805 results about "Freeze thawing" patented technology

The invention discloses a freezing and thawing stratum grouting numerical analysis modeling method and system, particularly relates to the technical field of hydraulic engineering numerical simulation, and is used for solving the problem of grouting parameter prediction inaccuracy caused by neglecting the dynamic coupling relationship between the thermodynamic behavior of a phase-change material and a seepage field and a damage field in an existing grouting model. A dynamic correlation system of phase change energy storage performance parameters and seepage field-damage evolution is established, a slurry diffusion path priority channel weight is corrected based on a freeze-thaw interface migration track, a bidirectional iteration equation of a seepage field and a diffusion migration field is coupled, and multi-physical field spatial-temporal scale cooperative solution is realized through a separated iteration algorithm; through multi-dimensional coupling of thermodynamic characteristics of the phase-change material, heterogeneous evolution of seepage paths and damage mechanical response, the prediction precision of the mechanical characteristics of the grouting stone body and the slurry diffusion range under the action of freeze-thaw cycle is remarkably improved, and the leakage and structural instability risks are effectively reduced.

The invention belongs to the technical field of rock freeze-thaw damage prediction, and relates to a deep learning rock freeze-thaw damage prediction method based on physical constraints, which is used for improving the physical consistency and prediction precision of a rock freeze-thaw damage prediction model. According to the method, a physical constraint formula is introduced into a data-driven deep learning model, and organic unification of data fitting and physical rationality is realized by using an adaptive weight strategy. The prediction method comprises the steps of data acquisition, data set generation, network construction, physical constraint mechanism formula design, rock freezing and thawing experiment observation or theoretical formula derivation, design of a formula reflecting evolution of various physical properties, model training and prediction output. The deep learning rock freeze-thaw damage prediction method based on the physical constraint has the advantages that generalization ability is remarkably improved, physical continuity and consistency are higher, multi-parameter and multi-source data are comprehensively applied, a staged self-adaptive training strategy is adopted, cost and resources are saved, operation is easy and convenient, and application and popularization are convenient.

The present invention relates to the technical field of mine rock slope analysis, and in particular to a freeze-thaw damage analysis method and system for mine rock slopes. The method comprises the following steps: selecting mine rock slope samples, performing freeze-thaw cycle tests on the mine rock slope samples, and obtaining rock freeze-thaw test information; on the basis of the rock freeze-thaw test information, setting displacement analysis indices, and on the basis of the displacement analysis indices, obtaining displacement variations of rock slopes under freeze-thaw cycles; on the basis of the rock freeze-thaw test information, analyzing plastic damage conditions and mine safety coefficients of the rock slopes under the freeze-thaw cycles; on the basis of the rock freeze-thaw test information, establishing a stress analysis model, and by means of the stress analysis model, obtaining stress distribution conditions of the rock slopes under the freeze-thaw cycles; and by combining the displacement variations, the plastic damage conditions, the mine safety coefficients and the stress distribution conditions, analyzing damage results of the mine rock slopes. In the present invention, multi-objective analysis of freeze-thaw damage conditions of mine rock slopes is performed, thereby ensuring the stability of the rock slopes.

The invention belongs to the technical field of geological engineering and environmental science, and relates to a rock freeze-thaw damage prediction method based on deep learning, which comprises the steps of data preparation, data preprocessing, data set generation, model construction, model training, model verification and prediction output. According to the method, the deep learning model is applied, the rock freeze-thaw damage rule is automatically extracted by using the deep learning model, and the large parameter quantity is achieved; adopting a missing value processing method, and marking a missing value through a two-dimensional vector; for sample distinguishing of different sources, hot independent coding is adopted; in the aspect of a mask mechanism, the model focuses on real data. According to the rock freeze-thaw damage prediction method, a deep learning model can be constructed, the model not only improves the prediction precision, but also enhances the robustness and generalization ability of the model, multiple defects of a traditional model can be effectively overcome, the output of the model can be used for evaluation and engineering design of rock freeze-thaw damage, and the method is suitable for large-scale popularization and application. Scientific basis and decision support are provided, and the method has a wide application prospect.

