Qun Xie

To establish the restoring force model of the cross-slanted self-buckling-restrained corrugated steel plate shear wall (hereafter abbreviated as CCSPW), finite element parametric analysis was conducted on the hysteretic behavior of the CCSPW by considering four key influencing factors: the axial compression ratio, aspect ratio, inclination angle, and end plate thickness. Based on the obtained hysteresis curves and skeleton curves, the skeleton curves were dimensionlessly normalized and regression-fitted to establish a trilinear skeleton curve model together with the functional expressions for each loading stage. Furthermore, the stiffness-degradation laws of different loading and unloading paths were analyzed, and the corresponding stiffness-degradation functions were proposed to construct the restoring force model of CCSPW. The restoring force model was verified by comparing the calculated results with the finite element analysis results. The results indicate that CCSPW exhibits favorable energy-dissipation capacity and high bearing capacity; in particular, the energy-dissipation capacity weakens for the specimens with small aspect ratios, for which noticeable pinching of the hysteresis curves is observed. The proposed restoring force model is in good agreement with the finite element results, providing a theoretical reference for the seismic analysis of this shear wall.

Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and an improved ellipse-fitting method are employed for sub-pixel edge extraction, and a five-level Gaussian pyramid structure is introduced to accelerate the matching speed. Experimental results show that the proposed method achieves high-precision displacement monitoring under sufficient illumination, and it maintains stable target localization and displacement quantification performance under conditions of noise interference and extremely low illumination. Notably, under salt-and-pepper noise interference, although YOLOv8n maintains a high level of localization confidence, the accuracy of gradient matching deteriorates, resulting in a root-mean-square error (RMSE) of 0.035 mm. This finding reveals the differential impact of various noise types on different stages of the algorithm. The proposed method offers a novel technological approach for precise structural displacement monitoring in complex environments.

A novel thermal conductivity prediction model was developed to address the complex influence of pore structure in porous materials. This model incorporates pore size (d) and a pore distribution parameter (t) to calculate the material’s thermal conductivity. To validate the model’s accuracy, geopolymer foamed concrete (GFC) samples with varying pore structures were fabricated. These utilized ground granulated blast furnace slag (GGBS) as the precursor, a mixed solution of sodium hydroxide (NaOH) and sodium silicate as the alkaline activator, and sodium stearate (NaSt), hydroxypropyl methylcellulose (HPMC), and sodium carboxymethyl cellulose (CMC-Na) as foam stabilizers. Conventional pore size characterization techniques exhibit limitations; consequently, this research implements a high-fidelity machine vision-driven image analysis methodology. Pore size measurement is achieved through a combined technical approach involving equivalent diameter modeling and morphological optimization. The feasibility of the proposed theory is validated by our experimental data and data from previous literature, with the error between experimental and theoretical values maintained within 5%. The value of t increases with increasing porosity and increasing disorder in pore distribution. Based on the experimental data obtained in this study and the research data from previous scholars’ studies, the t value for porous materials can be categorized according to porosity: when porosity is approximately 30%, t ≈ 0.9; when porosity is 55~65%, t ranges from 1.2 to 1.3; and when porosity is approximately 80%, t ranges from 1.9 to 2.2.

In order to address a challenging issue in the recycling of construction debris, the impact of carbonization treatment on the characteristics of recycled aggregates (RCAs) was experimentally examined in this work. Both direct carbonization and carbonization following calcium hydroxide pretreatment were used in the study to assess the impact of carbonization on the physical characteristics of recycled aggregates. According to the findings, carbonization raised the recycled aggregates’ apparent density while drastically lowering their porosity and water absorption (by as much as 20–30%). Although the recycled aggregate’s crushing index marginally increased with age, its overall physical qualities remained excellent. Pretreatment with calcium hydroxide can improve the physical characteristics of recycled aggregates, further optimize their pore structure, and efficiently encourage the carbonation process. Furthermore, recycled aggregate’s crushing index can be considerably decreased and its quality much enhanced by the ultrasonic cavitation treatment. According to the study, the carbonation-treated recycled aggregate’s microstructure was denser in the interfacial transition zone and had a stronger link with the cement paste, improving the recycled aggregate concrete’s overall performance. XRD, infrared spectral analysis, and SEM scanning were used to determine the increased calcium carbonate content in the recycled aggregate following carbonation treatment as well as its microstructure improvement process. The findings offer fresh concepts for achieving resource efficiency and environmental preservation through the use of recycled aggregates in concrete, as well as theoretical backing for their use.

During the loading process of concrete members, the identification of characteristic damage states is not sensitive enough. This paper investigates the damage evolution of four concrete sandwich wallboards subjected to vertical compression by employing the strain energy density increment to enhance identification sensitivity. First, the equivalent elastic modulus model for a wallboard subjected to vertical compression is established based on the material stress–strain relationship. Then, the strain data of concrete, obtained from experiments and numerical simulations, are modeled as the normalized unit approximate strain energy density increments (NUASEDIs), which follow the damage evolution of the wallboard as a more sensitive index. The first cracking formation of wallboard corresponds to the first high NUASEDI. The failure damage state corresponds to the final high NUASEDI, which reflects the process changing from the local to the global failure. Finally, the strain energy density increment theory improves averagely the cracking identification sensitivity of concrete members by 13.32% and the failure identification sensitivity by 3.01%.

A new type of fabricated shotcrete sandwich wall system is proposed. The wall system consisted of steel mesh, foamed concrete blocks, reinforced concrete layers, and core column. The shotcrete has been adopts in structural layer. Steel mesh is placed in the concrete layer. Foam concrete blocks are filled between concrete layers with function of insulation. Core columns are arranged along the cross section of wall with spacing 600mm. Prefabricated rebar cage place in core column. The finite element software ABAQUS is used to calculate its compressive strength, and the calculation results are compared with the theoretical method of related code. The results show that the FE simulation results have a good agreement with the formulation recommended by code.

Concrete sandwich panel is a kind of building element with the characteristics of light weight, high strength, suitability for standardized production, meanwhile it has the multi-function of heat preservation and sound insulation which can be used not only as enclosure components, but also as structural components for multi-story residential buildings. A novel sandwich wall system has been presented in this work with an innovative design concept. Compared with traditional steel wire sandwich panel, this sandwich panel wall system has unique features such as prefabricated steel system, core column with spiral stirrup, foamed concrete as insulation layer. This wall system also meets the national policy requirements in energy-saving and has potential application and development prospects. In this paper, Finite element method is used to simulate and analyze the seismic performance of this new sandwich wall panel. The results show that the panel with 3D steel wire has greater stiffness and better earthquake resistance than panel with planar steel wire mesh.