In this work, a near-beta Ti-5Al-5Mo-5V-1Cr-1Fe titanium alloy was fabricated by selective laser melting (SLM), and the microstructure evolution together with the mechanical properties was studied. The as-fabricated alloy showed columnar β grains spreading over multiple layers and paralleling to the building direction. The distinct microstructure of as-fabricated alloy was composed of near-β (more than 98.1 %) with a submicron cellular structure. Different SLM processing parameters such as hatch spacing could affect the microstructure of as-fabricated alloy, which could thus further significantly affect the mechanical properties of as-fabricated alloy. In addition, the as-fabricated alloy with the distinct microstructure exhibits yield strength of 818 MPa combined with elongation of more than 19 %, which shows that SLM is a potential technology for manufacturing near-beta titanium components.

The present study reports investigations on rheological, mechanical, thermal, tribological and morphological properties of feedstock filaments prepared with polylactic acid-polyether ketone ketone-hydroxyapatite-chitosan (PLA-PEKK-HAp-CS) composite for 3D printing of functional prototypes. The study consists of a series of melt processing operations on melt flow index (MFI) setup as per ASTM D-1238 for melt flow certainty followed by fixation of reinforcement composition/proportion as 94%PEKK-4%HAp-2%CS (B) by mass in PLA matrix (A). The blending of reinforcement and preparation of feedstock filament for fused deposition modeling (FDM) set up has been performed on commercial twin screw extruder (TSE). The results of study suggest that feedstock filaments prepared with blend of 95%A–5%B (by mass) at 200 °C processing temperature and 100 r/min rotational speed on TSE resulted into better tensile properties (35.9 MPa peak strength and 32.3 MPa break strength) with 6.24% surface porosity, 42.67 nm surface roughness (R_a) and acceptable heat capacity (2.14 J/g). However as regards to tribological behavior, the minimum wear of 316 µmwas observed for sample with poor tensile properties. As regards to crash application for scaffolds the maximum toughness of 1.16 MPa was observed for 85%A–15%B (by mass) at 200 °C processing temperature and 150 r/min rotational speed on TSE.

The electrodeposition of nickel-silicon carbide coatings on a copper electrode was done by mixing SiC particles in the nickel electrodeposition solution. The influence of surfactants and silicon carbide particle size on uniformity and quantity of silicon carbide particles in nickel-silicon carbide composite coatings was investigated. It was found that particle size affects the nucleation overpotential, with 40 nm silicon carbide nanoparticles more effective in promoting nickel nucleation than 500 nm particles due to an increase in active nucleation sites. In terms of surfactants, anionic surfactant sodium dodecyl sulfate (SDS) produced better dispersion of 40 nm silicon carbide particles than cationic surfactant cetyltrimethyl ammonium bromide (CTAB), but little difference was found between the two when 500 nm silicon carbide particles were used. Thus, although the suspension of silicon carbide particles can be improved and their co-deposition can be promoted with a cationic surfactant CTAB, it is less effective than an anionic surfactant SDS in terms of surface finish.

In this study, ceramics was prepared by slip casting (no pressure was used during shaping step) and atmospheric pressure sintering with low-melting point glass (LPG) powder as the binding material to facilitate the transformation of spodumene flotation tailings (SFTs) into ceramics at lower temperatures. The influence of sintering temperature and mass ratio of LPG on the mechanical properties (flexural strength and compressive strength) of ceramic materials was studied by orthogonal test. The results showed that when the mass ratio of LPG powder was higher than or equal to 20 wt% and the sintering temperature was higher than or equal to 550 °C, mutual adhesion between the sample particles was realised and consequently the ceramic materials could be prepared with good mechanical properties (the maximum flexural strength=19.55 MPa, the maximum compressive strength=42.25 MPa, average porosity=24.52%, average apparent density=1.66 g/cm³, and average water absorption=14.79%). The sintered ceramics were characterized by XRF, XRD, optical microscopy analysis, SEM, TGA-DSC and FT-IR. The formation of liquid phase at high temperature may lead to the mutual bonding between particles, which might be the main reason for the improvement of mechanical properties of ceramic materials. Overall, SFTs were successfully sintered at low temperature to prepare ceramic materials with good mechanical properties, which are crucial for energy conservation and environmental preservation.