The invention relates to the technical field of freeze-thaw mud flow simulation, in particular to a freeze-thaw mud flow chain disaster power simulation method and system. The method comprises the following steps: obtaining regional topographic measurement data and carrying out point cloud conversion and three-dimensional modeling, generating a digital topographic model, collecting regional meteorological data and extracting features, carrying out multi-source fusion with the digital topographic model, forming a data fusion model, and based on the model, identifying freeze-thaw critical conditions and positioning freeze-thaw susceptible regions. The method comprises the following steps: carrying out geological structure calculation and stability analysis on a susceptible area, generating mud flow risk data, carrying out dynamic change simulation by utilizing the risk data, obtaining a simulated mud flow node and generating a disaster formation track, carrying out disaster risk assessment on the disaster formation track, and carrying out emergency early warning processing based on an assessment result to generate corresponding early warning data. According to the invention, a more accurate freeze-thaw mud flow chain type disaster-forming power simulation method is realized.

The invention discloses a regional cotton water and fertilizer dynamic decision-making method considering salt stress and a freeze-thaw mechanism, and the method comprises the steps: obtaining the multi-source historical data of a target region, integrating the multi-source historical data, analyzing the historical rainfall data of the target region, and dividing the historical rainfall data into Fengping low hydroponic years; constructing a crop growth prediction model coupled with salt stress and a freeze-thaw process through the integrated and divided data; performing sensitivity analysis on the crop growth prediction model to obtain an objective function, optimizing the objective function, setting constraint conditions, and specifying a multi-objective optimized water and fertilizer strategy; establishing a farmland information system based on the Internet of Things technology, and storing real-time monitoring data; and establishing a water and fertilizer system dynamic adaptation system through a multi-objective optimized water and fertilizer strategy and the farmland information system based on the Internet of Things technology, and providing an accurate water and fertilizer system according to the water and fertilizer system dynamic adaptation system. According to the invention, a more accurate water and fertilizer system can be provided for farmers.

The invention provides a power transmission and transformation project reinforced concrete corrosivity evaluation method and system, and relates to the technical field of civil engineering durability evaluation.The method comprises the steps that temperature data of a project location and the total volume, the water content and the pore volume of reinforced concrete are collected, and a freeze-thaw failure index formula is constructed; the product type is judged according to the measured sulfate concentration, different sulfate erosion index formulas are constructed in combination with related data, and the magnesium ion concentration is independently considered in the marine environment; constructing a chlorine salt erosion index formula according to the chloride ion concentration; extracting data from the research report to construct a carbonization erosion index formula; and giving a weight to each erosion type to establish a comprehensive corrosivity evaluation index formula, and judging the erosion degree according to a result. By means of the method, various erosion factors can be comprehensively considered, the erosion degree can be effectively judged according to the evaluation result, and a key basis and scientific guidance are provided for durability guarantee, protective measure making and maintenance decision making of the reinforced concrete structure of the power transmission and transformation project.

The invention relates to the technical field of remote sensing science and technology, in particular to a frozen soil region freeze-thaw disaster identification method and system and a storage medium, and the method comprises the steps: generating a target differential interference image set; carrying out homogeneous point filtering, phase unwrapping optimization and unwrapping error correction on the basis of the target differential interference image set to obtain an unwrapped phase image set; for each unwrapped phase diagram, performing uniform sub-block division, and based on an elevation-phase empirical relationship, estimating and removing an atmospheric delay phase existing in each sub-block through a linear fitting method to obtain a phase optimization diagram set after atmospheric influence is removed; performing sequential superposition on unwrapping phases corresponding to the interferograms in the phase optimization diagram set, and performing analysis by using the relationship between the average phase change rate after superposition and the radar wavelength to obtain earth surface deformation data; and unsupervised classification and screening are carried out based on the earth surface deformation data, and freeze-thaw change areas are optimized, so that a high-precision freeze-thaw recognition result is obtained.

