Search

To reduce carbon emissions in the construction industry, more and more researchers have paid attention to engineered bamboo, a natural and green material. This research focused on laminated flattened-bamboo (LFB), a new bamboo composite produced by the advanced non-notched flattened-bamboo technology which can improve the utilization rate of bamboo and reduce production costs by reducing the use of adhesive compared with the gluing process of conventional bamboo laminates. The basic mechanical properties under compression, tension, three-point bending, and shearing of LFB in three orthogonal directions were mainly studied. Experimental results showed that compressive and tensile strength (modulus) along the grain direction were 56.2 MPa (9,542.7 MPa) and 106.9 MPa (10,151.1 MPa), respectively; in the radial direction were 43.1 MPa (580.9 MPa) and 1.8 MPa (1,459.6 MPa), respectively; in the tangential direction were 19.0 MPa (1,124.5 MPa) and 4.3 MPa (5,112.5 MPa), respectively; the mean bending strength (modulus) was 80.8 MPa (8,076.8 MPa), and the shear strength (modulus) was 17.3 MPa (1,878.8 MPa). The measured properties were comparable to that of other structural bio-based materials, showing LFB has the potential to be an alternative to timber in future construction applications. The modulus and Poisson's ratio was analyzed, and the result showed that LFB could be regarded as orthotropic material approximately. The failure types under various loading conditions were summarized. Based on the Ramberg Osgood relation, the stress-strain models of LFB composite under compression, tension, and shearing were proposed, and the characteristic value of ultimate strength and elastic modulus was determined by parametric analysis. [ABSTRACT FROM AUTHOR]

Because drainage network data is unavailable in many urban areas, the accuracy of urban flood simulation may be reduced. A linear reservoir method is proposed to characterize the drainage capacity of a pipe network, and a high-resolution hydrodynamic model of an urban surface and drainage pipe network is developed. Remote sensing satellites, design specifications, and other methods were combined with actual surveys to identify storm wells and generalize underground drainage systems. A high-resolution digital elevation model (DEM) that can represent the microscopic characteristics of the urban surface was used as an input. The process of water accumulation was investigated in the study area, and the results were validated with measured data. The results show that the simulated data agree well with the measured data. Overall, the model and method can quickly and accurately simulate large-scale high-resolution urban rainfall-runoff processes. [ABSTRACT FROM AUTHOR]

Experimental tests were conducted on composite rock-concrete specimens with four roughness profiles to investigate the propagation of interfacial cracks under three-point bending and four-point shear conditions. By measuring the initial fracture loads, various combinations of interfacial stress intensity factors (SIFs) of Modes I and II corresponding to the initial fracture conditions were determined. Based on these results, an expression for classifying the initiation of interfacial cracks in mixed Mode I-II fracture was derived by normalization, which could eliminate the effect of interfacial roughness. Furthermore, a criterion for specifying propagation of the interfacial crack that takes into account nonlinear interfacial characteristics was proposed, which indicated that the crack would start to propagate along the interface when the SIFs caused by the external loads and the cohesive stresses satisfied this criterion. Numerical simulations of the interfacial fracture process were also conducted, introducing the crack propagation criterion to predict load–versus crack mouth opening displacement (P-CMOD) curves. They revealed fairly good agreement with the experimental results. Finally, by combining the criterion for maximum circumferential stress with the proposed criterion for crack propagation, the interfacial crack propagation mode was assessed. The results indicated that, once the initial fracture toughnesses for the rock, the concrete, and the rock-concrete interface from the experimental work were obtained, the propagation of interfacial cracks and the corresponding fracture modes, including nonlinear characteristics of the materials and interface, could be predicted using the method derived in this study. [ABSTRACT FROM AUTHOR]

Long-span and wide railway bridges are loaded with various loading cases, and the structural dynamic amplification factor (DAF) corresponding to different loading cases has great variability. This study presents an approach to obtaining DAF under different loading cases. Then the approach is applied to the analyses of DAFs from long-term monitoring data. The usual values of vibration amplitude and DAF under eight single-train loading cases during long-term operation are analyzed, and the midspan amplitude and displacement DAF of the main girder under the typical two-vehicle intersection, three-train intersection, and four-train intersection loading cases are also investigated. The correlation between the DAF of the eight loading cases, the structural temperature, and the train speed under the single-train loading case is analyzed. The obtained results show that in the long-term operation, the vibration amplitude level and DAF level of the railway bridge are mainly related to the train loading case, and in 16-carriage loading cases, the DAF value is higher than that in eight-carriage loading cases in the same line. The vertical dynamic response of the midspan main girder under each working condition is small. Furthermore, depending on this evolution law, different traffic loading cases must be considered during the assessment of dynamic performance. [ABSTRACT FROM AUTHOR]