Chitosan-coated fly ash (CWF) was prepared by the acid leaching-coating method. Chitosan and fly ash were crosslinked in the solution of acetic acid and sulfuric acid. The microstructure of CWF was conducted by scanning electron microscope (SEM) and X-ray diffraction (XRD). The removal of Cr(VI) from water by CWF was studied by adsorption experiments. The composite prepared by the experiment developed a pore structure and a crystal structure similar to SiO₂ and chitosan chain-like coating was formed on the surface of fly ash. The new modified material has larger surface roughness, specific surface area and more adsorption channels. The Cr(VI) was enriched in modified materials by electrostatic adsorption between CrO₄²⁻, CrO₇²⁻ and —NH₃⁺ group and surface acid functional groups. The movement of Cr(VI) in solution is a diffusion process from the main body of the liquid phase to the surface of the liquid film.

To understand the effect of steam curing temperature on the hydrate and microstructure of hardened cement paste, several measuring methods including X-ray diffraction (XRD), atomic absorption spectroscopy (ASS), ion chromatography, conductivity meter, alternating-current impedance spectroscopy and nuclear magnetic resonance (NMR) are employed to investigate the hydration characteristics, pore solution composition and conductivity, resistivity and pore structure during the steam curing process. Experimental results show that steam curing promotes the hydration process, greatly raises the resistivity, and decreases the porosity of specimen at early age. Compared with being treated at 45 °C, higher temperature leads to a fast decomposition of ettringite at initial stage of the constant temperature treatment period, which improves the relative content and ionic activity of the conductive ions in pore solution. Furthermore, the number of pores larger than 200 nm increases significantly, which reduces the resistivity of the hardened cement paste. Cement paste treated at 45 °C has a more stable and denser microstructure with less damages.

Efficient modelling approaches capable of predicting the behavior and effects of nanoparticles in cement-based materials are required for conducting relevant experiments. From the microstructural characterization of a cement-nanoparticle system, this paper investigates the potential of cell-based weighted random-walk method to establish statistically significant relationships between chemical bonding and diffusion processes of nanoparticles within cement matrix. LaSr_0.5C_0.5O₃ (LSCO) nanoparticles were employed to develop a discrete event system that accounts for the behavior of individual cells where nanoparticles and cement components were expected to interact. The stochastic model is based on annihilation (loss) and creation (gain) of a bond in the cell. The model considers both chemical reactions and transport mechanism of nanoparticles from cementitious cells, along with cement hydration process. This approach may be useful for simulating nanoparticle transport in complex 2D cement-based materials systems.

For deep purification of As(V) from drinking water by adsorption, two adsorbents S-FeOOH and S-MnO₂ were successfully synthesized by loading FeOOH and MnO₂ nanoparticles onto silica gel in situ. Characterization of the adsorbents implied that S-FeOOH and S-MnO₂ with large particle size (diameter of 150–250 µm) still had high specific surface areas (357.0 and 334.6 m²/g) due to their specific amorphous and porous structure. In batch experiments, the influences of pH, contact time, adsorbent dosage, and temperature on the adsorption were investigated. Comparing with other adsorbents reported, the synthesized adsorbents in this study, especially S-FeOOH, showed good performance for As(V) removal in a wide pH (2–12) and temperature (25–65 °C) range. The residual As(V) concentration after S-FeOOH treatment was around 0.01 mg/L, which met the drinking water standard. The adsorption process followed the pseudo-second-order kinetic model, and the adsorption equilibrium was reached within 5 min. The equilibrium adsorption data of S-FeOOH can be well fitted by the Langmuir isotherm, while that of S-MnO₂ followed Freundlich model, which indicated their different adsorption mechanisms. The results show that S-FeOOH is superior to S-MnO₂ in eliminating As(V), and S-FeOOH could be used as a promising adsorbent for the deep purification of As(V) in drinking water.

