In the development of underground space in coastal urban areas,artificial freezing is commonly used to reinforce soft soils to ensure engineering safety.However,the freeze-thaw deformation induced by the method can threaten the stability of surrounding buildings and structures.In practice,cement is used for improvement before freezing to enhance soil strength and limit deformation.However,after freeze-thaw cycles,the properties of cemented-soil degrade to some extent,and long-term loading may induce creep,leading to potential failures.Therefore,it is crucial to investigate the creep characteristics and microstructural evolution mechanisms of freeze-thaw cemented-soil.This study focuses on soft clay from Shanghai and em-ploys low field-nuclear magnetic resonance(LF-NMR)and scanning electron microscope(SEM)to investigate the influence pattern of freezing temperature and cement reinforcement on the creep characteristics of freeze-thaw cemented-soil.The re-sults indicate that,after creep,the pore volume of the unfrozen samples increases from 24.5%to 28.5%,and the particle size decreases.After freeze-thaw at-25℃,structural damage intensifies,with pore volume reaching 39.1%and particle size re-ducing to 4.50 μm,confirming that low temperature causes particle fragmentation.Freeze-thaw cycle causes a shift in the NMR T2 spectrum of samples from a single peak to a double peak.Creep facilitates the conversion of large pores to small pores,resulting in a decrease in the average pore diameter but an increase in the total number of pores,which leads to an over-all rise in porosity.This study explains the mechanism by which freeze-thaw cycle causes microstructural damage of cemented-soil and consequently changes macroscopic creep,providing a theoretical basis for the long-term stability of engi-neering projects.
Weighted signed directed graphs have attracted widespread attention for their ability to model interactions in com-plex systems via signed,directed and weighted edges.Applying Laplacian-based spectral graph convolution methods to such graphs is of great value,as these methods are both concise and interpretable.However,such applications face three major challenges:the Laplacian matrix tends to lose positive semi-definiteness,spectral decomposability and eigenvalue bounded-ness,thus limiting its scope of application;model performance is sensitive to the number of edges and weight distribution of datasets,leading to poor stability;and the computational cost is high with limited efficiency.To address these issues,this pa-per proposes a novel magnetic signed Laplacian matrix and designs a Weighted Signed Directed Graph Convolutional Net-work(WSDGCN)based on this matrix.Theoretical derivation demonstrates that this matrix preserves the core superior prop-erties of the Laplacian matrix when adapted to weighted signed directed graphs.While achieving differentiated topological characterization,it exhibits favorable robustness to edge weights.Experiments on node classification and link prediction tasks conducted on both synthetic and real-world datasets verify that the proposed method achieves superior performance compared with other competing methods.
With the increasing application of energy storage technology in microgrids,the stability of energy storage conver-ters plays a critical role in the system's performance.This paper proposes a hybrid automaton model for the Cuk topology ene-rgy storage converter,which unifies the system's discrete and continuous states.Nonlinear analysis methods are employed to quantitatively analyze the dynamic behavior of the system under variations of key parameters.In buck mode,a Thevenin equivalent circuit model for the battery is introduced,incorporating the battery's polarization effect into the system descrip-tion,to analyze its influence on the system's stability boundaries and bifurcation behavior.In boost mode,a multi-scale dy-namic model is established by introducing parametric and external excitation,and the oscillatory behavior under three typical excitation frequency ratios is analyzed using the fast-slow dynamic analysis method.The results show that as the excitation frequency ratio changes,the structure of the system's slow variables is altered,leading to the evolution of bursting oscillations from symmetric periodic bursting to asymmetric or multi-segment bursting forms.This study reveals the variation in the system's dy-namic response when parameters change,providing significant insights into the operational characteristics of the converter.
In this study, the phase stability of martensite in the heat-affected zone of 17-4PH stainless steel during laser cladding is investigated through a combination of phase field simulation, finite element analysis, and phase transformation experiments. Based on the JMAK model and experimental data, the evolution of secondary phases during the high-temperature stage of the cooling process in laser cladding is analyzed. The effects of this evolution on the matrix chemical composition and yield strength are examined. The coefficient of the phase-field model is optimized by combining martensite transformation experiments with a BP neural network. A quantitative elastoplastic phase field model that involves the evolution mechanism of secondary phases is established. Phase-field simulations show that zones with higher peak temperatures in the heat-affected zone exhibit higher martensite transformation start temperatures (Ms) and faster martensite transformation rates. The simulation results are in good agreement with experimental results. The phase-field simulation in this study reveals that elastic strain energy is the dominant factor controlling the thermal stability of martensite transformation.