Modal frequencies are widely used to capture dynamics and reveal possible failures of bridge structures. However, the non-Gaussianity and nonlinearity of nonstationary modal frequencies associated with the actual structure under changing environmental conditions often restrict the application in structural health monitoring. Therefore, a new localized frequency cointegration without environmental measurements for the elimination of environmental interference and damage warning is proposed in this paper. The k -nearest neighbor rule is first employed to search for sufficient nearest neighbors for each modal feature based on similarity measurements over a wide range of training data. After that, the cointegration analysis associated with the Johansen procedure is performed to remove environmental trends and obtain multivariable cointegration residuals. Then, the defined early warning index (i.e., the weighted Mahalanobis distance) derived from the exponentially weighted moving average is adopted with respect to the identification of subtle damage. Eight groups of cointegration models between nonstationary modal variables are constructed and validated on the Z24 bridge case. The results demonstrate that the proposed approach can successfully discard spurious influences of environmental variations and identify the occurrence of real structural damage compared to traditional methods. Additionally, this approach is not constrained by the statistical distribution of observation samples, and the selection and combination of different modal orders are crucial in capturing the changes in frequency anomalies for the bridge condition assessment. [ABSTRACT FROM AUTHOR]

In this study, nano- SiO2 was synthesized using the sol-gel method to modify the properties of fly ash-slag geopolymers (FASGs). FASGs with six contents of sol-type nano- SiO2 (0, 0.1%, 0.2%, 0.3%, 0.4%, and 0.5%) and two alkali dosages (5% and 7% of Na2O) were prepared. The influences of sol-type nano- SiO2 and alkali content on the compressive strength, flexural strength, drying shrinkage, and microstructure of FASG were studied. The results demonstrated that the early-age compressive and flexure strength of FASG can be enhanced by sol-type nano- SiO2 due to the improved microstructure and the reaction products. The improvement effect of sol-type nano- SiO2 on mechanical properties was more significant for FASGs with lower alkali dosages. The optimized content of sol-type nano- SiO2 in FASG was 0.2% for the mechanical properties. The addition of the sol-type nano- SiO2 can mitigate the drying shrinkage of the FASG when the content is lower than 0.4%. The sol-type nano- SiO2 can promote the formation of reaction products in FASG and result in a denser microstructure of FASG. [ABSTRACT FROM AUTHOR]

Environment-induced nonlinear and seasonal variabilities in modal frequency are still a major challenge for bridge damage detection and condition assessment. Almost all techniques focus on the method's improvement and ignore its linear or multivariate Gaussian distribution assumptions with unsatisfactory detection accuracy. Little attention was given to the feasibility of environmental suppression before damage detection. A data-driven modal equivalent standardization (MES) method is developed without environmental measurements. The nearest neighbor modal set is first searched from the bridge modal baseline training database based on a similarity measure that corresponds to several smaller Euclidean distances. Then, the MES method is implemented by the localized mean and standard deviation. After this analysis, a damage detection model based on the slow feature analysis is established. A real bridge case verifies the method's validity in an environment-tolerant capacity, Gaussification of data distribution, and modal variable linearization, which outperforms global data standardization for damage detection. [ABSTRACT FROM AUTHOR]

Because bridge modal frequency is inevitably influenced by environmental factors, and single-order frequency is possibly insensitive to some damage conditions, frequency anomaly detection will fail. Therefore, conducting overall multiorder modal frequency anomaly detection is essential considering multiple environmental factors. This paper focuses on identifying multiorder modal frequency anomalies from the perspective of probability. The Gaussian process regression (GPR) model is first established to map the multiple environmental factors to the modal frequencies, whose prediction results consist of frequency estimations with uncertainties. Then, the single- and multiorder modal frequency anomaly characteristic indices are derived by conditional probability and Bayes' theorem, respectively. Multiorder modal frequency anomaly detection is finally conducted after setting a threshold value. Two groups of GPR models with temperature and environmental inputs are verified in a cable-stayed bridge case. The proposed anomaly detection method can take into account the insensitivity of low-order frequencies to simulated frequency reduction conditions and accurately identify anomalous frequencies affected by multiple environmental factors. [ABSTRACT FROM AUTHOR]

