Since the concept of resilience was introduced into the field of transportation， resilient transportation has received extensive attention from researchers in the transportation field. Road transportation infrastructures with good resilience can effectively deal with various natural and man-made disasters， and further meet the needs of efficient and safe transportation in the future. In order to clarify the current research status of road transportation infrastructure resilience around the world， the research results of road transportation infrastructure resilience were summarized from the definition， measurement methods， and resilience improvement technologies of road transportation infrastructure， and the future road transportation infrastructure resilience research was discussed especially the development direction and research focuses of resilience improvement technology. The analysis shows that the research on the resilience of road transportation infrastructure mainly focuses on the overall traffic network organization and planning level of the road network. The research on the resilience of the infrastructure structure is relatively scattered， and there is a lack of unified and comprehensive definitions and metrics. In addition， in the research on the catastrophic failure mechanism of structural resilience， there is a lack of a comprehensive research understanding of all elements and the coupling between structural systems， and it is difficult to reveal the chain process and catastrophe characteristics of catastrophic evolution. Therefore， the research on the resilience of future road transportation infrastructure should further reveal the theories and methods of catastrophe analysis of different types of facility structures， and establish a comprehensive and unified definition and measurement standard for the structural resilience of road transportation infrastructures. At the same time， from the perspectives of disaster monitoring， structural safety and resilience improvement， flexible operation and post-disaster recovery， etc.， more effective technologies for improving the resilience of road transportation infrastructure should be formed and furtherly promoted in the future.

In order to accelerate post-earthquake repair of bridges and reduce earthquake losses， a systematic review， summary， and outlook were conducted on the research of resilient structural systems in bridges. Firstly， the development history of resilient structural systems was reviewed. Secondly， from the perspective of seismic mechanism and engineering application， the similarities and differences between ductile and resilient structural systems were elaborated. Emphasis was placed on the important way to achieve earthquake-resistant resilient in bridges the rocking structural systems， and the working mechanisms， hysteresis curves， and engineering applications of the current four typical rocking structural systems were discussed. Thirdly， the progress of the domestic and foreign cutting-edge researches in resilient structural systems was summarized and analyzed from the aspects of rocking structural systems， self-centering energy dissipation devices， and seismic design methods. Finally， the existing problems and development trends of bridge resilient structural systems were summarized and prospected.

In order to promote the application of road safety intelligent perception technology， the research progress about intelligent monitoring of pavement icing condition based on optical fiber sensing at home and abroad was overviewed. Firstly， the principle of fiber-optic pavement icing detection was revealed. Subsequently，based on the analysis of different optical fiber performance indexes， the distribution mode of common probes and various weak signal detection methods， the fiber-optic pavement icing detection system was constructed. Then， common icing detection data pre-processing and its thickness analysis methods were explored， the main environmental influencing factors and measures to enhance detection effectiveness were outlined， and burying technology of fiber-optic road icing detection sensor was analyzed. Finally， current research status of icing pavement monitoring and early warning were summarized， the existing problems were discussed， and the development direction of intelligent sensing of pavement icing condition was attempted to outlook.

Firstly， the models used in parameter identification were summarized. Then， two popular techniques for frequency-domain identification were discussed， namely the Peak Picking method and the Complex Mode Indication Function method. The Peak Picking method is performed by selecting the modal frequency from the peak value of the output spectrum measured. While the Complex Mode Indication Function method is performed by diagonalizing the spectrum matrix. In addition， when the Complex Mode Indication Function is applied to the power spectral density， it becomes the reputed Frequency-Domain Decomposition method. Finally， the poly-reference Least Squares Complex Frequency domain method was discussed. This method shows advantages of low memory requirement， short computing time and high degree of automation， lying promising application in the operational modal analysis of bridge.

A bridge scour identification method based on dynamic characteristics of bridge structure and improved particle swarm optimization algorithm was proposed， in order to identify the position and degree of bridge scour damage quickly and accurately. The dynamic characteristics of the bridge structure and the static displacement of the pier top are taken as the scour identification parameters of the bridge in this method， and the quantitative correlation between the scour identification parameters and the scour depth of different piers was obtained by using multiple nonlinear regression. Therefore， the uneven scour depth of the pier can be identified according to the dynamic characteristics obtained during the actual detection of the bridge. Finally， the numerical simulation analysis of a simply-supported beam bridge was carried out， and the concrete application steps of the proposed bridge scour identification method based on the improved particle swarm optimization algorithm were demonstrated. The results show that the proposed method can identify the bridge scour location and scour depth， which has a certain accuracy. In practical engineering， scour damage identification of bridge foundation can be realized by using this method through conventional bridge detection， which avoids operational difficulties brought by underwater operation， and can evaluate the scour state quickly and accurately.

