Abstract:On basis of the probability density evolution theory and stochastic damage mechanics of concrete， a class of stochastic modeling principle is established from the perspective of probability density. In the context of concrete biaxial strength tests， a method is proposed to solve the inverse problem of probability based on the genetic algorithm. Utilizing the test data and the proposed method， the statistical parameters of fracture strain in the elastoplastic stochastic damage model for concrete are identified， and the basic parameters of the model are obtained. It is demonstrated that the identified parameters can faithfully capture the randomness of concrete strength at both probability density and statistical moment levels. The study of this paper aims to provide a new road for solving the inverse problem of probability.

Abstract:Laboratory scale tornado was generated with tornado vortex simulator， and the reliability of the simulated tornado was also verified. On this basis， wind-force measurement tests with high frequency force balance （HFFB） for typical transmission tower head model was completed under tornado wind fields with two kinds of swirl ratio. The distribution characteristics of the aerodynamic coefficients of tower head under tornado were studied. Moreover， the unique torsional effect of the tower head under tornado was also analyzed. The experimental results show that， the simulated tornado vortex matches well with the measured tornado. The maximum horizontal force coefficients of the tower head occur near the positions of 1 to 1.5 times the radius of the vortex core. The lift coefficient is generally smaller than the resistance coefficient under the corresponding conditions. Compared to the aerodynamic coefficient in the wind-axis coordinate system， the aerodynamic coefficient in the body-axis coordinate system is more sensitive to the wind angle. The difference in the most unfavorable wind angle among different aerodynamic coefficients is also significant. In addition， due to the strong tangential wind velocity of tornadoes， the tower head model with long cross-arm will experience an undeniable torsion effect when located inside the tornado， and the torsion coefficient increases with the decrease of swirl ratio.

Abstract:To study the mechanical properties of orthotropic steel-concrete composite bridge deck with big U-ribs. The orthotropic steel bridge deck with a U-rib opening width of 450mm was chosen as the research object in which ultra-high performance concrete was introduced. Two full-scale big U-rib steel-concrete composite bridge decks are tested to evaluate the static bearing capacity including the strain of concrete and steel bars， the deformation of the structure and the development of cracks. And parametric analysis is carried out based on the finite element model of UHPC plastic damage. The results showed that the thickness of the big U-rib in the bridge deck was increased from 8mm to 10mm， the yield load and ultimate bearing capacity were arisen by 24.86% and 47.48%， the number of concrete cracks in the pure bending section was reduced， and the crack spacing increased. The effect of the thickness of the troughs on the static performance of the structure is mainly reflected in the nonlinear stage. The parametric analysis results showed that when the cross-sectional configuration of the 450-level big U-rib structure were changed， the buckling deformation capacity of the structure were influenced differently. Changing the thickness of the top plate of the structure has less influence on the safety factor in ultimate state， while increasing the thickness of the U-rib could significantly increase the safety factor of the structure. Based on the experimental results and FEA， an empirical formula for the buckling reduction coefficient of 450-level big U-rib steel-UHPC composite bridge deck is proposed， which is more related to the height-thickness ration of U-rib and width-thickness ratio of U-rib bottom plate.

Abstract:Understanding the anticipated behavior of bridge structures is crucial for early identification of potential structural issues or failure modes. This paper proposes a novel predictive framework for bridge structural performance based on Long Short-Term Memory Networks （LSTM）. The block maxima （BM） method is employed to extract hourly deflection extremes from monitoring data， which serve as key indicators for assessing bridge safety. The method involves sliding window LSTM predictions for periodic deflection extreme sequences， integrating Singular Spectrum Analysis （SSA） and error-updating Bayesian Dynamic Linear Models （BDLM） to effectively extract long-term trends and cyclic deflection changes caused by environmental factors. This process effectively reduces the impact of noise while preserving the critical information of vehicle load effects. Applications in three real engineering cases demonstrate that proposed method significantly improves prediction accuracy compared to sliding window LSTM and BDLM approaches. Furthermore， the paper proposes a dynamic warning threshold setting method based on extreme value theory， which effectively avoids the limitations of static warning indicators and utilizes the confidence intervals of predictions for proactive warning.