The invention discloses a slope physical similarity model device and a slope internal crack evolution identification method, and relates to the technical field of open pit coal mine slope ecological protection, and the slope physical similarity model device comprises a similar material simulation system, a monitoring system and an artificial rainfall system. Through cooperation of the similar material simulation system, the monitoring system and the artificial rainfall system, surface water seepage field change and instability process simulation caused by slope rock-soil mass fracture evolution under different main control factors can be artificially controlled, and temperature, rainfall, stress, fracture development and other characteristic changes in the whole process can be monitored in real time; the method can deeply explore the internal relationship with slope instability, obtain the slope instability failure path, failure source and key block, determine the main control factor threshold of each stage, reveal the seepage and instability mechanism of the open pit coal mine slope under the freeze-thaw cycle, and improve the stability of the open pit coal mine slope. And a theoretical basis is provided for establishment of multi-source criteria of seasonal freeze-thaw landslide of the high and cold opencast coal mine and early-and-middle-stage early warning.

The invention provides an experimental system of a hot water force coupling landslide model, which is characterized in that on the basis of a large freezing and thawing environment test box, an artificially manufactured slope model is placed in the large freezing and thawing environment test box, and meanwhile, a rainfall and snowfall system, a slide rail system, a water level control system, a servo loading system, a medium strain rate disturbance system and a data acquisition system are integrated; a complete slope landslide model indoor experiment device under the combined action of freeze thawing-load-seepage is formed and used for simulating slope landslide caused by rainfall and snowfall, blasting vibration, slope body water level change and other conditions, and multi-source heterogeneous data of the whole process of the landslide from the unstable factor accumulation stage, the temporary sliding stage, the sliding stage and the stable stage are obtained.

The invention discloses a rapid reconstruction method, device and equipment for a soil mass freeze-thaw hydrothermal field and a storage medium, and the method comprises the steps: building a one-dimensional soil column frost heaving-thaw collapse calculation model through finite element software, carrying out the simulation calculation to obtain a soil mass one-dimensional freeze-thaw transient temperature field and a moisture field, and obtaining a source domain data set containing the position, time, temperature and saturation; the position and time in the source domain data set serve as input, temperature and saturation serve as output, a deep neural network is established, and a loss function comprises data loss and physical loss and also relates to a temperature field and a moisture field; training the source task model to obtain neural network parameters; and training the target task model. On the basis of numerical simulation and deep transfer learning, the problem of multi-field coupling under the background of machine learning is solved, and meanwhile, the generalization performance of the model is improved, so that rapid reconstruction of the transient temperature field and the moisture field of the one-dimensional frost heaving-thaw collapse test of the soil body under the condition of sparse measuring points is realized.

The invention discloses a marine low-temperature concrete additive and a preparation method thereof, and belongs to the technical field of concrete admixtures. The marine low-temperature concrete additive is prepared from the following raw materials: silane / polymer hybrid modified silicon dioxide, anti-freezing fibers, an air entraining and water reducing agent, silica fume, sodium hexametaphosphate and calcium chloride. Through scientific proportioning of silane / polymer hybrid modified silicon dioxide, compound anti-freezing fibers and other components, on one hand, cement matrix interface bonding is enhanced, the integrity of the internal structure of concrete is improved, microcrack initiation in the freezing and thawing cycle process is reduced, and the surface hydrophilicity of the hybrid modified silicon dioxide is enhanced; according to the present invention, by adding the cross-linked polymer, the dispersibility can be improved, the pore structure of the concrete can be optimized, the macroporosity can be reduced so as to reduce the freeze-thaw damage risk and improve the freeze-thaw erosion resistance of the concrete, and the cross-linked network structure is formed in the cement matrix so as to improve the strength and the toughness of the concrete and enhance the freeze-thaw resistance.

The invention relates to the technical field of dam body detection, in particular to a dam body leakage diagnosis method and system based on an AI technology. The method comprises the following steps: acquiring a sensor array data set, analyzing the sensor array data set, and determining a unified space-time detection data set; analyzing the unified space-time detection data set, determining a freeze-thaw conversion time axis, tracking and screening corresponding detection data in the unified space-time detection data set according to the freeze-thaw conversion time axis, and determining a target period detection data set; and according to the target period detection data set, evolution simulation is conducted on the seepage development situation of the dam foundation curtain, and dam foundation curtain seepage trend information is determined and output. According to the method, the pushing effect of the freezing and thawing cycle on the dam foundation curtain leakage condition is accurately captured, the dam foundation curtain leakage trend information used for visually representing the dam foundation curtain leakage development state is provided for corresponding dam body maintenance personnel, and the hysteresis of the dam foundation curtain leakage detection result is effectively eliminated.

