The role of polyurethane foam compressible layer in the mechanical behaviour of multi-layer yielding supports for deep soft rock tunnels

The polyurethane foam(PU)compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels.Nevertheless,the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated.To fill this gap,large-scale model tests were conducted in this study.The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method.Two types of multi-layer yielding supports with different thicknesses(2.5 cm,3.75 cm and 5 cm)of PU compressible layers were investigated respectively.Digital image correlation(DIC)analysis and acoustic emission(AE)techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time.Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation,crack propagation,strain-hardening,and failure stages.Compared with those of the stiff support,the toughness,deformability and ultimate load of the yielding supports were increased by an average of 225%,61%and 32%,respectively.Additionally,the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties.The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports.The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels.

Responses of calcareous sand foundations to variations of groundwater table and applied loads

The long-term settlement of calcareous sand foundations caused by daily periodic fluctuations has become a significant geological hazard,but effective monitoring tools to capture the deformation profiles are still rarely reported.In this study,a laboratory model test and an in situ monitoring test were conducted.An optical frequency domain reflectometer(OFDR)with high spatial resolution(1 mm)and high accuracy(10-6)was used to record the soil strain responses to groundwater table and varied loads.The results indicated that the fiber-optic measurements can accurately locate the swelling and compressive zones.During the loading process,the interlock between calcareous sand particles was detected,which increased the internal friction angle of soil.The foundation deformation above the sliding surface was dominated by compression,and the soil was continuously compressed beneath the sliding surface.After 26e48 h,calcareous sand swelling occurred gradually above the water table,which was primarily dependent on capillary water.The swelling of the soil beneath the groundwater table was completed rapidly within less than 2 h.When the groundwater table and load remain constant,the compression creep behavior can be described by the Yasong-Wang model with R2¼0.993.The daily periodically varying in situ deformation of calcareous sand primarily occurs between the highest and lowest groundwater tables,i.e.4.2e6.2 m deep.The tuff interlayers with poor water absorption capacity do not swell or compress,but they produce compressive strain under the influence of deformed calcareous sand layers.

Effect of inclusions on the formation of acicular ferrite in Ti-bearing non quenched-and-tempered steel

Nucleation of acicular ferrite and its influence factors in non quenched-and-tempered steel was studied by using TEM and thermodynamic calculation. The results show that the complex particles with a center made of Ti oxide, Al2O3, and silicate and an outside made of a small quantity of mixture of TiN and MnS are able to act as ferrite nucleation nuclei. The acicular ferrite percentage changes little with Ti. When the oxygen content was 80 ppm, the volume percentage of acicular ferrite decreased due to an increase in allotriomorphic ferrite. The larger the cooling rate and the shorter the incubation time, the finer the titanium oxide and the higher the nucleation ratio of acicular ferrite.

Intelligent Detection Model Based on a Fully Convolutional Neural Network for Pavement Cracks

The crack is a common pavement failure problem.A lack of periodic maintenance will result in extending the cracks and damage the pavement,which will affect the normal use of the road.Therefore,it is significant to establish an efficient intelligent identification model for pavement cracks.The neural network is a method of simulating animal nervous systems using gradient descent to predict results by learning a weight matrix.It has been widely used in geotechnical engineering,computer vision,medicine,and other fields.However,there are three major problems in the application of neural networks to crack identification.There are too few layers,extracted crack features are not complete,and the method lacks the efficiency to calculate the whole picture.In this study,a fully convolutional neural network based on ResNet-101 is used to establish an intelligent identification model of pavement crack regions.This method,using a convolutional layer instead of a fully connected layer,realizes full convolution and accelerates calculation.The region proposals come from the feature map at the end of the base network,which avoids multiple computations of the same picture.Online hard example mining and data-augmentation techniques are adopted to improve the model’s recognition accuracy.We trained and tested Concrete Crack Images for Classification(CCIC),which is a public dataset collected using smartphones,and the Crack Image Database(CIDB),which was automatically collected using vehicle-mounted charge-coupled device cameras,with identification accuracy reaching 91.4%and 86.4%,respectively.The proposed model has a higher recognition accuracy and recall rate than Faster RCNN and different depth models,and can extract more complete and accurate crack features in CIDB.We also analyzed translation processing,fuzzy,scaling,and distorted images.The proposed model shows a strong robustness and stability,and can automatically identify image cracks of different forms.It has broad application prospects in practical engineering problems.