Abstract:Reinforced concrete （RC） columns have different failure modes under earthquake excitations. The damage state quantification methods of RC columns under different failure modes have problems including inconsistent quantification procedure， and poor prediction accuracy. Therefore， an energy equivalence principle was proposed in this study to quantify the damage states of RC columns under different failure modes using quasi-static experimental data of 246 RC columns with rectangular cross-sections. The Bayesian neural network was introduced to develop the drift angle prediction models for RC columns independent of failure patterns. The research results indicated that the energy equivalence principle can transfer the backbone curves of RC columns into an idealized elastic-plastic model. This not only facilitates the definition of yield point， peak point and ultimate point， but also benefits to compare the seismic performance of RC columns under different failure modes in a unified framework. The damage states of RC columns under different failure modes can be categorized into four groups， namely basic intact damage stage， slight damage state， moderate damage state and sever damage state using the drift angle at yield point， peak point and ultimate point. The Bayesian neural network model can predict well the drift angles of RC columns independent of failure modes at yield point， peak point and ultimate point. The traditional empirical factor method by reducing the peak strength tends to underestimate the drift angle at yield point， and overestimate the drift angle at ultimate point.

Abstract:The paper regards the tunnel as a thin-walled ring structure with four deformation modes， including bending， shearing， warping and flattening， on elastic foundation， by introducing the Generalized Beam Theory and three-dimensional soil reactions. The finite element solution of the proposed soil-tunnel model considering coupled transverse and longitudinal actions is derived. The effectiveness of the model is verified by two case studies. Furthermore， the effects of tunnel width-to-thickness ratio and soil resistance coefficient on the transverse and longitudinal behaviours of the tunnels are obtained by parametric analysis. The results show that： The effect of warping and flattening on tunnel with large diameter are significant under high-stress external load， where the cross-section presents a typical form of "horizontal duck egg" and the warping aggravates the longitudinal strain of the tunnel with more than 30% increasing. The smaller the thickness to diameter ratio of tunnel is， the larger the transverse and longitudinal deformation are. The increasing amplification can reach about 30%. The longitudinal behaviors of the tunnel are more sensitive to tangential soil resistance coefficient than the normal coefficient， while the cross-sectional performance is equally sensitive to bidirectional soil resistance coefficient.

Abstract:In order to explore the spatial distribution characteristics， pollution status and sources of heavy metals in farmland soil downstream of a heap leaching field， 152 soil samples were collected from 76 sampling points at 0.2 m and 0.5 m depths， and the contents of 8 metal elements such as Cu， Zn and Cr were determined. The pollution level was evaluated by single factor pollution index method and Nemerow pollution index method， and then the pollution sources were analyzed by principal component analysis， absolute principal component-multiple linear regression （APCS-MLR） model and UNMIX model， and verified by geostatistical analysis. The results showed that the average contents of Cr， Pb， As and Hg in the soil exceeded the soil background values in Yunnan Province， and the proportion of As content higher than the background value and the screening value exceeded 90% and 70%， respectively. The results of UNMIX model analysis showed that there were four main sources of heavy metal pollution. Source 1 is the mining development and traffic source， which contributed 65% and 56% to As and Pb， respectively. Source 2 is the source of agricultural activities， and the contribution rate to Cd was 91%. Source 3 is the natural source， and the contribution rates of Cu， Zn， Cr and Ni were 63%， 61%， 62% and 55%， respectively. Source 4 is the coal-fired source， which contributes 94% to Hg. The analytical results of APCS-MLR model were basically consistent with those of UNMIX model， but the natural parent material source was not identified alone. The above results can provide technical support for the precise implementation of farmland ecological environment management， and provide theoretical basis for mine pollution prevention and improvement of mining process.

Abstract:Chinese ancient bridge engineering has a long and abundant history， and can well reflect historical features and regional culture of China. However， the performance of the existing ancient bridges has been degraded because of the long-term service and the evolution of natural environment. Especially in recent years， with the intensification of climate change， more ancient bridges have been being damaged， which makes the relevant protection in urgent need. Statistics show that scour causes long-term adverse effect to the foundation and wholistic structure， limiting the service life of ancient bridges. During ancient times， based on the qualitative understanding of the scour， some countermeasures were created and applied， according to the different hydrological and geological conditions. In this paper， combined with the present criteria for the occurrence and development of scour， the mechanism and protection benefit of countermeasures， such as cutwaters， riprap-foundations and pilings， which were adopted by three representative existing ancient bridges， are analyzed. Furthermore， the protection effect index is proposed from three aspects including disaster types， the application scope and the service performance. Besides， the criterion is improved by service performance index， based on which some suggestions are provided for the protection and repair work of ancient bridges.