In this study, different influence mechanisms associated with temperatures and pH values were investigated through cemented paste backfill (CPB) systems. CPB samples were prepared with temperatures ranging from 10 to 50 °C in 10 °C increments and pH values of 3, 7, and 13. Then, the CPB mixture were subjected to rheological tests, thermogravimetric analysis (TG), derivative thermogravimetry analysis (DTG), Fourier-transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Results demonstrated that the temperatures had significant effects on the rheological properties of CPB, whereas the effects of pH values were relatively unapparent. Higher temperatures (over 20 °C) were prone to bring higher shear stress, yield stress, and apparent viscosity with the same pH value condition. However, an overly high temperature (50 °C) cannot raise the apparent viscosity. Non-neutral conditions, for pH values of 3 and 13, could strengthen the shear stress and apparent viscosity at the same temperature. Two different yield stress curves could be discovered by uprising pH values, which also led to apparent viscosity of two various curves under the same temperatures (under 50 °C). Microscopically, rheological properties of CPB were affected by temperatures and pH values which enhanced or reduced the cement hydration procedures, rates, products and space structures.

Residual coal pillars play an important role in mining the adjacent coal seam safely, managing the gobs and maintaining the stability of abandoned coal mines. The height to diameter ratio (H/D) affects the stability of residual coal pillars. In this study, uniaxial compressive tests of coal specimens with five H/D (2.0, 1.5, 1.0, 0.8 and 0.6) were performed, and the stress, strain and acoustic emission (AE) were monitored. Results show that the uniaxial compressive strength (UCS) and peak strain increase with H/D decreasing. An empirical equation is proposed to calculate the UCS based on the H/D. The AE activities during coal failure process can be separated into four periods. The span of quiet period and rapid decline period shorten with H/D decreasing. The smaller the H/D is, the more complicated the failure characteristics of coal will be. The failure form of coal with H/D of 2.0, 1.5, and 1.0 is primarily shear failure, while splitting failure along the axial direction is the mainly mode when H/D is 0.8 or 0.6. The initiation, expansion, aggregation and connection of micro-cracks can be reflected by the real-time spatial evolution of AE event points.

To analyze wheel wear discrepancy between motor car and trailer of an intercity train, a novel wheel wear rates calculation model was proposed, which was composed of the intercity train dynamics model, wheel-rail three-dimensional rolling contact FEM model and the wear model. The simulated results were contrasted with measured results in field test. The simulated results showed the motor car wheels had larger rotation rate and longitudinal creepage than the trailer wheels. Meanwhile, the motor car wheels encountered larger vertical forces and longitudinal forces from bogie because of the heavier car body and the impact of traction torque. The traction torque acting on motor car wheel could increase the slip rates in the rear part of wheel contact patch and weaken the spinning phenomenon of relative slip. Larger contact pressure and slip rates caused the higher wear rates of motor car wheel than those of trailer wheel. The overall trends of wheel wear depth in simulated and tested results were similar. And they both showed the motor car wheel encountered the more serious wear than the trailer wheel. These models can be used to study the effect of the traction characteristics curves on the wear of wheel.

In machine learning, randomness is a crucial factor in the success of ensemble learning, and it can be injected into tree-based ensembles by rotating the feature space. However, it is a common practice to rotate the feature space randomly. Thus, a large number of trees are required to ensure the performance of the ensemble model. This random rotation method is theoretically feasible, but it requires massive computing resources, potentially restricting its applications. A multimodal genetic algorithm based rotation forest (MGARF) algorithm is proposed in this paper to solve this problem. It is a tree-based ensemble learning algorithm for classification, taking advantage of the characteristic of trees to inject randomness by feature rotation. However, this algorithm attempts to select a subset of more diverse and accurate base learners using the multimodal optimization method. The classification accuracy of the proposed MGARF algorithm was evaluated by comparing it with the original random forest and random rotation ensemble methods on 23 UCI classification datasets. Experimental results show that the MGARF method outperforms the other methods, and the number of base learners in MGARF models is much fewer.