The invention provides an ultrahigh bridge tower safety regulation and control method and system based on a concrete time-varying effect, and relates to the technical field of bridge tower regulation and control systems. Aiming at the problems that in the prior art, the prediction accuracy of long-term internal force redistribution caused by concrete shrinkage and creep is insufficient, the coupling effect of multiple risk factors and bridge tower concrete shrinkage and creep is insufficiently considered, so that the prediction accuracy of the state of a bridge tower is low, and a maintenance regulation and control guidance basis is lacked, multi-source heterogeneous data are fused, and the prediction accuracy of the state of the bridge tower is improved. Concrete shrinkage and creep, dynamic ice impact, static ice pressure, concrete freeze thawing and ice wedging influence indexes are calculated respectively, a comprehensive risk assessment model based on machine learning is adopted for fusion, and a comprehensive risk report containing risk levels and regulation and control suggestions is generated; according to the method, the accuracy of single risk factor assessment is remarkably improved, the comprehensive prediction precision of complex coupling risks is improved, and the decision robustness and maintenance efficiency of the system in a multi-risk concurrent complex scene are enhanced.

The invention relates to the technical field of spectral analysis and the technical field of computers, and discloses a freeze-thaw soil spectrum correction method and device, a storage medium and computer equipment, and the method comprises the steps: obtaining an in-situ spectral reflectivity curve of freeze-thaw soil, and determining a to-be-corrected spectral reflectivity group corresponding to each wave band; based on a frozen-thawed soil spectral reflectivity correction model and the spectral reflectivity group to be corrected, the spectral reflectivity of each wave band in a preset wave band range is restored and corrected, a corrected spectral reflectivity curve is obtained, and the frozen-thawed soil spectral reflectivity correction model is a transfer function model realized based on a random forest model. Aiming at the problem of spectral information distortion caused by multi-factor change in the freezing and thawing process of the soil, the frozen and thawed soil spectral reflectivity correction model can effectively correct the in-situ spectral reflectivity curve of the frozen and thawed soil, so that the estimation precision of the surface soil parameters in the freezing and thawing season is improved.

The invention provides a high-ductility cement-based composite material freeze-thaw damage prediction method and system fused with surface multi-scale structure recognition. The method comprises the following steps: S1, obtaining ECC surface damage information after a freeze-thaw cycle effect; s2, constructing an optimized ECC freeze-thaw damage strength prediction model based on a machine learning method; s3, according to the parameters obtained in the step S1, the surface damage coefficient of the ECC is determined through the prediction model in the step S2; and S4, predicting the damage strength of the ECC after freezing and thawing according to the surface damage coefficient. The invention provides an ECC freeze-thaw damage prediction model based on surface recognition, and the damage strength of a material can be speculated by analyzing surface damage picture information. According to the model, image information such as fiber exposure and surface peeling is directly associated with damage strength by using an image feature extraction and machine learning algorithm, and efficient and accurate prediction of the performance of the ECC material after freeze-thaw damage is realized.

The invention discloses a permafrost hydrothermal state simulation method and system based on a physical model, and relates to the technical field of permafrost region engineering. The method comprises the following steps: acquiring meteorological driving data and land surface feature data; constructing a numerical model of a permafrost hydrothermal process by considering a permafrost freezing and thawing process and a soil ice effect by utilizing land surface feature data; preparing boundary constraint conditions of the numerical model according to the meteorological driving data and the existing temperature field data; and performing permafrost hydrothermal state simulation on the land surface characteristic data by using meteorological driving data, constraint condition data, key vegetation and soil parameters and a driving numerical model to obtain a sample set formed by key permafrost hydrothermal information. According to the method, the dependence of an existing model on data and structures is broken through, the multi-scale application requirement of the permafrost region is met, and finally a high-quality meteorological driving and boundary constraint condition data set suitable for permafrost simulation without an observation region can be generated.