A temporary-permanent conversion rush-repair steel pier was developed. Based on ABAQUS three-dimensional simulation， the selection of main material was determined by analyzing the influence factors of ultimate bearing capacity. On this basis， the ultimate bearing capacity of steel pier structures in non-damaged and damaged state was studied. The results show that， the ultimate load bearing capacity of steel pier decreases with the increase of pier diameter to thickness ratio and increases with the increase of steel strength grade. When steel pier damage position is same， the deeper the damage degree is， the more sensitive the ultimate load coefficient is. When the damage degree of steel pier is same， the closer the damage position is to the bottom， the more significant the influence on the ultimate load coefficient is. In the local segmental damage， compared with material stiffness degradation， with the change of reduction coefficient， the impact of section size reduction and material strength degradation on the ultimate load coefficient is similar and more obvious. In the overall damage， the reduction of cross section size has the greatest effect， followed by material strength degradation and material stiffness degradation.

To understand the action law of flood on bridge pier， a numerical method was proposed to directly solve the main control equation of flow in order to find the law of various flow phenomena. Combined with the fluid dynamics simulation analysis technology， the numerical solution of the flow field was described by computer numerical calculation and image display， and then Latin hypercube sampling and stratified random sampling were adopted to ensure the full coverage of each variable as far as possible， and statistical analysis method was used to analyze the sampling data. Research was conducted on the influence of flood flow velocity， pier shape， pier number and spacing， water flow incidence Angle and other key flood disaster factors on the horizontal resistance effect of pier， to obtain a more comprehensive and accurate flood effect， and establish the flood disaster effect analysis model under the influence of various factors. In order to correctly evaluate the service status of bridge and provide theoretical support to ensure safe operation of bridge under flood.

In order to propose the finite element analysis method of steel-concrete composite beam bridges with multiple damages， and find out the influence law of different damage types and degrees on the mechanical properties of steel-concrete composite beam bridge， firstly， the finite element simulation method of multi-damage combination of steel-concrete composite beam bridge and the quantitative assessment method of damage grade were studied. Then， based on the vehicle-bridge coupling vibration， the dynamic response of the steel-concrete composite beam bridge midspan and the acceleration response of the vehicle body under different vehicle speeds and different damage grades were analyzed； At last， the key section deflection， relative slip between slabs and beams and stress variation of steel-concrete composite beam bridge under different damage grades were studied. The results show that the multi-damage combination simulation method can effectively characterize the multi-component damage intertwined state of steel-concrete composite beam bridges and achieve the quantitative description of the multi-damage state of steel-concrete composite beam bridges. With the increase of the damage grade， the mid-span vertical vibration displacement and acceleration response peaks increased， and the vertical， lateral and pitch vibration acceleration of the vehicle body also showed the same change pattern， compared with the undamaged state， the maximum increase of its peak value is 2.16 times， 92.5 times， 205 times， 565 times and 235 times respectively. The deflection and slip of the key section also increased， and the stress at the lower edge of the steel beam did not change significantly， while the stress at the upper edge of the concrete slab increased significantly.

To study the influence of transient effects of nonstationary wind field on wind-induced bridge response， the nonstationary wind field was simulated based on the Hilbert spectrum， and the wind field spatial correlation was introduced by the Cholesky decomposition. The 2-D indicial response function was applied to the nonstationary wind-induced bridge buffeting response analysis method considering the transient effects. The Hilbert spectrum was obtained from the measured data of downburst and typhoon to reappear the real downburst/typhoon wind field with high accuracy. A long-span suspension bridge was selected to implement the nonstationary buffeting response analysis， the influence of transient effects embedded in nonstationary wind field on the aerodynamics and buffeting response of the bridge was discussed. The results show that the downburst presents significant nonstationarity， and the time-varying mean wind-induced transient effects significantly modify the aerodynamics of the wind-bridge interaction system， which exerts a significant impact on the indicial response function and buffeting response of long-span bridges. However， the time-varying mean wind-induced transient effects are insignificant in typhoon case， and the influence on the aerodynamics and the buffeting response is almost negligible.

