Structures最新文献

China has been increasingly promoting the use of prefabricated timber structure buildings in recent years. However, unlike other countries, China lacks a diverse range of local tree species and engineered wood products suitable for load-bearing components in timber structures. This shortage poses a risk to the sustainable development of timber structures in China. This issue is addressed in this study, which focuses on the development and manufacture of glued laminated timber (GLT) using Chinese fir from plantation forests. The dynamic elastic modulus of 549 laminae was evaluated using the FAKOPP stress wave approach. A total of 28 laminae were randomly selected from Classes I, II, and III to assess the influence of stress grading on bending performance. This study included an analysis of failure modes, bending capacity, and the prediction model for bending stiffness of GLT with different layups and cross-sectional heights. The findings showed that the dynamic elastic modulus of the laminae followed a normal distribution. The bending strength and modulus of elasticity of finger-jointed laminae across different grades were 29.59 MPa to 37.05 MPa and 8.13 GPa to 10.94 GPa, respectively. The mechanical properties of both same-grade and mixed-grade composition GLT manufactured from Chinese fir met the TC_T28 (MOR≥28 MPa, MOE≥8000 MPa) and TC_YD24 (MOR ≥ 24 MPa, MOE ≥ 8000 MPa) garde requirements in GB/T26889, respectively. Failure modes in the GLT specimens typically began at the knots or finger joints of the bottom layer laminae. The cross-sectional height had no significant effect on the modulus of elasticity of GLT but exerted a significant effect on bending strength. The prediction model for bending stiffness, developed using the transformed section method, agreed with the experimental results. The outcome of this research provides a scientific and data-driven foundation for the application of Chinese fir in the field of structural materials.

Both of test and numerical simulation methods are employed to study the vertical progressive collapse and collapse assessment methods of steel frame under accidental loads. Firstly, a steel frame collapse test model with a geometric similarity ratio of 1:1.5 is designed and manufactured. The ends of column of test model is fixed. The upper and lower flange angle steel connection is used. The far end of the beam is constrained by a controllable sliding hinge support. The various stages of vertical progressive collapse of structures are simulated by a large displacement loads applied at the far end of the beam. The main focus of the testing is to examine the stress and deformation of beam and joint at various stages, particularly the development of stress and deformation in the angle steel attached to the beam-column connection. The development law of collapse load-displacement curve, joint rotation, beam strain, and angle steel strain are analyzed. The structural resistance mechanism and the transformation relationship between resistance mechanisms during collapse are studied. Subsequently, the relationship between the structural dynamic increase factor curve and the structural collapse process is analyzed using finite element method. The results show that the strain of angle steels can better reflect the destruction and deformation process of substructure during the collapse, the collapse resistance mechanism of structure, and the transition between resistance mechanisms.With the help of the characteristic points on the structural dynamic increase factor curve, the collapse limit state of structure can be reliably determined.

Solid wastes, including granulated blast furnace slag (GBFS) and low-carbon mushroom-corn straw mixed biomass ash (MCA), are utilized to create supplementary cementitious materials (MCG) on a 1:1 basis in place of cement in response to the Global Carbon Reduction Initiative (GCRI). This study examines the regular relationships of seven types of recycled aggregate concrete (RAC) with varying MCG substitution rates (0 %, 7 %, 14 %, 21 %, 28 %, 35 %, and 42 %). These multiscale properties include slump, strength at various ages, freeze-thaw resistance, hydration characteristics, and pore structure characteristics based on NMR. With a 28-day compressive strength of 45.6 MPa, the highest percentage of transition and capillary holes at 79.13 %, and the lowest rate of mass and strength loss at 36 freezes and thaws at 0.35 % and 17.65 %, respectively, the results indicate that MCGRC has the best overall performance at a 21 % MCG substitution rate. Furthermore, there are notable quadratic and linear correlations between the MCGRC compressive strength and the alkalinity of the pore solution and chemically binding water, respectively.