In order to comprehensively weigh the mutual constraints and design contradictions of ultra-long blades in transportation logistics, aerodynamic efficiency, structural topology, lightweight demand and service life, this paper focuses on the key technical bottlenecks and design difficulties in the research and development of large megawatt blades, systematically discusses the structural design methods of adaptive blades, bionic blades and segmented blades, and further expounds the aerodynamic shape design for power maximization and the design concept of recyclable materials for sustainable development. The research results can provide theoretical basis and technical reference for solving the key problems of large-scale blades in development, transportation, noise reduction, operation and maintenance, improving their life cycle performance, realizing cascade utilization and green recycling, and promoting the application of new intelligent materials, bio-based materials and biodegradable materials, and have guiding significance for realizing cost reduction and efficiency increase.
To address the engineering risk of steel wire corrosion induced by chloride salts in Prestressed Concrete Cylinder Pipe(PCCP)in saline soil environments,which readily triggers wire breakage and pipe bursting,improving the chloride ero-sion resistance of PCCP protective layer mortar is of critical engineering value.Aiming at the prominent performance gap be-tween laboratory-fabricated specimens and on-site roller-sprayed molded specimens,this study introduces 3%water reducer to optimize the laboratory molding process,realizing the matching of key indicators between the two types of specimens.Through a 180 d chloride dry-wet cyclic erosion test,combined with microscopic characterizations via X-Ray Diffraction(XRD),Scanning Electron Microscope(SEM)and Mercury Intrusion Porosimetry(MIP),as well as correlation analysis of macroscopic indicators including compressive strength and total porosity,we systematically investigate the effects of Nano-Silica(NS),Fly Ash(FA)and Calcined Layered Double Hydroxides(CLDHs)on the chloride erosion resistance of PCCP mortar,and elucidate the corresponding enhancement mechanism.The results show that the L2 group with 2%CLDHs alone exhibits excellent erosion resistance,with compressive strength increased by 56.39%,chloride ion concentration at the same depth decreased by 31.1%,and total porosity reduced by 8.69%at 180 d compared to the reference group;the F20-N0-L2 group with 20%FA and 2%CLDHs presents the optimal comprehensive performance,with flexural strength increased by 51.28%,chloride ion concentration decreased by 41.1%,and total porosity reduced by 24.07%.
In this paper,a higher-order method to solve the viscous Burgers equation is constructed and analysed.The main idea of the method is based on a proper selection of the numerical fluxes,a higher-order spatiotemporal evolution method which combines the local discontinuous Galerkin(LDG)method in the spatial direction and the spectral deferred correction(SDC)method in the temporal direction is proposed.Theoretically,the L2 stability and the optimal error estimation for the spa-tial semi-discrete LDG method are proved,and the stability of the fully discrete method is given.Numerical examples are dis-played to show the effectiveness of the proposed method.
The flow behavior of molten slag directly impacts the stability of slag removal processes in high-temperature fur-naces,with alkali metal oxides exerting a significant influence on slag flow characteristics.To elucidate the structural evolu-tion mechanism by which Na2O modulates the viscosity-temperature properties of silicate slag,molecular dynamics simula-tions,FactSage thermodynamic calculations,and Raman spectroscopy analysis are employed to investigate the effects of Na2O content on slag structure and viscosity under fixed SiO2/Al2O3 conditions.Results indicate that as Na2O content in-creases within the 0 wt%-8.91 wt%range,the complex structural unit[Si2O5]2-(Q3)continuously depolymerizes into[SiO4]4-(Q0)and[Si2O7]6-(Q1),leading to increased non-bridging oxygen(NBO)proportion and decreased polymerization degree(DOP).Concurrently,Na+compensates for Al3+charges,promoting the transformation of unstable[AlO6]octahedra into more stable[AlO4]tetrahedra.The network depolymerization effect of Na2O dominates its macroscopic viscosity-temperature be-havior,resulting in a significant viscosity decrease with a good linear correlation between viscosity and degree of polymeriza-tion.Below the liquidus temperature range,when Na2O<8.91 wt%,its addition suppresses slag crystallization tendencies.This promotes the transformation of high-melting-point minerals like wollastonite and calcium feldspar into low-melting-point feldspars,thereby enhancing slag fluidity and reducing viscosity.This study reveals the microscopic mechanism by which Na2O regulates the viscosity-temperature characteristics of silicate slag,providing a theoretical basis for safe slag disposal.