Dynamic Response Solution of Multi-Layered Pavement Structure Under FWD Load Appling the Precise Integration Algorithm

The pavement layered structures are composed of surface layer,road base and multi-layered soil foundation.They can be undermined over time by repeated vehicle loads.In this study,a hybrid numerical method which can evaluate the displacement responses of pavement structures under dynamic falling weight deflectometer(FWD)loads.The proposed method consists of two parts:(a)the dynamic stiffness matrices of the points at the surface in the frequency domain which is based on the domain-transformation and dual vector form equation,and(b)interpolates the dynamic stiffness matrices by a continues rational function of frequency.The mixed variables formulation(MVF)can treat multiple degree of freedom systems with considering the coupling term between degree of freedoms.The accuracy of the developed method has been demonstrated by comparison between the proposed method and published results from the other method.Then the proposed method can be applied as a forward calculation technique to emulate the falling weight deflectometer test for multi-layered pavement structures.

Equilibrium Precipitation of Niobium Carbonitride in Austenite

The equilibrium between niobium carbonitride and austenite has been studied. Experimentally, X-raydiffaction technique was adopted to verify that the precipitates have the same composition and structure. Theoretical-ly, Hillert and Staffansson's regular model about stoichimetric phase was used to describe the thermodynamic proper-ties of multi-component precipitate. Calculated results agree well with experimental values from literatures.

GPR Wave Propagation Model in a Complex Geoelectric Structure Using Conformal First-Order Symplectic Euler Algorithm

Possessing advantages such as high computing efficiency and ease of programming,the Symplectic Euler algorithm can be applied to construct a groundpenetrating radar(GPR)wave propagation numerical model for complex geoelectric structures.However,the Symplectic Euler algorithm is still a difference algorithm,and for a complicated boundary,ladder grids are needed to perform an approximation process,which results in a certain amount of error.Further,grids that are too dense will seriously decrease computing efficiency.This paper proposes a conformal Symplectic Euler algorithm based on the conformal grid technique,amends the electric/magnetic fieldupdating equations of the Symplectic Euler algorithm by introducing the effective dielectric constant and effective permeability coefficient,and reduces the computing error caused by the ladder approximation of rectangular grids.Moreover,three surface boundary models(the underground circular void model,the undulating stratum model,and actual measurement model)are introduced.By comparing reflection waveforms simulated by the traditional Symplectic Euler algorithm,the conformal Symplectic Euler algorithm and the conformal finite difference time domain(CFDTD),the conformal Symplectic Euler algorithm achieves almost the same level of accuracy as the CFDTD method,but the conformal Symplectic Euler algorithm improves the computational efficiency compared with the CFDTD method dramatically.When the dielectric constants of the two materials vary greatly,the conformal Symplectic Euler algorithm can reduce the pseudo-waves almost by 80% compared with the traditional Symplectic Euler algorithm on average.

Current Efficiency of Low Temperature Aluminum Electrolysis Studied by Neural Network

A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neural network principles. The nonlinearmapping between CE of LATE and various electrolytic conditions was obtained from a number of experimental data and used to predictCE of LATE. The trsined neural networks possessed high precision and resulted in a good predicting effect. As a result, attificial neuralnetworks as a new cooperating and predicting technology provide a new approach to the further studies on low temperature aluminumelectrolysis.

Static Softening Behaviour of Hot-worked Austenite in Microalloyed Structural Steel StE460

Double-hit compression tests were performed on StE460 steel containing microalloying elements niobium and vanadium over a range of temperatures and strain rates penment to hot rolling. The fractional softening was evaluated by use of the offset method, which was confirmed to be a very reasonable method. Appropriate expressions are given for the static recrystallization kinetics as a function of temperature and strain rate. Particular attention is paid to the effect of strain rate on static recrystallization. It can be shown that the static softening is apparently accelerated by strain rate. Recrystallization in low temperature austenitic region is stopped due to precipitation of carbonitrides of microalloying elements, which is reflected in the form of a plateau in the curves of static softening.

Mechanical Properties and Erosive Wear Resistance of Zirconia Toughened Al_2O_3-TiC Ceramics

The effect of ZrO2, content on the fracture toughness, flexural strength and Vickers hardness as well as the erosive wear resistan properties of zirconia toughened Al2O3-TiC ceramic composites has been investigated. The results showed that the improvement in fracture toughness and flexure strength of composites with the content of zirconia less than 50% and 10% in mass fraction respectively,is primarily attributed to stress-induced transformation toughening by the analyse of X-ray diffraction. The dependance of erosion wear resistance on the attak angle and the content of ZrO2, panicles of the composites was also revealed. It is found that the erosion rate of the composites has a sharp rise at a attack angle over 65°. This phenomenon is due to a brittle response to the erosion test by microsmictural observation on eroded surface.