Bridge modal frequency is an important parameter reflecting its overall property change and widely used for bridge condition assessment. However, the effects of multiple environmental conditions on the modal frequency will mask the variation induced by structural damage. Traditional single regression models cannot quantify measurable and unmeasurable environmental effects simultaneously, resulting in poor prediction and separation performance. Therefore, a two-stage elimination model (TSEM) integrating regression analysis and trend decomposition technique was developed. Environmental principal components (PCs) sensitive to the single-order modal frequency were extracted based on partial least-squares analysis. To quantify the nonlinear effects of measurable environmental factors, the baseline predictor with respect to modal frequency and environmental PCs was constructed through relevance vector machine technology. An error compensation model based on singular spectrum analysis was established to extract trend-related components and remove the part of residual modal variability unknot considered by the baseline model. On this basis, exponential weighted moving average control chart was established to highlight slight abnormal changes in modal frequency. A cable-stayed bridge case verified its validity and accuracy. The results indicate that the proposed TSEM has better modeling, generalization, and separation performance than the baseline model, and the variation of normalized frequency tends to be more stable. Additionally, the significant differences of damage sensitivity of different orders were determined. [ABSTRACT FROM AUTHOR]

Detection of potential damage is of great significance for aging railway bridges. In this paper, a damage location method for beam railway bridges based on the rotation response to operational train loading is presented. The method is based on deformation area analysis of the operational rotation response of bridges to the passage of trains. The theoretical basis of this method is elaborated. The calculated deformation curvature area difference ratio (CADR) change is used to identify damage in bridges. To obtain the curvature area, a technique is proposed for the curvature area calculation. The results are presented in terms of the damage condition extracted from each ratio, which was obtained by dividing the deformation area from the current interval to the sum of the areas from all the intervals. The location of damage was identified by observing the magnitude of the changes in the CADR. Finite element models were utilized to verify the method. The influences of train-track-bridge interaction and environmental temperature changes were considered. The calculation process is given for the application of the proposed method to the damage location of railway bridges. Thereafter, vehicle-bridge models with different parameters are investigated. The results show the capability of the method. [ABSTRACT FROM AUTHOR]

With an increase in bridge service time, damage will inevitably occur. Accurately identifying damage is of great significance to the operation and maintenance of a bridge. To realize a frequent identification of local stiffness reduction caused by structural damage in operation, this paper proposes a new method for damage localization of short-span bridges based on the axle weight time history identified by bridge weigh-in-motion technology. This method is based on a least squares QR decomposition recursive algorithm, and the orthogonal matrix is updated by the newly added measured rotation response and the axle weight identified in the previous step to recursively obtain the current axle weight. Then, the axle weight time history is obtained and the damage is located according to the mutation of axle weight time history caused by the first axle passing through the damage. The accuracy and applicability of the proposed method are verified by a numerical model of a simply supported beam. The results show that the axle weight time history has a strong sensitivity to damage, and the average normalized axle weight time history can accurately locate the damage and significantly reduce the impact of environmental noise. This method can be used for long-term health monitoring of bridge structures. [ABSTRACT FROM AUTHOR]

Due to the influence of multiple environmental factors, bridge frequencies can vary with time, which can affect the frequency variations that cause structural damage. However, the nonlinear effects of multiple environmental factors and other uncertain effects on structural frequencies cannot be properly considered, which is a major obstacle to achieving bridge damage detection based on structural frequency variations. Therefore, this paper focuses on establishing an appropriate mapping model between modal frequencies and multiple environmental factors, which can consider such nonlinear and uncertain effects simultaneously. Principal component analysis integrates the features of long-term environmental monitoring data into several principal components. To address nonlinearity and uncertainty in modeling, a Gaussian process regression model with principal components as inputs is developed to estimate the modal frequency distributions. Four groups of models with different inputs are validated in a cable-stayed bridge case. The proposed modeling method can map multiple environmental factors onto modal frequencies by considering both nonlinearity and uncertainty and accurately describe the environmental impacts on frequencies based on monitoring data. [ABSTRACT FROM AUTHOR]

