in terms of peak ground acceleration (PGA) and peak ground velocity (PGV) to evaluate the tunnel’s seismic performance. The results show that the vulnerable parts that shift with different PGAs in conjugate directions are particularly prone to suffering damage. And PGA and PGV are identified as the appropriate indices for predicting the probability of tunnels in various damage states. Void behind the arch dome can increase the fragility of tunnels, and the tunnels embedded in softer sites become more vulnerable to seismic damage.
The construction of China’s high-speed railway (HSR) network has reached earthquake-prone regions, necessitating a timely and accurate post-disaster quick prediction approach to ensure the safety of the HSR systems’ transportation lifeline. This study proposes a fast prediction method utilizing a Bayesian self-optimized bi-directional long short-term memory (Bi-LSTM) network to develop a fast prediction framework for the seismic response of the HSR track-bridge system. It describes a hierarchical clustering algorithm based on discrete wavelet decomposition. The results indicated that the proposed framework effectively predicts the nonlinear seismic response of HSR bridge structures. The model also showed the performance of the work migrate ability and robustness. In addition, the impact of different prediction locations on the HSR track-bridge system is minimal. The hierarchical clustering method based on wavelet decomposition can effectively reduce the number of inputs to the seismic training dataset while ensuring prediction accuracy.
As high-speed railways become increasingly prevalent in urban areas and operating speeds continue to rise, the issue of bridge noise has become a critical concern, giving that bridge sections account for over 80% of high-speed railway noise. As train speeds continue to increase, the number of bridge spans included in a noise prediction model becomes a crucial factor in accurately predicting bridge noise. To address this issue, using a 32-m simply supported box girder, which is commonly used for high-speed trains, as an example, we conducted a comprehensive study using both the Fourier series method and the 3D boundary element method to investigate the impact of bridge span number on highspeed railway bridge noise. Our results indicate that the effect of bridge span number on bridge noise is highly dependent on the location of observation points with respect to the bridge and the distribution of bridge noise. Specifically, when beyond 54 m and part of the near-field area, a minimum of five bridge spans are necessary to obtain a more precise estimation of total bridge noise. This study aids to control bridge noise and can inform the implementation of noise reduction measures of varying lengths at different locations along the bridge.
The aerodynamic load of high-speed trains (HSTs) undergoes significant changes when they pass through the transition section of the cutting under crosswind conditions. This paper establishes a coupled train-cutting-wind three-dimensional aerodynamic model based on the improved delayed detached eddy simulation turbulence model, focusing on the influence of the cutting depth on the change of aerodynamic load and the deterioration of the train’s aerodynamic performance, while also revealing the mechanism of the evolution of the flow field. The results indicate that at the cutting depth of 6 m, the aerodynamic impact energy of the head train during operation is at its highest. As the train completely enters the next operational scenario, with an increase in the cutting depth, the impact of incoming flow on the aerodynamic loads of the train is diminished, leading to a corresponding reduction in fluctuation amplitude. The magnitude of the head train’s abrupt change in aerodynamic load has a near-linear positive correlation with the wind speed.
A high-speed train with wings (HSTW) is a new type of train that enhances aerodynamic lift by adding wings, effectively reducing gravity, to reduce the wear and tear of wheels and rails. This study, based on the RNG k−ε turbulence model and employing a sliding grid method, investigates the aerodynamic effects of HSTWs with different angles of attack when passing through tunnels. The precision of numerical simulation method is validated by data obtained through a moving model test. The results show that the lift of the HSTW increases upon entering the tunnel, with an average lift in the tunnel of 33.3% greater than that in the open air. The angle of attack is reduced from 12.5° to 7.5° when the train enters the tunnel, which can better reduce the lift fluctuations and concurrently also reduce the peak-to-peak pressure on the surface of the train and the tunnel, which is conducive to the train passing through the tunnel smoothly; hence, the angle of attack for the HSTW when passing through a tunnel is adjusted 7.5°. Furthermore, a comparison between the high-speed trains with and without wings demonstrates that the frontal pressure of the trains increases due to the blockage effect caused by the wings, while the rear of the trains experiences decreased pressure, which is primarily influenced by the wing wake. The outcomes of this study provide technical support for HSTWs passing smoothly through tunnels.
In practice, bifurcated railway tunnels are occasionally employed in the construction of long tunnels due to specific geological reasons. However, the aerodynamic behaviors of trains moving through such complex tunnels are not yet fully understood. To address this issue, this study analyzes the aerodynamic interactions produced by a high-speed train moving through a bifurcated tunnel in different directions. A three-dimensional, unsteady, compressible method based on the RNG k-ε turbulence model is used to simulate the train motion in the tunnel. Additionally, the simulation algorithm is validated by comparing the data with full-scale experimental results. The analysis includes the examination of aerodynamic loads and transient pressures on both train surface and tunnel wall. The results indicate that the maximum peak-to-peak pressures on train surface and the the single-track tunnel wall of DTE (double-track tunnel as entry) scenario are larger than that of STE (single-track tunnel as entry). Moreover, for the DTE scenario, the energy consumption of the train moving through the tunnel is significantly higher, and the average drag of the leading vehicle is increased by 19.2% compared with the STE. However, the side force of the leading vehicle for the STE is 26% higher than that of the DTE. The research findings presented in this paper can serve as a valuable aerodynamic reference for the design and construction of specialized tunnels.