Abstract:In view of the current situation of airfield operation and the needs of managers， combined with the "Smart Civil Aviation Construction Roadmap" and the future technological development trend of technology， a clear vision for the operation of smart flight areas at airports has been established . On this basis， the framework of smart smart areas is further interpreted. Smart areas is based on physical elements and supported by functional systems and organized into relevant service modules to， finally ensuring the realization of operation vision. What’s more， the development directions of smart areas in the aspects of scene operation， facility maintenance， ground service， emergency rescue and energy security are systematically analyzed， and a service organization model that effectively supports the safety， efficiency， benefit and environmental protection is proposed， which have important significance for guiding the research and application of smart airfield.

Abstract:To overcome the unstable results of bus operation status evaluation among different cities， the Natural Breaks was used to cluster the order statistics of bus travel speeds and determine the critical speed. The optimal classification of the bus operation state was determined according to the Goodness of Variance Fit and its increment. The critical speed， percentile， and ratio to bus free-flow speed are taken as the classification parameters to evaluate their stability. The research results show that： Dividing bus operation states into four categories is a sound choice， corresponding to the congested， slow， smooth， and free-flow states， and three critical speeds， e.g.， congestion， smooth， and free-flow speeds. The ratio between bus travel speed and free-flow speed should be the best parameter to recognize bus operation states. The ratios of the congestion and smooth speeds to the free-flow speed are 1/3 and 2/3， respectively. Taking the ratio between bus travel speed and free-flow speed R_BF as the evaluation parameter， when 0≤R_BF<1/3， the urban bus system is in congested status； when 1/3≤R_BF<2/3， it is in slow status； when 2/3≤R_BF， it is smooth.

Abstract:In an attempt to investigate the seasonal characteristics of longitudinal irregularity of the ballastless track in high-speed railways， this study utilized actual data collected from the high-speed comprehensive trains to analyze the longitudinal irregularity of China Railway Track System （CRTS） I， II， and III ballastless tracks in different types of sections during the four seasons. The impact of seasonal changes on the longitudinal irregularity was quantitatively evaluated using the seasonal index. Considering the seasonal characteristics， a seasonal index adjusted moving average model， and a Long Short-Term Memory （LSTM） model in the field of deep learning were applied to predict the longitudinal irregularity of CRTS III ballastless track. The results show that the longitudinal irregularity of CRTS series ballastless track has obvious seasonality， with higher values in the summer than in other seasons. The longitudinal irregularity of curved sections is more affected by seasonal changes than that of straight sections， while the longitudinal irregularity of bridge sections is more affected by seasonal changes than that of embankment sections. Both the seasonal index adjusted moving average model and the LSTM model can predict the longitudinal irregularity of ballastless track， with the latter showing better predictive performance.

Abstract:Based on intelligent engineering technology， precise identification of track defects and quantified repair issues， combined with deep learning and computer vision techniques， a method for fine-grained image recognition and intelligent evaluation of rail surface defects has been proposed. Rail surface Defects dataset （named RD-1 094 dataset） was established by collecting images of rail surface defects and realizing fine-grained annotation of defects. The target density of the dataset reaches 22.9 targets （defects） per image. Moreover， a target detection algorithm with the ability of deep-learning for rail surface defects was established. Through training and learning to the RD-1094 Dataset， it achieved millimeter-level fine-grained recognition， such as realizing the recognition of spalling with size in 0.5 ~ 30 mm， corrugation with a wavelength in 20 ~200mm and other rail defects with their own growth situation. The algorithm has good generalization compatibility on single or double row corrugations， small or dense spallings in different levels， fatigue cracks with a single piece or with obscure distribution on the rail surface. It can measure the shape and localization of contact band on the rail surface， the size of the defects， the total number of defects in different levels， cracking area， the wavelength of corrugation and other quantitative evaluation metrics.

Abstract:A rotor system model was built based on ANSYS，which is used in the hydrogen circulation pump for fuel cell vehicles. Through the modal analysis of the rotor system， the first six natural frequencies and vibration modes of the single rotor system and the dual rotor system were obtained. Based on the modal analysis， the harmonic response characteristics of the rotor system were analyzed. The results show that the vibration deformation at the shaft end and rotor is relatively serious， and the vibration response amplitude is the largest when the vibration frequency is near the first three natural frequencies （960Hz）. The coupling effect will cause the rotor system to appear more complex vibration modes， and the rotor response to the unbalance is more significant. The research will provide a positive reference for the design， manufacturing， and vibration characteristic estimation of the hydrogen circulation pump rotor system， and lay the foundation for the study of the dynamic characteristics of the hydrogen circulation pump.