Semantic segmentation is a crucial step for document understanding. In this paper, an NVIDIA Jetson Nano-based platform is applied for implementing semantic segmentation for teaching artificial intelligence concepts and programming. To extract semantic structures from document images, we present an end-to-end dilated convolution network architecture. Dilated convolutions have well-known advantages for extracting multi-scale context information without losing spatial resolution. Our model utilizes dilated convolutions with residual network to represent the image features and predicting pixel labels. The convolution part works as feature extractor to obtain multidimensional and hierarchical image features. The consecutive deconvolution is used for producing full resolution segmentation prediction. The probability of each pixel decides its predefined semantic class label. To understand segmentation granularity, we compare performances at three different levels. From fine grained class to coarse class levels, the proposed dilated convolution network architecture is evaluated on three document datasets. The experimental results have shown that both semantic data distribution imbalance and network depth are import factors that influence the document’s semantic segmentation performances. The research is aimed at offering an education resource for teaching artificial intelligence concepts and techniques.

As the demand for bike-sharing has been increasing, the oversupply problem of bike-sharing has occurred, which leads to the waste of resources and disturbance of the urban environment. In order to regulate the supply volume of bike-sharing reasonably, an estimating model was proposed to quantify the urban carrying capacity (UCC) for bike-sharing through the demand data. In this way, the maximum supply volume of bike-sharing that a city can accommodate can be obtained. The UCC on bike-sharing is reflected in the road network carrying capacity (RNCC) and parking facilities’ carrying capacity (PFCC). The space-time consumption method and density-based spatial clustering of application with noise (DBSCAN) algorithm were used to explore the RNCC and PFCC for bike-sharing. Combined with the users’ demand, the urban load ratio on bike-sharing can be evaluated to judge whether the UCC can meet users’ demand, so that the supply volume of bike-sharing and distribution of the related facilities can be adjusted accordingly. The application of the model was carried out by estimating the UCC and load ratio of each traffic analysis zone in Nanjing, China. Compared with the field survey data, the effect of the proposed algorithm was verified.

As the critical equipment, large axial-flow fan (LAF) is used widely in highway tunnels for ventilating. Note that any malfunction of LAF can cause severe consequences for traffic. Specifically, fault deterioration is suppressed tremendously when an abnormal state is detected in the stage of early fault. Thus, the monitoring of the early fault characteristics is very difficult because of the low signal amplitude and system disturbance (or noise). In order to overcome this problem, a novel early fault judgment method to predict the operation trend is proposed in this paper. The vibration-electric information fusion, the support vector machine (SVM) with particle swarm optimization (PSO), and the cross-validation (CV) for predicting LAF operation states are proposed and discussed. Finally, the results of the experimental study verify that the performance of the proposed method is superior to that of the contrast models.

Prticle swarm optimization (PSO) is adopted to invert the self-potential anomalies of simple geometry. Taking the vertical semi-infinite cylinder model as an example, the model parameters are first inverted using standard particle swarm optimization (SPSO), and then the searching behavior of the particle swarm is discussed and the change of the particles’ distribution during the iteration process is studied. The existence of different particle behaviors enables the particle swarm to explore the searching space more comprehensively, thus PSO achieves remarkable results in the inversion of SP anomalies. Finally, six improved PSOs aiming at improving the inversion accuracy and the convergence speed by changing the update of particle positions, inertia weights and learning factors are introduced for the inversion of the cylinder model, and the effectiveness of these algorithms is verified by numerical experiments. The inversion results show that these improved PSOs successfully give the model parameters which are very close to the theoretical value, and simultaneously provide guidance when determining which strategy is suitable for the inversion of the regular polarized bodies and similar geophysical problems.