Functional canonical correlation analysis is a key method in multivariate statistics for identifying optimal linear correlations between two functional datasets.However,some functions within these datasets may exhibit anomalies such as sudden changes or fluctuations that deviate from the overall trend,resulting to inaccurate results.To address this,we propose an improved method:Sparse functional canonical correlation analysis based on the L2,1-norm.This approach reduces outliers by optimizing the selection of orthogonal basis functions,thereby enhancing the accuracy and reliability of the analysis.Nu-merical experiments show that the L2,1-norm-based method significantly outperforms traditional methods.
Intelligent identification of low-resistivity thin oil layers is crucial for improving logging interpretation accuracy in complex reservoirs.In Dongying formation of Chengbei 35 block,Chengdao oilfield,the low-resistivity and thin interbed characteristics lead to ambiguous logging responses and minimal differences between productive and non-productive layers.This paper innovatively applies the Gradient Boosting Decision Tree(GBDT)model for intelligent identification of low-resistivity thin oil layers.By integrating logging curve characteristics,lithoelectric test results,production data,and reservoir physical properties,a logging feature set of low-resistivity layers is constructed through mathematical feature extraction.Key discrimination parameters are selected via a decision tree feature selection mechanism as input for the GBDT model,establish-ing an intelligent identification model for low-resistivity reservoirs.Combined with lithoelectric test data,the reservoir lower limit standards are determined.Application results show that the GBDT model achieves an identification accuracy of 89.5%,approximately 30%higher than the traditional logging numerical model,significantly reducing errors caused by manual inter-pretation and providing an intelligent solution for efficient exploration and development of low-resistivity thin oil layers.
Many engineering problems require simulations of parameterized partial differential equations.It takes a lot of time to solve this kind of problem when the discretization scale of the equation is larger and the parameter space is more com-plex.To improve the solving efficiency of partial differential equations with parameters,this paper proposes an ST-Greedy-POD reduced basis method for parameterized PDEs based on the space-time finite element discretization.Firstly,the param-eterized PDE is discretized in both space and time via the space-time finite element method,yielding a parameterized alge-braic equation.Then,the parameterized equation is separated into the parameter-dependent part and the parameter-independent part.Secondly,the Greedy algorithm is adopted to select optimal parameters from the parameter sample set ac-cording to posterior error,and the space-time reduced basis space is constructed iteratively,to further derive the space-time projection matrix.Finally,the parameterized system separated by parameters is projected onto the space-time reduced basis matrix to obtain the space-time parameterized reduced-order model and the corresponding reduced basis algorithm is pre-sented.The proposed method reduces both the time variable and the space variable simultaneously.The results of two numeri-cal examples verify the feasibility and effectiveness of the proposed method.
The central and western regions of China are located in high-intensity seismic zones,with some areas having a seismic fortification intensity as great as 9-degree,posing great challenges to structural seismic design.This paper takes a high-rise elderly-care building structure in a 9-degree seismic fortification area in western China as an example,focusing on the combined seismic isolation and seismic mitigation design method of steel structures.We compare 3 design schemes:Con-ventional steel structure scheme,seismic isolation scheme,and combined seismic isolation and seismic mitigation scheme,where lead rubber and natural rubber bearings as well as viscous dampers are arranged in the isolation layer,and buckling re-strained braces are arranged in the upper structural steel frame.In comparison,the combined scheme yields the best seismic reduction performance,and the seismic response of the upper structure is significantly reduced.The result analysis of the base shear force,upper structure deformation,tensile stress of isolation bearings,and energy dissipation of typical components shows that this combined design method for the high-rise building is feasible,and all calculation indexes can meet the requirements of Chinese design codes,providing references for similar high-rise buildings in high-intensity zones.