The use of yield steel dampers in structures improves seismic resilience by efficiently absorbing energy, reducing the impact of seismic forces, and enhancing overall safety and stability. This paper introduces Arc and Ring Dampers (ARDs), a replaceable structural fuse system with the goal of improving seismic performance of structures against earthquakes. The ARD configuration consists of a central ring surrounded by four arcs. For the first time, an experimental study is carried out on full-scale damper specimens to determine seismic performance and failure mechanisms under cyclic loading. Nonlinear finite element method (FEM) analysis is employed for numerical validation and parametric exploration, taking into account variables such as arc and ring thickness, ring and arc radius, and stiffener width. According to the results, by carefully selecting and designing the geometric characteristics of this damper, it would offer a remarkably efficient energy absorption capacity and a significant load-bearing ability, resulting in a 36 % increase in its equivalent damping ratio. This study also describes these geometric features in detail, including the arcs' and ring's width-to-thickness ratios. Furthermore, this damper maintains structural stiffness without degradation under cyclic loading conditions, showing good ductility up to a value of 5.5. The theoretical predictions here are in good agreement with the experimental outcomes.

Post-earthquake structural damage shows that out-of-plane (OOP) wall collapse is one of the most common failure mechanisms in unreinforced masonry (URM) buildings. This issue is particularly critical in Groningen, a province located in the northern part of the Netherlands, where low-intensity induced earthquakes have become an uprising problem in recent years. The majority of buildings in this area are constructed using URM and were not designed to withstand earthquakes, as the area had never been affected by tectonic seismic activity before. OOP failure in URM structures often stems from poor connections between structural elements, resulting in insufficient restraint to the URM walls. Therefore, investigating the mechanical behaviour of these connections is of prime importance for mitigating damages and collapses in URM structures.

This paper presents the results of an experimental campaign conducted on timber joist-masonry cavity wall connections. The specimens consisted of timber joists pocketed into masonry wallets. The campaign aimed at providing a better understanding and characterisation of the cyclic axial behaviour of these connections. Both as-built and strengthened conditions were considered, with different variations, including two tie distributions, two pre-compression levels, two different as-built connections, and one strengthening solution. The experimental findings underscored that incorporating retrofitting bars not only restores the system’s initial capacity but also guarantees deformation compatibility between the wall and the joist. This effectively enhances the overall deformation capacity and ductility of the timber joist-cavity wall system.

Masonry vaults are common structural elements in heritage buildings that, given their long lifespan, are susceptible to the accumulation of damages and deformations from diverse actions such as overloads, support movements, seismic action, etc. The use of 3D point clouds from terrestrial laser scanners and structure from motion photogrammetry survey to investigate these deformations can offer valuable information for structural assessment and conservation, particularly when historical information is limited. The analysis of the deviation measured between the surveyed as-built point cloud of a vault and a reference geometry could reveal deformation patterns. Those, compared with recurring damage mechanisms discussed in literature, can provide a preliminary identification of the damage mechanisms affecting a structure, and the evaluation guide the recognition of the underlying action. The aim of this paper is to investigate how to generate different reference geometries and the impacts of their choice as reference geometry for the identification and quantification of different deformations. Deviation analyses were performed on the main vaults of two different churches with different reference geometries (i.e., geometries derived from the survey and geometrical primitives fitted on point-cloud), and the results were discussed by comparing the deviation maps obtained with the crack pattern and the already known deformations of the buildings.