Abstract:To improve the reliability of train electro-pneumatic brake system， an adaptive degradation condition prediction method for electromagnetic coils of electro pneumatic （EP）valve， considering multi-phase dynamic changes of degradation trend， is proposed. First， the accelerated degradation test data and exponential fitting form are used to derive the state and observation equations of the extended Kalman filter （EKF） algorithm. Second， the EKF algorithm is used to obtain the optimal estimation of degradation data， reducing the interference caused by uncertain volatility of degradation data. Third， the original degradation model is established based on the optimal estimation of historical data， and the interaction between the predictions and observations of the next degradation phase is used to update the degradation model. In the end， adaptive forgetting factors are used to adjust weights of historical data and new observations after EKF optimal estimation， and adaptive updates of degradation model are accomplished through multi-phase degradation modeling. The verification results show that the proposed approach can accurately and effectively achieve multi-phase continuous degradation prediction； the proposed weight adjustment strategy with adaptive forgetting factors can significantly improve the accuracy of degradation prediction.

Abstract:To improve the ability to cope with material supply delay interference in aircraft assembly， this paper studies the dynamic scheduling problem of aircraft assembly line under material supply delay. By analyzing two types of information， material delivery determinacy， and predictability， the jobs are classified into four categories for scheduling decisions. A periodic rolling scheduling framework and a corresponding mathematical optimization model based on time and event mixed driving are established. An improved discrete particle swarm optimization algorithm is designed for this problem， which embeds Levy flight and discretization decoding mechanisms into the algorithm for the rolling scheduling model solution. The results of numerical experiments show that the proposed scheduling method can fully utilize material supply information， make predictive decisions while determining decisions at this stage， and can more effectively cope with various types of material supply interference compared with other dynamic scheduling methods， meeting the needs of aircraft assembly dynamic scheduling.

Abstract:Based on an effective sampling strategy named the maximum distance rule， a greedy two-subspace extended Kaczmarz method is proposed for solving coherent linear least-squares problems. Theoretical analysis gives the convergence rate of the greedy two-subspace extended Kaczmarz method and the tighter upper bound of the convergence rate of the two-subspace randomized extended Kaczmarz method. Numerical experiments show that the greedy two-subspace extended Kaczmarz method outperforms the two-subspace randomized extended Kaczmarz method and the random double block Kaczmarz method in terms of the number of iteration steps and CPU time.

Abstract:This study aims to predict consumption changes， which can help precise policymaking， further promote the recovery of consumption. Based on 485 million truck crossing records generated by highway toll stations in Fujian Province， we combed monthly truck flow data from 2017 to 2023 within Fuzhou City， as well as between it and 8 other prefecture-level cities in Fujian Province. Firstly， we summarize the time-series and cross-sectional features to analyze the correlation between truck flow and consumption. And then we use regression model to examine the correlation differences before and after 2020. Furthermore， we select the truck flow indicators with higher correlation in the above analysis， using Ordinary Least Squares （OLS） method and Vector Autoregressive （VAR） model to construct a prediction model of the Total Retail Sales in Fuzhou City. The results indicate that the truck flow and the total consumption of Fuzhou City show a similar trend， growing steadily before 2020 and declining significantly afterward. And the year-on-year percentage of both are highly correlated. The empirical results show that the truck flow from most prefecture-level cities into Fuzhou City is positively correlated with the total retail sales of Fuzhou City， and this correlation is weakened after 2020. Compared with the OLS method， the multivariate VAR model has a higher prediction accuracy with its probability of absolute error less than 1 pct reaching nearly 95%， which allows for the advance prediction of the monthly total consumption in Fuzhou City.

Abstract:This research uses the project data of new expressways from 2012 to 2018 to explore the efficiency and mechanism of expressway construction to promote common prosperity. The empirical results show that expressways can achieve common prosperity by increasing the income level of residents and narrowing the income gap， and urbanization and industrial structure upgrading play an intermediary role. This study shows that although the marginal benefits of highways on the income level are diminishing， the marginal benefits on the income gap between residents are increasing. The contribution of this paper is to deepen the theory of the realization way of common prosperity and demonstrate the necessity of "moderately advanced construction" expressway.