The invention provides a hydraulic concrete freeze-thaw damage microstructure segmentation method, electronic equipment and a medium. The method comprises the following steps: acquiring concrete two-dimensional CT images of different freeze-thaw cycle times; and taking the concrete two-dimensional CT image as the input of the U-Net network model, and training the U-Net network model to obtain a concrete microstructure segmentation model. According to the method, the problem that high-density groups of hydrated silicate, calcium hydroxide, unhydrated clinker and the like belonging to a mortar phase are misclassified into coarse aggregates is effectively avoided, and the problems that a traditional threshold method is not obvious in dividing boundary and unstable in dividing result are solved. The method provides an effective means for quantifying the influence of freeze-thaw damage on a multi-scale pore structure in the concrete and establishing damage evolution of the concrete under the action of freeze-thaw cycle.

The invention relates to a method for evaluating sulfate freezing and thawing resistance of recycled coarse aggregate self-compacting concrete. The method comprises the following steps: S1, preparing a recycled coarse aggregate self-compacting concrete test piece in which stones are completely or partially replaced by recycled coarse aggregate according to design requirements; s2, immersing the recycled coarse aggregate self-compacting concrete test piece in a freeze-thaw medium to carry out a freeze-thaw cycle test; s3, measuring a damage index of the recycled coarse aggregate self-compacting concrete test piece; s4, comparing the damage indexes of different recycled coarse aggregate self-compacting concrete test pieces to obtain the recycled coarse aggregate self-compacting concrete test piece with excellent comprehensive performance. According to the method, the influence of different replacement rates of the recycled coarse aggregate, different freeze-thaw environments and multiple freeze-thaw cycles on the performance of the recycled coarse aggregate self-compacting concrete can be accurately evaluated, so that theoretical basis and technical support are provided for improving the durability and engineering application of the recycled coarse aggregate self-compacting concrete in the sulfate freeze-thaw environment.

The invention discloses freeze-thaw resistant concrete and a preparation method thereof, and belongs to the technical field of cement-based building materials, the freeze-thaw resistant concrete comprises the following raw materials by mass: 35-40 parts of ordinary Portland cement, 100-180 parts of aggregate, 0.5-0.8 part of a water reducer, 4-6 parts of a phase change material, 2-5 parts of modified composite cellulose and 15-20 parts of water. According to the freeze-thaw resistant concrete prepared by the invention, polar groups on the surface of the modified fiber and the phase-change material form chemical bonds, so that the heat conduction efficiency is improved, the phase-change material quickly absorbs / releases heat during temperature change, the thermal response time is shortened, and the adaptability of a concrete structure to environmental temperature fluctuation is improved. The cellulose network with controllable porosity limits the volume expansion of the phase change material in the phase change process, so that the stress concentration in the concrete is avoided, and the generation of microcracks is reduced.

The invention relates to the technical field of water and soil loss monitoring, in particular to a water and soil loss monitoring and early warning system and method based on the Internet of Things. The system comprises a water and soil data acquisition and processing unit which acquires meteorological data, soil environment data and regional basic data by using an NB-IoT communication technology based on an Internet of Things sensor; the soil state monitoring unit divides a soil state monitoring period into a freezing period, a transition period and a rainwater period by using a soil state label mechanism; the water and soil loss monitoring unit combines the snow melting factor and the rainfall factor into a USLE model to obtain soil erosion amount models in different periods, and calculates the soil erosion amount; and the water and soil loss early warning unit analyzes the water and soil loss risk of each period and performs early warning. Based on a soil state label division mechanism of a freezing period, a transition period and a rainwater period and a staged water and soil loss monitoring model construction method, dominant erosion factors are dynamically switched according to freezing and thawing characteristics of black land in northeast China, and water and soil loss monitoring is achieved.