Self-resilient composite frames exhibit robust resistance to progressive collapse and excellent seismic performance. However, their behavior under fire conditions is inadequately explored. This study investigates the collapse resistance mechanisms and response of self-resilient composite frame substructures (SRCFS) under fire-induced progressive collapse. A three-dimensional finite element model was developed, incorporating temperature-dependent thermal and mechanical properties of concrete and steel. Sequentially coupled thermal-mechanical analysis was conducted using the ABAQUS/Explicit solver in a quasi-static manner. Existing experimental data at both ambient and high temperatures were used to validate the proposed model. The study analyzed the contributions of steel beams and strands to vertical resistance, examining their impact on the collapse-resistance mechanism through a constant load-heating transient loading scheme. Structural responses under ambient and fire conditions were compared, focusing on different damage mechanisms. The effects of initial prestressing of strands, angle gauge length, angle thickness, and various heating curves on collapse resistance were evaluated. Findings suggest that the ISO-834 standard's failure criterion is overly conservative for SRCFS, as it neglects the enhanced load-carrying capacity provided by tensile catenary action. This mechanism offers additional escape time, enhancing personnel safety. The study identifies factors influencing the performance of SRCFS against progressive collapse under fire and proposes design recommendations.

The seismic assessment of the out-of-plane (OOP) behaviour of unreinforced masonry (URM) buildings is essential since the OOP is one of the primary collapse mechanisms in URM buildings. It is influenced by several parameters, including the poor connections between structural elements, a weakness highlighted by post-earthquake observations. The paper presents a mechanical model designed to predict the contributions of various resisting mechanisms to the strength capacity of timber-joist connections in masonry cavity walls. The research presented in this paper considers two different failure modes: joist-wall interface failure, and OOP rocking behaviour of the URM walls. Consequently, two mechanical models are introduced to examine these failure modes in timber-joist connections within masonry cavity walls. One model focuses on the joist-wall interface failure, adopting a Coulomb friction model for joist-sliding further extended to incorporate the arching effect. The other model investigates the OOP rocking failure mode of walls. The combined mechanical model has been validated against the outcomes of an earlier experimental campaign conducted by the authors. The considered model can accurately predict the peak capacity of the joist connection and successfully defines the contribution of each mechanism in terms of resistance at failure.

Segmental assembly joints with excellent shear bearing capacity are the key to ensure the integrity of precast concrete girder bridges, which directly affects the force transmission state of the girders. However, with the existence of unfavorable factors such as the multi-key shear capacity reduction effect, the traditional prediction model for calculating the concrete joints shear capacity has poor prediction accuracy and large dispersion. To overcome the shortcomings of the existing prediction model, this study established a database consisting of 311 sets of test data and 110 sets of numerical results based on existing research. A total of seven data-driven models for predicting shear capacity of concrete joints were trained and generated based on the database, namely, two linear models (Linear Regression Support Vector Machine Algorithm, Least Squares Linear Regression) and five nonlinear models (Neural Network Bayesian Regularization; Neural Network Quantized Conjugate Gradient Model, Neural Network Levenberg-Marquardt (LM), Decision Tree, and Gaussian regression). The coefficient of determination (R²), root mean square error (RMSE)，mean absolute error (MAE), error range (A20-index), and error analysis were adopted to evaluate those model's performance. The evaluation results show that the LM model has excellent prediction accuracy, stability, robustness, and can guide the engineering design. Finally, the established database (421 data sets) and trained LM algorithm model were open sourse in this study to promot the investigate of precast concrete structures.

To achieve reasonable fire damage evaluation of concrete structures, a model-driven and data-driven fusion prediction framework is proposed in this investigation. In the framework, finite element method (FEM) coupled with a thermo-mechanical damage model is used to provide forward response calculation of concrete structures under the combined action of high temperature and external forces. Kernel extreme learning machine (KELM) is utilized to invert the thermal and mechanical performance parameters in finite element computation with aid of the measured response data. Additionally, sand cat swarm optimization (SCSO) algorithm is utilized to improve inversion performance. Fire damage of a concrete column and a concrete frame structure is studied and compared with the corresponding experiments. Through comparison, it can be found that the fire damage simulation of the two examples can match well with the corresponding experimental results. The results support that the proposed model-driven and data-driven fusion prediction framework with aid of KELM coupled with a SCSO and FEM coupled with a thermo-mechanical damage model can be utilized to support a useful tool for fire damage prediction of concrete structures.