A filter algorithm based on cochlear mechanics and neuron filter mechanism is proposed from the view point of vibration. It helps to solve the problem that the non-linear amplification is rarely considered in studying the auditory filters. A cochlear mechanical transduction model is built to illustrate the audio signals processing procedure in cochlea, and then the neuron filter mechanism is modeled to indirectly obtain the outputs with the cochlear properties of frequency tuning and non-linear amplification. The mathematic description of the proposed algorithm is derived by the two models. The parameter space, the parameter selection rules and the error correction of the proposed algorithm are discussed. The unit impulse responses in the time domain and the frequency domain are simulated and compared to probe into the characteristics of the proposed algorithm. Then a 24-channel filter bank is built based on the proposed algorithm and applied to the enhancements of the audio signals. The experiments and comparisons verify that, the proposed algorithm can effectively divide the audio signals into different frequencies, significantly enhance the high frequency parts, and provide positive impacts on the performance of speech enhancement in different noise environments, especially for the babble noise and the volvo noise.

As a new kind of air-hardening soil reinforcement material, polymer is being widely applied in river-bank slope reinforcement and ecological slope protection area. Thus, more attention should be paid to study the characteristics of reinforced soil after immersion. In this study, water-induced changes in strength characteristics of sand reinforced with polymer and fibers were reported. Several factors, including polymer content (1%, 2%, 3% and 4% by weight of dry sand), immersion time (6, 12, 24 and 48 h), dry density (1.40, 1.45, 1.50, 1.55 and 1.60 g/cm³,) and fiber content (0.2%, 0.4%, 0.6% and 0.8% by weight of dry sand) which may influence the strength characteristics of reinforced sand after immersion were analyzed. The microstructure of reinforced sand was analyzed with nuclear magnetic resonance (NMR) and scanning electron microscope (SEM). Experimental results indicate that the compressive strength increases with the increase of polymer content and decreases with the increase of immersion time; the softening coefficients decrease with the increase of the polymer content and immersion time and increase with an increment in density and fiber content. Fiber plays an active role in reducing water-induced loss of strength at 0.6% content.

Acoustic Emission (AE) waveforms contain information on microscopic structural features that can be related with damage of coal rock masses. In this paper, the Hilbert-Huang transform (HHT) method is used to obtain detailed structural characteristics of coal rock masses associated with damage, at different loading stages, from the analyses of the characteristics of AE waveforms. The results show that the HHT method can be used to decompose the target waveform into multiple intrinsic mode function (IMF) components, with the energy mainly concentrated in the C₁–C₄ IMF components, where the C₁ component has the highest frequency and the largest amount of energy. As the loading continues, the proportion of energy occupied by the low-frequency IMF component shows an increasing trend. In the initial compaction stage, the Hilbert marginal spectrum is mainly concentrated in the low frequency range of 0–40 kHz. The plastic deformation stage is associated to energy accumulation in the frequency range of 0–25 kHz and 200–350 kHz, while the instability damage stage is mainly concentrated in the frequency range of 0–25 kHz. At 20 kHz, the instability damage reaches its maximum value. There is a relatively clear instantaneous energy peak at each stage, albeit being more distinct at the beginning and at the end of the compaction phase. Since the effective duration of the waveform is short, its resulting energy is small, and so there is a relatively high value from the instantaneous energy peak. The waveform lasts a relatively long time after the peak that coincides with failure, which is the period where the waveform reaches its maximum energy level. The Hilbert three-dimensional energy spectrum is generally zero in the region where the real energy is zero. In addition, its energy spectrum is intermittent rather than continuous. It is therefore consistent with the characteristics of the several dynamic ranges mentioned above, and it indicates more clearly the low-frequency energy concentration in the critical stage of instability failure. This study well reflects the response law of geophysical signals in the process of coal rock instability and failure, providing a basis for monitoring coal rock dynamic disasters.