In order to eliminate the influence of temperature variation on crack width of continuous rigid frame bridges and improve the efficiency and accuracy of evaluating bridge safety through crack width variation， a rigid frame bridge in Guangxi Province was taken as the research object. The whole bridge model and the refined model of beam segment with cracks were established respectively. The relationship between temperature and crack width variation was studied according to the calculation results of cross-level model. The results show that both the uniform temperature and the gradient temperature action have an effect on the crack width variation. The modified formula considering the change of concrete material characteristics can be used to quickly determine the crack width variation caused by temperature change， which can provide an important basis for bridge safety early warning. Finally， the proposed method is applied to Luotianle Bridge project， and the accuracy of this method is verified by measured data.

The wind speed law in the simplified U-shaped valley was studied by theoretical deduction and terrain model wind tunnel test， and the buffeting response of a long-span suspension bridge in the valley was evaluated. The results demonstrate that the wind speed in the simplified U-shaped valley is the result of combined effects of pressure gradient and width to depth ratio. The acceleration effect of wind speed grows with the increase of the width to depth ratio. The spanwise distribution of wind speed conforms to the parabolic model， and the result of the terrain model wind tunnel test also verifies its rationality. Compared with the parabolic distribution model， the uniform distribution wind speed model recommended by the Code overestimates the buffeting displacement response at the main girder position and the internal force response at the key position of the bridge. The research can provide a reference for bridge wind-resistant design in the valley.

In order to solve the current situation that the reserve of existing bridge wooden sleepers is seriously insufficient and thus restricts the emergency use of assembled truss beams， a new type of steel sleepers instead of wooden sleepers was studied. To find out the vertical load distribution mechanism of the new steel sleeper used for assembled truss beam， full scale test of 4 m section and finite element simulation analysis were carried out. According to comparison between simulation and test， the influence of loading position， rail stiffness， chord stiffness， steel sleeper stiffness， and bridge vertical stiffness on vertical load distribution was discussed according to real bridge finite element model. It can be concluded that the actual distribution range of vertical load on the bridge sleepers is larger than the theoretical value. The steel sleeper at the position of chord joint bears larger proportion of load than the steel sleepers at the position between chord joints， and the stronger the support stiffness is， the larger the proportion of load is borne. The load extremum ratio of single sleeper borne decreases with the increase of rail stiffness， increases with the increase of steel sleeper stiffness， and has little relationship with the vertical stiffness of bridge structure. The increase of chord stiffness weakens the influence of loading position on the load extremum ratio of single sleeper born. The new type of steel sleeper can be applied to the deck of the assembled truss beams which are used to repair 16~32 m span bridges in common steel rail lines of Chinese railway. It can provide infrastructure support for the emergency repair of the assembled truss beams， and improve the reopened speed.

In order to study the effects of pore size， pore spacing， pore shape and porosity on the application performance of porous structures such as wind barriers， a multi-parameter porous plate force wind tunnel test was carried out， and the effect of various parameters on the wind resistance coefficient of porous plates was compared. The flow field characteristics and pressure drop variation of porous plate under different parameters were analyzed by numerical simulation. The effects of pore size and pore spacing on the boundary layer thickness and effective porosity under the same porosity were discussed， and the results were compared with the wind tunnel test results. The following conclusions are obtained： the pore shape has little effect on the drag coefficient of porous plate. The aspect ratio， pore diameter and pore spacing have great influence on the drag coefficient of porous plate， which can be used as the key parameters affecting the resistance coefficient of porous structure.

In order to investigate the bonding performance between ultra-high performance glass sand concrete （UHPGC） and HRB600 high-strength reinforcement， the influences of water-cement ratio （0.17， 0.19， 0.21）， steel fiber volume fraction （1%， 2%， 3%） and glass sand replacement ratio （0%， 50%， 100%） on the working and mechanical properties of UHPGC were analyzed. The variations of bonding performance between UHPGC-HRB600 were clarified based on pull-out test and acoustic emission monitoring. The results reveal that the addition of glass sand can improve the compressive strength of UHPGC， and corresponding optimum replacement ratio is 50%. The bond strength is positively correlated with the water-cement ratio and the amount of steel fiber， while it presents first increase and then decrease with the increase of the replacement ratio of glass sand. The bond-slip failure between UHPGC and HRB600 can be mainly divided into two types： splitting failure and shear pullout failure. The acoustic emission parameters exhibit favorable bond-slip characterization ability.