Effect of pH Value on Stress Corrosion Cracking of X70 Pipeline Steel in Acidic Soil Environment

The effect of pH value on the stress corrosion cracking （SCC） of API XT0 pipeline steel in simulated acidic soil solutions was investigated by using slow strain rate test, electrochemical polarization curves, electrochemical impedance spectroscopy, and scanning electron microscopy, pH plays an important role in the susceptibility and electrochemical mechanism of SCC. The pH higher than 5 has no significant effect on electrochemical processes. By contrast, the pH lower than 5 intensifies cathodic hydrogen evolution reactions, thus increasing the cathodic current and corrosion potential. Under different pH values, the SCC mechanism of XT0 pipeline steel varies among anodic dissolution （AD）, hydrogen embrittlement （HE）, and the combination of AD and HE （AD ＋ HE） with variations of applied potential. At -850 mVscE, the SCC mechanism is HE if pH is less than 4 or AD 4- HE if pH value is more positive.

Existence form of lathanum and its improving mechanism of visible-light-driven La-F co-doped TiO2

The existence form and effect of La on the phase composition,morphology,recombination of photocarriers,and optical absorptivity of La-F codoped TiO2 were investigated.Experimental results indicate that all the phase composition of samples is anatase TiO2,the grain sizes decrease with the increasing of La content The catalysts have a well-defined spherical structure with an average size of 12-14 nm,and the doping elements are uniformly dispersed.Compared with pure TiO2,the absorption edge of La1.5F5-TiO2 red shifts from 388 to 437 nm,accordingly the energy gap(Eg) reduces from 32 to 2.84 eV,Besides,the recombination rate of electron-holes in La1.5F5-TiO2 is the weakest among the prepared samples,and the specific surface area of La1.5F5-TiO2 reaches 105.27 m2/g.The apparent reaction rate constant k of La1.5F5-TiO2 for methylene blue(MB) degradation under visible light obtained from the apparent first-order model achieves 0.0166±0.52 min-1,which is greater than 0.0033±0.09 min 1 of TiO2.Moreover,high-resolution transmission electron microscopy(HRTEM) observation reveals that there coexist La2O3 particles in the co-doped TiO2.

Less is more: a new machine-learning methodology for spatiotemporal systems

Machine learning provides a way to use only portions of the variables of a spatiotemporal system to predict its subsequent evolution and consequently avoids the curse of dimensionality.The learning machines employed for this purpose,in essence,are time-delayed recurrent neural networks with multiple input neurons and multiple output neurons.We show in this paper that such kinds of learning machines have a poor generalization ability to variables that have not been trained with.We then present a one-dimensional time-delayed recurrent neural network for the same aim of model-free prediction.It can be trained on different spatial variables in the training stage but initiated by the time series of only one spatial variable,and consequently possess an excellent generalization ability to new variables that have not been trained on.This network presents a new methodology to achieve finegrained predictions from a learning machine trained on coarse-grained data,and thus provides a new strategy for certain applications such as weather forecasting.Numerical verifications are performed on the Kuramoto coupled oscillators and the Barrio-Varea-Aragon-Maini model.

An approach of dynamic response analysis of nonlinear structures based on least square Volterra kernel function identification

Analysis of the dynamic response of a complex nonlinear system is always a difficult problem.By using Volterra functional series to describe a nonlinear system,its response analysis can be similar to using Fourier/Laplace transform and linear transfer function method to analyse a linear system’s response.In this paper,a dynamic response analysis method for nonlinear systems based on Volterra series is developed.Firstly,the recursive formula of the least square method is established to solve the Volterra kernel function vector,and the corresponding MATLAB programme is compiled.Then,the Volterra kernel vector corresponding to the nonlinear response of a structure under seismic excitation is identified,and the accuracy and applicability of using the kernel vector to predict the response of a nonlinear structure are analysed.The results show that the Volterra kernel function identified by the derived recursive formula can accurately describe the nonlinear response characteristics of a structure under an excitation.For a general nonlinear system,the first three order Volterra kernel function can relatively accurately express its nonlinear response characteristics.In addition,the obtained Volterra kernel function can be used to accurately predict the nonlinear response of a structure under the similar type of dynamic load.