The influence line is an important static property in bridges. The shape and magnitude of the girder bridge influence line contain stiffness information for the bridge supports and beam. This research sought to directly identify the rotational stiffness of bridge supports and the flexural stiffness of beams from extracted influence lines, which provides a quantification method for bridge damage and performance degradation. The paper first reviews the influence line identification method from vehicle-induced bridge responses. Then, the complete theoretical formulations of the deflection, rotation, and strain influence line for a general girder bridge are derived. Based on these derivations, the rotational stiffness at two supports and the equivalent flexural stiffness value of the beam are identified. Next, a certain span of a continuous girder bridge is converted to an equivalent simply supported system, and the flexural stiffness distribution of the beam is estimated based on the bending moment-curvature relationship and Betti's law. The paper then presents a three-span continuous girder bridge verification example. The stiffness estimation results under different test conditions combined with the bridge influence line identification algorithm are presented to verify the reliability of the proposed method. This stiffness estimation method can be applied to baseline-free bridge performance evaluations based on vehicle-induced bridge responses. [ABSTRACT FROM AUTHOR]

Moving forces are one of the major loads acting on bridge decks, and moving force identification (MFI) is essential for bridge safety. However, there are two shortcomings in existing MFI methods. First, time discrete sampling for the force leads to ill-posedness in MFI. Second, identifying moving forces by means of a fixed frequency and a single type of force dictionary cannot fully and sparsely represent these forces. To address these issues, basis functions containing a trigonometric function and variable-frequency rectangular function are used to sparsely express the force, and the Duhamel integral is used to avoid ill-posed reduction of time discrete sampling for the force. A generalized discrete estimating method (GDEM) is proposed to identify moving forces. The l1-norm regularization method in a sparse solution is introduced to transform the force identification problem into an l1-norm regularization solution problem. The fast-iterative shrinkage threshold algorithm (FISTA) is used to solve the l1-norm regularization problem, and the coefficient of the basis functions is obtained by combining the Bayesian criteria to identify the force. To validate the GDEM, the single and double time-varying forces on a simply supported beam are identified by numerical simulation. The results illustrate that the GDEM can accurately identify moving forces with strong robustness and performs better than the dictionary method. The response combinations of MFI are also discussed. [ABSTRACT FROM AUTHOR]

Structural health monitoring represents an efficient way to diagnose the condition of cable-stayed bridges. Most studies assessing the condition of cable-stayed bridges and detecting damage to them have been developed to monitor the longitudinal performance of bridge bearings. However, few studies have aimed to detect the damage to tension pendulums, which are usually tie-down cables that resist girder uplift from auxiliary piers. This study aims to develop an effective method for detecting the damage of tension pendulums in cable-stayed bridges using structural modal frequencies. First, the sensitivity of the bridge frequency to tension pendulum damage is derived according to the Rayleigh method. Then, a finite-element simulation of a cable-stayed bridge is conducted to validate the rationality of the frequency index. Finally, a case study on tension pendulum damage is carried out for the cable-stayed Yonghe Bridge. The results indicate that the frequency change is far more sensitive to the damage of the tension pendulums than to the damage of the stay cables. The failure of tie-down cables will result in a substantial decrease in the bridge frequency, up to approximately 35% for the first vertical bending mode of the bridge. In practice, the damage of tension pendulums can be effectively detected by a sudden decrease in the measured frequency of cable-stayed bridges. [ABSTRACT FROM AUTHOR]

Urban public security incidents are prone to occur. Better understanding of pedestrian abnormal behavior and trajectory in crowded places is conducive to crowd management and safety monitoring. A novel pedestrian abnormal behavior detection model (PABDM) is proposed to identify crowd behavior under abnormal scenarios. This model originated from a multiscale fusion you only look once (YOLO) version 3 (V3) algorithm and was trained using the PASCAL visual object classes (VOC) in combination with an abnormal pedestrian data set (APD), denoted as VOC+APD. Compared with YOLOV3-VOC, single-stage detectors (SSD)-VOC, and SSD-VOC þ APD, the proposed model has notable advantages in prediction accuracy and detection efficiency. The results show that the network loss function of the model tends to be stable after 500 epochs, and its detection accuracy is 6% higher than the average accuracy of the compared models. This proposed model also effectively solves the problem of missing detection caused by edge target, fuzzy target, and small target in abnormal state human detection. The research results are of great significance for real-time crowd monitoring in complex scenes. [ABSTRACT FROM AUTHOR]