Firstly， a seismic resilience assessment framework was proposed for highway bridge networks by comprehensively integrating various influencing factors （network topologies， deterioration effects of bridges， regional seismic hazards， etc.） and their uncertainties. Then， the network topologies， seismic performance of regional bridges and traffic functionalities of highway segments were analyzed， and integrated to establish a time-dependent post-disaster simulation of highway bridge networks. Subsequently， an artificial neural network based methodology was proposed for rapid seismic fragility assessment of regional bridges. Finally， the life-cycle seismic resilience of the highway bridge network in San Francisco， USA was analyzed as a case study， which reveals the evolution law of seismic resilience the service life. The results demonstrate the developed data-driven fragility model can act as a reliable surrogate to traditional time-consuming fragility methods， with the goodness of fit of 0.73. Consequently， the proposed methodology for the life-cycle seismic resilience of highway bridge networks is effective and accurate， providing decision-making strategies for disaster prevention and mitigation.

Aiming at the problem that the natural frequency measured in the process of damage identification and state assessment of bridge structure is significantly affected by temperature and vehicle action， resulting in errors in frequency test results， the frequency coefficient of variation was introduced， the bridge frequency theory formula was simplified based on the temperature theory analysis model and the vehicle parameter law， and the key influencing factors were extracted to form an empirical formula for the bridge frequency coefficient of variation that excludes temperature and vehicle action. The results show that the bridge frequency calculation results obtained by the elimination method in this paper have little difference with the theoretical calculation results， which can well characterize the frequency of pure beam bridge and improve the accuracy of assessing the safety of bridge by using frequency variation.

Finite element models of simply-supported beam bridge with lead rubber bearing， friction pendulum bearing and viscous damper was established separately based on ANSYS. Through changing seismic excitation， structural parameters and vibration reduction isolation device parameters， the earthquake-induced residual displacement of bridge was analyzed. The results showed that the residual displacement was sensitive to seismic spectrum characteristics，and it increased significantly both with the rise of peak acceleration and shear span ratio， and it increased with the enlarge of duration and pier height at the same time. The residual displacement was the most sensitive to the change in parameters of lead rubber bearing and friction pendulum bearing， while changes in parameters of viscous dampers had less impact on it. The residual displacement could be reduced by increasing yield force and post-yield stiffness of lead rubber bearing， friction coefficient of friction pendulum bearing， length of the damping hole， outer diameter and viscosity of silicone oil of viscous damper， and by reducing curvature radius of friction pendulum bearing. The research results can provide theoretical basis for the improvement of disaster resilience of bridge structures.

Firstly， the mesoscopic parameters of asphalt upper layer， lower layer and waterproof bond layer were calibrated by uniaxial compression test， splitting test and oblique shear test. Then， by setting the failure area of interlayer bond， the stress， displacement and velocity of each structural layer was monitored. The results show that the bonding failure between asphalt surface layers significantly affects the stress and motion state of the top particles of the upper and lower layers， and the transverse stress of the bottom particles increases obviously. The bonding failure between the asphalt surface and the bridge panel leads to the increase of transverse stress of the particles at the bottom of the lower layer and the transverse movement trend between the layers. By monitoring the mechanical state changes of different structural layer materials after interlayer bonding failure， the development of bridge deck paving layer disease can be predicted， which can provide reference for preventive maintenance of asphalt bridge deck pavement.

In order to reasonably conduct a comprehensive evaluation of asphalt pavement performance， a PCA-PSO-SVM evaluation model based on principal component analysis and particle swarm optimization support vector machine is proposed to address the problems of the strong subjectivity of traditional pavement performance evaluation methods and the defects of existing models. The evaluation indicators are dimensionally reduced by Principal Component Analysis （PCA） to form mutually independent principal components. The key parameters of the Support Vector Machine （SVM）—the penalty coefficient C and the kernel function parameter g are optimized using the global search advantage of the Particle Swarm Algorithm （PSO） to improve model accuracy. Finally， 170 maintenance sections of a highway in the southwest region were used as an example to evaluate the pavement performance comprehensively using the PCA-PSO-SVM model and“Highway performance assessment standards”respectively. The results show that the PCA-PSO-SVM model overcomes the drawbacks of relying on empirical methods of determining parameters， improves the identification accuracy and makes the evaluation results more in line with the actual road conditions.