Wind turbines are subjected to long-term cyclic loading during their service life span,leading to progressive accu-mulation of deformation,which may compromise the structural integrity and operational safety of the turbines.In China,sandy soils are widely distributed in wind farm construction sites.To investigate the long-term deformation behavior of sandy soils under such cyclic loading conditions,a series of drained triaxial tests are conducted on saturated Toyoura sand,involving both static and cyclic loading modes.The effects of dynamic deviator stress,static deviator stress,and initial confining pres-sure on the accumulation of strain are systematically examined.Owing to their concise structure and practical applicability,ex-plicit models are frequently employed to represent the long-term cyclic deformation characteristics of sandy soils.Utilizing the results from laboratory tests,this study establishes an explicit formulation tailored to saturated Toyoura sand,capturing its axial strain accumulation under cyclic loading.The corresponding model parameters are also calibrated based on the experi-mental observations.Two formulations of deviator stress are compared,and the influence of initial consolidation stress and cy-clic stress amplitude on deformation accumulation is interpreted from a mechanistic perspective.Comparison with laboratory observations verifies that the model provides a reasonable prediction of the long-term cyclic deformation response in satu-rated sand.
Considering the great social benefits of vaccination and the unpredictability of changes in the natural environ-ment,this paper introduces the Ornstein-Uhlenbeck process to characterize the stochastic fluctuations in the transmission rate,proposes and studies a stochastic SVI epidemic model.Firstly,the existence and uniqueness of the global positive solution for the model are analyzed.Secondly,by constructing appropriate Lyapunov functions,defining a compact set,and using tools such as Itô's formula,the existence of a stationary distribution for the model is proved.In addition,the sufficient condition for disease extinction is derived.Finally,some numerical simulations are used to explain the main theoretical results.The re-sults show that,increasing vaccination rates can inhibit the rise in the number of infections and reduce the risk of transmis-sion,but it can not completely eliminate the disease.
Effects of different annealing processes on the mechanical properties and interfacial microstructure of warm-rolled Ti/Al/Al/Fe laminated multimetallic composite plates(LMCs)are investigated in this manuscript.The results indicate that with the increase of annealing temperature,the thickness of the interface diffusion layer gradually increases,the bonding strength of Ti/Al interface gradually increases,while the tensile shear strength of Fe/Al interface first decreases and then in-creases.When annealing at 550℃/1 h,Ti/Al/Al/Fe composite plates exhibit the best comprehensive properties,tensile strength(170 MPa)and elongation after break(52%).After annealing,TiAl3 phase is formed at the Ti/Al interface,while FeAl3,Fe2Al5,and Fe4Al13 phases are formed at the Fe/Al interface.The interface gradually transitions from mechanical mesh-ing to large-area metallurgical bonding.
Density reduction of saturated silty sand layers caused by construction disturbance of underground engineering in soft soil,can lead to pore-pressure accumulation under undrained loading and triggering instability.To investigate the me-chanical behavior of saturated silty sand under different levels of construction disturbance,a quantitative index is developed to characterize the degree of construction disturbance,based on which reconstituted specimens are prepared and tested using consolidated drained and consolidated undrained triaxial shear tests.The stress-strain curve analysis shows that,under low confining pressure,loose and medium-dense saturated silty sand exhibits static liquefaction accompanied by strain softening,and the extent of softening decreases with increasing confining pressure.Loose and medium-dense silty sand shows a higher susceptibility to static liquefaction under low confining pressure;low-density silty sand demonstrates a stronger liquefaction potential and a higher undrained brittleness index under low confining pressure.With increasing initial relative density,the re-gion between the failure line and the instability line in stress space shrinks,implying a reduced likelihood of static-liquefaction instability.
To address the problems of uneven switching loss and low efficiency existing in the three-level active neutral point clamped(3L-ANPC)inverter,a hybrid 3L-ANPC inverter composed of 4 SiC power devices and 2 Si power devices has been built,and two modulation schemes have been proposed to balance the distribution of switching loss.The proposed modu-lation schemes complement each other and are mixed use in a cycle.By the regulation of the proportion time in a cycle for the two modulation schemes,the balanced distribution of loss and temperature for the power devices in 3L-ANPC inverter has been realized.A 3 kW experimental platform has been constructed,the device temperature and working efficiency have been compared for 3L-ANPC inverter modulated by the proposed scheme of loss-balancing distribution and a traditional modula-tion scheme,the result has shown that the working efficiency has been improved by 0.5%,and the maximum device tempera-ture difference has been reduced by 78.6%.