A frozen-thawed soil expansion deformation detection device comprises an operation box and a power distribution cabinet located at the bottom of the operation box, an openable sealing door is arranged on the front side of the operation box, a fixed bottom plate is fixed between the bottoms of guide rods, a quantitative sample containing cavity is formed in the top of a sample storage barrel, and an electric heating wire is arranged at the bottom or on the side wall of the quantitative sample containing cavity. An opening of the quantitative sample containing cavity is covered with a measuring piston, a measuring barrel cover is arranged above the sample storage barrel, the lower surface of the measuring barrel cover is used for making contact with the upper end of the supporting column, a measuring telescopic rod is arranged on one side of the sample storage barrel, and the measuring barrel cover is fixed to the center of the lower portion of the lifting plate; the two ends of the lifting plate are provided with guide sleeves arranged on the guide rods in a sleeving mode. The vertical displacement can be measured through the measuring telescopic rod which synchronously ascends and descends with the measuring barrel cover along with the change of the heating volume of a soil sample, so that sampling detection can be better performed according to soil in different regions, and the detection is more comprehensive.

The utility model relates to the technical field of tunnel engineering disease prevention and control, in particular to a tunnel deformation joint leakage water disease treatment structure under freeze thawing conditions, which comprises a stratum, a primary support and a tunnel lining are sequentially arranged on one side of the stratum, and a back-attached waterstop is arranged between the tunnel lining and the primary support; a deformation joint is arranged in the tunnel lining, and a steel plate middle-buried water stop belt is arranged in the middle of the deformation joint. A heating device is arranged in the area, located outside the steel plate middle-buried water stop belt, of the deformation joint, a drainage structure is arranged outside the heating device, and a water stop structure is arranged outside the drainage structure. And a gap in a deformation joint area between the steel plate middle-buried water stop belt and the back-attached water stop belt is filled with a grouting water stop material. The heating device is installed at the leakage position of the deformation joint, and grouting liquid reaction and plugging are promoted. A water stop structure is arranged on the downstream face of the deformation joint after grouting, a physical extrusion waterproof measure is formed, the deformation requirements of expansion caused by heat and contraction caused by cold and the like of the deformation joint can be met, and the water stop effectiveness is further improved.

The invention provides a concrete freeze-thaw damage degree characterization method based on image processing. The concrete freeze-thaw damage degree characterization method comprises the following steps: acquiring a picture after concrete surface freeze-thaw damage; preprocessing the picture to obtain a gray value picture capable of reflecting damage characteristics, and calculating a corresponding fractal dimension and an image information entropy; and establishing a concrete damage degree equation according to fractal dimensions and information entropy of the image in combination with components of a concrete material, and finally obtaining the concrete damage degree. The method is convenient and fast to operate, the damage degree of the frozen and thawed concrete can be accurately represented, meanwhile, the method considers concrete components, and therefore the method can be suitable for detection of all concrete materials. The method does not damage the test piece, and can be used for long-time tracking measurement and aging degree evaluation of the existing concrete building.

The invention relates to a curing agent for an iron tailing engineering backfill material and a use method of the curing agent. The curing agent is composed of Portland cement, calcium hydroxide, fly ash, modified superfine slag powder, alkaline residues and a sodium phosphate buffer system. And by adding the curing agent, the backfill material has excellent compressive strength, durability and permeability resistance. Due to the filling and interface enhancing effects of the modified superfine slag powder, the compactness of the material is remarkably improved, and the porosity and the permeability coefficient are reduced; the alkaline residues accelerate the curing reaction, and the freeze-thaw resistance of the material is improved. The method is suitable for various complex geological and environmental conditions, and the stability and safety of the backfill material in an extreme environment are ensured.

The present invention provides a frost heave strain test device for a concrete lined channel, and relates to the technical field of freeze-thaw cycle test devices, including a frost heave body storage bin, wherein a plurality of temperature sensors are evenly arranged at intervals from bottom to top at the axis of the frost heave body storage bin; a simulated lining, wherein the frost heave body storage bin below the simulated lining is filled with a frost heave soil layer, and an axial displacement monitoring device is used to detect the axial displacement of the simulated lining; by pumping freeze-thaw medium into the medium storage bin, the freeze-thaw medium exchanges heat with the frost heave body storage bin above, thereby causing the frost heave soil layer to undergo frost heave changes. The present invention replaces the traditional precast concrete lining structure with a simulated lining, and the simulated lining can be used repeatedly, and can further simulate concrete of different strength grades, thereby greatly reducing the consumption of raw materials, being fast, efficient, energy-saving and environmentally friendly; and at the same time, the existing scattered structures are integrated, thereby reducing the occupied space.