The impact of joint stiffness on vibration transmissibility across concrete pavement joints was analyzed by theoretical analysis， and a vibration-based identification method for joint damage was proposed. Furthermore， laboratory tests were conducted using MTS to verify the influence of local stiffness-loss on vibration transmissibility， with 400，000 loading cycles being applied. In addition， six concrete pavement slabs were constructed to conduct a comparative analysis with the deflection-based method， to further validate the proposed vibration-based method in actual engineering environments. The results indicate that there is a significant correlation between frequency transmissibility and joint stiffness， with a correlation coefficient of over 0.8. The repeated tests conducted on different joints and in different seasons suggest that the stiffness-loss ratio of joints can be identified with an accuracy of ± 0.069， thereby confirming the accuracy and reliability of the proposed damage identification method.

In order to realize high-precision prediction of road surface temperature， considering the influence of the road environment and the characteristics of the road structure in the longitudinal direction， a gridding monitoring method for dividing the asphalt pavement road surface temperature of the weather type was proposed， and conducted data mining and analysed based on a large amount of measured data of the test road section. Two perceptual network models （Euclidean distance model and correlation distance model） were established according to the logic of two different distance functions of the hierarchical clustering algorithm， the prediction accuracy of the model was validated by the measured data， and the evaluation and comparison of performance of the models were carried out by the mean absolute error （MAE）， root mean square error （RMSE） and mean absolute percentage error （MAPE）， based on which the applicability of the two models was discussed. By comparing estimated value and measured value， the results show that the gridding monitoring method proposed is sensitive to weather condition， the MAPE of the models is less than 5% on cloudy and overcast weather， and the maximum MAPE is 5.43% on clear weather. The RMSE of the model reach maximum value of 1.2 ℃ in clear weather and is less than 1 ℃ in other weather condition.

To study the influence of the vehicle detecting track offset on the calculation results of the degree of wear of asphalt pavement， three models of pavement with light， medium， and heavy wear grades were reconstructed based on the measured 3D laser elevation point cloud data， the mean profile depth（MPD） distribution of its full section wear index was drawn. The three-line method was used to calculate the road wear rate X_WR， and the track of the measuring line after the testing vehicle was offset to the left and right by 100 and 200 mm， respectively， were simulated. The absolute and relative errors of the wear rate X_WR before and after the offset were used as evaluation indexes to analyze the influence law of the track offset on the wear rate calculation error. The results show that the larger the offset distance of the detecting track offset， the absolute error and relative error of the wear rate increase gradually. The maximum absolute errors of the wear rate of the light， moderate and heavy wear sections are 5.95%， 10.71%， and 12.39%， respectively. The heavy wear level will be misjudged as the medium wear level， which may lead to the underestimation of the grade of pavement wear， and further lead to the misjudgment of road condition evaluation and maintenance decisions. Increasing the number of measured lines and reducing the distance between measured lines are effective measures to reduce the offset error and improve the accuracy of wear detection.

Based on the vehicle impulse response， a method of pavement roughness identification using vehicle dynamic response was proposed. First， road roughness was taken as input and the equation of vehicle response computation based on the impulse response function was derived. Then， the impulse response function was discretized into the matrix form and a linear equation for road roughness identification was established based on the impulse response matrix. Furthermore， considering that the front and rear wheels experienced the same road roughness， the correlation matrix of the front and rear wheels was constructed， which can decrease the computational work of road roughness identification. Then， take the advantage of the continuity of the road roughness， the load shape function was used to approximate it and thus not only the unknown identification number was further reduced but also the robustness of method to noise was improved， which achieved the real time identification. At last， the effectiveness of the proposed method was verified by numerical simulation and field test.

Due to the deficiency of the study on the resilience of road structure， the response function of road structure performance under the impact and siltation of debris flow was proposed. And the response function was solved by analyzing the characteristics of debris flow protection and toughness of road structure. Furthermore， the cumulative loss degree of road structure performance after debris flow is used to characterize the safety toughness， and a theoretical model of road structure safety toughness is established. Taking Shuiyugou debris flow in Shawan Town， Gansu Province as an example， the toughness curve and safety toughness of road structure at 394 km+800 m of Shuiyugou National Road was analyzed. The results show that the safety toughness value of road structure is only 63.92% when no measures are taken. After taking the emergency treatment， the safety toughness value of road structure increased to 81.98%. After taking measures to resist debris flow， the ability of road structure to deal with disasters further increased to 85.76%， which significantly improved the toughness. The results quantified the resistance and resilience of road structure under the impact and siltation of debris flow and provided a decision basis for improving the toughness of road structure under the impact and siltation of debris flow.