Rapid standardization of rock color determination is a crucial aspect of geological research.Current methods pri-marily rely on expert visual description,Munsell color chart comparison,and spectral analysis,which fall short of meeting the demands for rapid and accurate rock color identification and digital standardization during extensive indoor and outdoor core observations.This paper proposes a computer vision-based intelligent rock color recognition method.Based on the Codes for names and colors of rocks in the petroleum geology(SY/T 5751-2012),a standard database containing 112 rock colors is constructed.Three algorithms—color thresholding,edge detection,and GrabCut—are designed to accurately segment target rock regions.Digital analysis,including color feature extraction,is performed on coordinate-based and gridded images to cal-culate the color vector of the rock image.Addressing the challenge of accurately identifying similar color systems,a weighted multi-feature fusion color matching algorithm is designed,incorporating evaluation indicators such as cosine similarity,Eu-clidean distance,RGB component differences,and brightness factor,significantly improving the system's ability to identify similar hues.A visualized intelligent rock color recognition system is developed using Python programming language and the PyQT6 framework,achieving digital quantitative identification of rock colors and improving recognition accuracy and effi-ciency.The results show that the system's identification results for 35 rock samples are highly consistent with the Munsell color chart interpretation results,with the consistency of hue(H),value(V),and chroma(C)reaching 91.43%,85.71%,and 71.43%,respectively.The system also shows complete consistency in the identification of independent test samples,verifying the correctness of the core algorithm logic,and the average identification time can reach the millisecond level.
In order to study the mesoscale pore structure and damage evolution of modified raw soil materials incorporating cement and oil sludge,CT scanning tests are conducted on cube specimens under axial pressure.Cross-sectional CT images of the specimens at different stress stages under dynamic load are obtained,and the variation law of internal porosity of materials with different ratios is quantitatively characterized by gray scale analysis and threshold processing methods.The intrinsic rela-tionship between porosity and material damage is established,which reveals the evolution law of damage in modified raw soil materials with stress and the corresponding failure mechanisms.The results show that:under different stress conditions,the cracks of YS1 specimens extend from the core compression zone to the edge,and YS2 specimens exhibit a"figure-eight"fail-ure mode.The addition of oil sludge promotes the formation of a gel with strong binding capacity and plasticity,which en-hances the deformability of YS2 specimens.Increasing the cement content leads to the generation of dense crystalline poly-mers,which results in superior mechanical performance of YS1 specimens.In the XY and YZ scanning sections,porosity varia-tions differ significantly among specimens under different stress conditions.The damage degree of YS1 specimens increases continuously,whereas that of YS2 specimens rises initially and then declines.Although YS2 specimens exhibit lower overall damage levels,their mechanical performance remains inferior to that of YS1 specimens.Excessive oil sludge content ad-versely affects mechanical properties,which suggests an optimal mass ratio of oil sludge to cement of approximately 1∶2.
Coal-fired power plants serve as primary sources of NOx emissions,and the efficient operation of SCR denitrifica-tion systems is crucial for reducing pollutant emissions.However,the highly dynamic changes of data during NOx prediction processes limit the accuracy of predictive models.Therefore,a hybrid prediction framework based on modal energy diffe-rence and sample entropy,which combining variational mode decomposition(MEVMD)with genetic algorithm(GA)to opti-mize convolutional neural network(CNN)and long short-term memory network(LSTM),is proposed.Firstly,abnormal data are corrected using the 3σ criterion;20 key auxiliary variables are selected via Pearson correlation coefficients.The maximum information coefficient(MIC)is employed to determine the delay time for each variable,achieving temporal alignment be-tween features and target variables.Secondly,adaptive variational mode decomposition(VMD)precisely extracts multi-frequency features from NOx time-series signals.Hyperparameters are optimized via GA to achieve adaptive modeling of mul-tiple sub-modes.Finally,prediction results are generated through data reconstruction.Experimental results demonstrate that the proposed model achieves RMSE of 0.949 2,MAE of 0.496 9,and R2 of 0.976 7,outperforming comparison models.