The object of this article is to investigate the energy evolution mechanism and failure criteria of cross-jointed samples containing an opening during deformation and failure based on the uniaxial compression test and rock energy principle. The results show that the energy evolution characteristics of the samples correspond to a typical progressive damage mode. The peak total energy, peak elastic energy, and total input energy of the samples all first decrease and then increase with an increase of half of the included angle, reaching their minimum values when this angle is 45°, while the dissipated energy generally increases with this angle. The existence of the opening and cross joints can obviously weaken the energy storage capacity of the rock, and the change in the included angle of the cross joint has a great influence on the elastic energy ratio of the sample before the peak stress, which leads to some differences in the distribution laws of the input energy. The continuous change and the subsequent sharp change in the rate of change in the energy consumption ratio can be used as the criteria of the crack initiation and propagation and the unstable failure of the sample, respectively.

Rock blocks sliding along discontinuities can cause serious disasters, such as landslides, earthquakes, or rock bursts. The shear rate-dependent behavior is a typical time-dependent behavior of a rock discontinuity, and it is closely related to the stability of a rock block. To further study the shear rate-dependent behavior of rock discontinuities, shear tests with alternating shear rates (SASRs) were conducted on rock discontinuities with various surface morphologies. The dynamic evolution of the shear rate dependency was studied in detail based on the shear test results, and three stages were identified with respect to the shear stress and shear deformation states. The test results revealed that dynamic changes in shear stiffness and the energy storage abilities of the rock discontinuities occurred in relation to the shear rate-dependent behavior of crack growth, which increased with an increase in normal stress and/or the joint roughness coefficient. The stage of decreasing shear stiffness corresponded to a stage of noticeable shear rate-dependency, and the shear rate was found to have no influence on the initial crack stress.

The excavation of foundation pit generates soil deformation around existing metro tunnel with shield driving method, which may lead to the deformation of tunnel lining. It is a challenge to evaluate the deformation of shield tunnel accurately and take measures to reduce the tunnel upward displacement as much as possible for geotechnical engineers. A new simplified analytical method is proposed to predict the longitudinal deformation of existing metro tunnel due to excavation unloading of adjacent foundation pit in this paper. Firstly, the additional stress of soils under vertical axisymmetric load in layered soil is obtained by using elastic multi-layer theory. Secondly, the metro tunnel is regarded as a Timoshenko beam supported by Winkler foundation so that the shear effect of tunnels can be taken into account. The additional stress acting on the tunnel due to excavation unloading in layered soil are compared with that in homogeneous soil. Additionally, the effectiveness of the analytical solution is verified via two actual cases. Moreover, parametric analysis is conducted to investigate the responses of the metro tunnel by considering such factors as the variation of subgrade coefficient, offset distance from the excavation center to tunnel longitudinal axis as well as equivalent shear stiffness. The proposed method can be used to provide theoretical basis for similar engineering project.

Iron-modified biochar (FeOS) is known to be effective at immobilization of arsenic (As) in soils. A pot experiment was conducted to investigate the effects of FeOS on As availability and ttransportation in the soil-rice system at different growth stages of rice with different pollution levels. The results showed that Fe concentration decreased and As concentration increased in paddy soils with the FeOS addition, especially in 120 mg/kg As treatment, the As concentration decreased by 16.46% and 30.56% at the maturity stage with 0.5% and 1% FeOS additions, respectively. Compared with the control, the application of FeOS reduced the arsenic content in rice tissues and increased the biomass, with the root biomass increased by 12.68% and the shoot biomass was increased by 8.94% with the addition of 1% FeOS. This may be related to the promotion of iron plaque formation and the transformation of microbial community structure in FeOS treatments, in accordance with the result of gene abundance and Fe/As contents of iron plaque in the study. This study is expected to provide further support and theoretical basis for the application of FeOS in the remediation of As contaminated paddy soil.