To understand the actual dynamic response of graded crushed rock （GCR）， the laboratory model testing and numerical analysis of GCR base layer were performed. First， based on the cross-anisotropy theory， a mechanical-empirical model for elastic modulus of GCR was established. Then， the stress and deformation laws at different positions of GCR structure were analyzed through laboratory model test. Finally， a novel calculation approach of finite element model was proposed for GCR base layer. The results of model testing and numerical analysis show that changes of stress in the GCR structure present a significant cross-anisotropy characteristic. The loading time and peaking displacement at the top of GCR layer are closely related to vehicle speed. The calculation results of finite element model are basically consistent with the trend of laboratory model test， but it is still conservative in pavement design.

The effects of the number of freeze-thaw cycles was used the method of indoor test and the stress level on the static shear strength and plastic deformation soil were investigated. The results show that the static shear strength decreases with the decrease of confining pressure and the accumulation of freeze-thaw cycles， and the permanent deformation gradually develops from plastic stability to plastic creep or incremental instability when the dynamic stress level increases. Based on the comprehensive analysis of the test results， the critical stress level to avoid the instability of permanent deformation and the discrimination criteria of each type are defined， a description formula of critical dynamic stress considering confining pressure and freeze-thaw cycles is proposed， and the ratio of shear stress generated by dynamic stress to shear strength is used to represent shear action， and a mechanical-empirical model suitable for permanent deformation of subgrade clay subjected to freeze-thaw cycles was established and verified. The results of the study can provide theoretical support for the stability and durable operation of the subgrade in the monsoon freeze zone.

In order to investigate the influences of factors such as load form， packaging material and shape characteristics on the monitoring results of the SmartRock sensor， so as to provide an effective way for evaluation of the physical and mechanical properties of the mixture media based on sensor parameters. Firstly， the indoor secondary calibration tests of the SmartRock sensor were carried out； secondly， 3D finite element numerical modelling of the embedded sensor-mixture medium coupling were used to study the matching error. In addition， the gyratory compaction and unconfined compressive strength tests of cement stabilized macadams with the SmartRock sensor were performed， and the sensor responses were analyzed. The results show that the stress response of SmartRock under concentrated load is much greater than that of a uniform load； provided the ratio of sensor height to bottom side length H/D is less than 0.3 and the ratio of the sensor package material to the modulus of the surrounding medium E_p/E_m is greater than 5， a low and stable matching error can be achieved； in addition， the evolution of the compaction degree and strength of the mixture can be characterized by the dispersion coefficient S_v of the stress response of SmartRock.

In order to further improve the applicability and safety of lime stabilized soil in complex environmental engineering， the mechanical properties of lime stabilized soil modified by nano clay and fiber were studied. By analyzing the unconfined compression behavior of modified lime stabilized soil under the action of dry wet cycle and freeze-thaw cycle， the modified effect of nano clay and fiber on lime stabilized soil can be judged. The test results show that fiber and nano clay can improve the compressive strength and residual strength of lime stabilized soil， increase the failure strain and change the failure mode. Especially， under the combined action of fiber and nano clay， nano clay/fiber modified lime soil （NFLS） presents the best unconfined compression behavior， and can delay the internal damage of NFLS caused by dry wet cycle and freeze-thaw cycle.

To address the problem of high slope instability due to bonding failure of prestressed anchor cables， the application of prestressed anchor cables in combination with high performance materials was proposed to improve slope resilience. Firstly， the pull-out tests of prestressed steel strands and Basalt Fiber Reactive Powder Concrete （BFRPC） were carried out in the laboratory. The bonding properties of steel strands with a nominal diameter of 15.2 mm under two slurry materials （BFRPC， M40 ordinary cement mortar） were studied， and the failure modes were summarized. Then， based on the distribution law of characteristic parameters， the damage process of reinforced concrete materials under stress state was identified. Secondly， by comparing the RA-AF values， the damage mode of steel strand-concrete during drawing process was clarified. Finally， according to the Ib-value， the stages of crack development of steel strand concrete under different stress states were identified. The results show that： the energy and amplitude law of the three stages are closely related to the damage process such as the generation and expansion of cracks inside the specimen. Through RA-AF analysis， it is concluded that shear cracks mainly occur near the interface concrete， while the macroscopic manifestation of tensile cracks is cracks perpendicular to the loading direction. When the fluctuation difference of Ib-value reaches 0.25， it can be regarded as an early warning value to warn that the prestressed steel strand-concrete material is about to split.