The invention provides a method, medium and equipment for evaluating stability evolution of an unsaturated soil slope in a cold region, and establishes a framework combining a soil-atmosphere interaction model and a cold region unsaturated soil water-steam-heat coupling transmission model. A finite element transient simulation program for simulating the water-heat state response of the unsaturated soil body in the cold region under the action of long-term and short-term climates is developed, and the technical problem that when a traditional numerical model simulates the sand freezing and thawing phenomenon, the latent heat release amount is prone to losing due to the narrow phase change temperature interval is solved. According to a limit analysis upper limit theorem, a slope stability evaluation method is established by adopting a discretization recursion technology, and a novel iterative solution scheme combining a dichotomy and a meta-heuristic optimization algorithm is innovatively provided. A finite element transient analysis model-stability evaluation coupling method is provided, so that the stability evolution evaluation of the unsaturated soil slope in the cold region driven by climate data can be carried out.

The invention relates to the technical field of soil detection, and particularly discloses a soil detection method based on a freeze thawing-unsaturated dynamic load hollow cylinder torsional shear apparatus, which comprises the following steps: respectively applying a vertical dynamic load, a torsional shear dynamic load and confining pressure through a vertical servo motor, a torsional shear servo motor and a triaxial pressure chamber, and simulating the stress state of a roadbed under the action of a dynamic wheel load; the unsaturated state of the sample is controlled through an axis translation method for controlling pore air pressure and pore water pressure, and the hydraulic state of the roadbed in the actual situation is simulated; the temperature of the sample is further controlled through a low-temperature water bath connected with the upper bottom surface and the lower bottom surface of the sample, and the temperature gradient in the roadbed freezing and thawing process is simulated; therefore, the instrument can introduce the influence of freezing and thawing and unsaturation while simulating the traffic dynamic load, can more accurately reflect the mechanical response of the cold region roadbed under the coupling action of freezing and thawing-unsaturation-traffic load, and provides a more accurate and more scientific basis for the performance evaluation of the cold region roadbed.

The invention relates to the technical field of building material modification, in particular to an anti-freeze thawing-sulfate composite modifier and application thereof in a water-stable base layer. In road engineering, a water-stable base layer often faces the problems of freeze-thaw cycle and sulfate erosion damage. The key point of the technical scheme of the invention is as follows: on the basis of the mass of cement, a composite modifier is composed of the following components in percentage by mass: 2%-5% of sodium sulfate, 0.02%-0.05% of sodium gluconate, 0.4%-0.6% of polypropylene fiber, 0.1%-0.2% of steel fiber, 1%-3% of butadiene styrene rubber emulsion, 0.05%-0.5% of sodium carboxymethyl cellulose, 0.05%-0.1% of triethanolamine, 0.1%-0.5% of naphthalene water reducer, 0.005%-0.02% of air entraining agent, 8%-10% of silica fume and the like. The composite modifier is mainly used for the water-stabilized base, can effectively improve the freeze-thaw resistance and sulfate erosion resistance of the water-stabilized base, and prolongs the service life of a road.

The present invention discloses a kind of preparation method and use method of anti-abrasion concrete admixture under freeze-thaw-solution environment, the admixture includes the components of following parts by weight:50~60 parts of STG powder, 5~8 parts of polyimide fibers, 1~3 parts of hydroxypropyl methyl (HPMC) cellulose, 10~13 parts of polycarboxylate water-reducing agent, 10~15 parts of antifreeze, 10~13 parts of expansion agent, wherein STG powder includes modified silica fume-glass powder, silicon carbide titanium, graphene oxide. Anti-abrasion concrete admixture under freeze-thaw-solution environment of the present invention can effectively suppress the decomposition of calcium hydroxide, and can refine pore structure, make hydraulic concrete more compact, while improving the ability of hydraulic concrete to resist dissolution, enhance its anti-abrasion performance, the admixture has good low temperature resistance, can be applicable to cold low temperature environment, for the anti-abrasion strength under low temperature conditions there is obvious improvement.