In response to the problem that the landslide displacement prediction models are mainly based on one-step prediction combining dynamic variables such as rainfall and deformation， and lack of consideration of static variables such as time period related to multi-step displacement influence factors. A multi-step landslide displacement prediction model integrating dynamic and static variables was proposed. First， the variable selection network was used to select the initial input variables， excavate the highly correlated variables with the daily displacement of the landslide， and weaken the influence of redundant variables on the model. Then， the static variables were integrated into the network， and the dynamic correlation of time was adjusted by encoding the context. Finally， the multi-step displacement prediction of landslide was realized by capturing the long-term dependence of time series with multi-head attention module. Taking Xinpu landslide in Chongqing as an example， the method is compared with DeepAR and Long Short-Term Memory（LSTM） models. The experimental results show that the method can achieve more robust and high-precision multi-step displacement prediction of landslide.

Aiming at the problems of non-toughness and weak disaster resistance of the anchor cable system under the condition of seismic slip on high and steep slopes， a leaf spring shock absorption anchor head structure and implementation method were proposed. The seismic working program of leaf spring anchor head was analyzed， a dynamic calculation model was constructed， and the deformation characteristics were analyzed. Based on the main influencing indicators， the scale analysis of the leaf spring anchor head was carried out， and the seismic response characteristics of the leaf spring anchor head were obtained by finite element program. The results show that the bearing capacity and deformation characteristics of the leaf spring anchor head structure are mainly determined by the aspect ratio， width-thickness ratio， span and number of plates， and are most sensitive to the thickness of the plates. With the increase of excitation peaks， the shorter the recovery time of its springback， the more energy is dissipated throughout the process. The optimal scale leaf spring anchor head seismic response Fourier main frequency is 14.73Hz， reciprocating deformation and frictional energy loss occur during the seismic response process to reduce the seismic impact effect， with good seismic performance and toughness， but the application design should comprehensively consider the deformation coordination ability， energy dissipation effect and economic factors. The research results can provide a theoretical basis and method for the design and application of slope anchor cable toughness component structure.

In view of the non-stationary and nonlinear characteristics of the slope displacement monitoring data of high-speed railway tunnel entrance and the poor prediction performance caused by random generation of initial parameters of extreme learning machine （ELM） model， an ELM displacement prediction model based on variational mode decomposition （VMD） and grey wolf optimizer （GWO） was established. The optimal decomposition number of VMD was determined by the adaptive decomposition layers of Empirical Mode Decomposition， and the displacement of periodic term， trend term and wave term were obtained by VMD. The GWO was used to search for the optimal weight matrix connecting the input and hidden layers and the threshold of the hidden layer neurons of ELM. Each subsequence was predicted and the cumulative displacement was obtained by combining the results. Example verification shows that the root-mean-square error， mean absolute percentage error and goodness of fit of VMD-GWO-ELM model are 0.3822 mm， 1.0047% and 0.9837， respectively. The VMD-GWO-ELM model has higher prediction accuracy and applicability.

Defining highway region as study area， the research subject of this paper was constructing an early warning monitoring method system for geological disaster. Combined with the characteristics of highway， eight disaster-causing factors were selected：elevation， topographic slope， surface deformation rate， rainfall， land-use， engineering geological rock formations， fault distribution and waterway distribution. Information extraction was solved by satellite remote sensing technology to input to the weights of evidence and logistic regression coupled model， in order to get expressway within the scope of the geological hazards in the calculation results. The results were divided into regions to determine the target region of early warning and monitoring. The practice subject of this method is the highway from Ya'an to Kangding in Sichuan Province. The results show that this method has a good data representation effect on the characteristics of the road research area with highway as the main body. The accuracy of early warning and monitoring of geological disasters in the road region is high， and the AUC value is 0.906. This method has certain reference and guiding significance for disaster prevention and resistance of highway traffic infrastructure.