Due to sensor failure, noise interference and other factors, the data collected in the structural health monitoring (SHM) system will show a variety of abnormal patterns, which will bring great uncertainty to the structural safety assessment. This paper proposes an automatic data anomaly diagnosis method for SHM based on a multimodal deep neural network. In order to improve the detection accuracy, both two-dimensional and one-dimensional features of the sensor data are fused in the multimodal deep neural network. The network consists of two convolutional neural network (CNN) channels, one a 2D-CNN channel for extracting time–frequency features of sensor data and the other a 1D-CNN channel for extracting raw one-dimensional features of sensor data. After convolution and pooling operations for the sensor data by the 2D channel and 1D channel separately, the two types of extracted features are flattened into one-dimensional vectors and concatenated at the concatenation layer. The concatenated vector is then fed into fully connected layers for final SHM data anomaly classification. In order to evaluate the reliability of the proposed method, the monitored data lasting for one month of a long-span cable-stayed bridge were used for training, validation, and testing. Six types of training conditions (missing, minor, outlier, over-range oscillation, trend, and drift) are studied and analyzed to address the issue of imbalanced training data. With an accuracy rate of 95.10%, the optimal model demonstrates the effectiveness and capability of the proposed method. The proposed method shows a promising future as a reliable AI-assisted digital tool for safety assessment in structural health monitoring systems.

Research on the multi-field coupling effects in rocks has been ongoing for several decades, encompassing studies on single physical fields as well as two-field (TH, TM, HM) and three-field (THM) couplings. However, the environmental conditions of rock masses in deep resource extraction and underground space development are highly complex. In such settings, rocks are put through thermal-hydrological-mechanical-chemical (THMC) coupling effects under peak temperatures, strong osmotic pressures, extreme stress, and chemically reactive environments. The interaction between these fields is not a simple additive process but rather a dynamic interplay where each field influences the others. This paper provides a comprehensive analysis of fragmentation evolution, deformation mechanics, mechanical constitutive models, and the construction of coupling models under multi-field interactions. Based on rock strength theory, the constitutive models for both multi-field coupling and creep behavior in rocks are developed. The research focus on multi-field coupling varies across industries, reflecting the diverse needs of sectors such as mineral resource extraction, oil and gas production, geothermal energy, water conservancy, hydropower engineering, permafrost engineering, subsurface construction, nuclear waste disposal, and deep energy storage. The coupling of intense stress, fluid flow, temperature, and chemical factors not only triggers interactions between these fields but also alters the physical and mechanical properties of the rocks themselves. Investigating the mechanical behavior of rocks under these conditions is essential for averting accidents and assuring the soundness of engineering projects. Eventually, we discuss vital challenges and future directions in multi-field coupling research, providing valuable insights for engineering applications and addressing allied issues.

Engineering residue soil, a prominent type of construction solid waste, can offer considerable environmental and socioeconomic benefits if efficiently utilized. Unburned brick represents an environmentally friendly and high-value approach to reusing this residue soil. Mud, a primary constituent of residue soil, typically hinders the performance of unburned brick using cement-based materials. This study investigates the effects of mud on the performance of unburned brick made from engineering residue soil based on experimental tests and mechanism analysis. The residue soil is silty clay sourced from the alluvial soil layer in South China. A comprehensive analysis of the physical and chemical properties of the residue soil and mud is conducted to assess the feasibility of using them in unburned brick production. Using ordinary Portland cement as the cementitious material, the unburned residue soil bricks are produced via semi-dry static-press forming and natural curing. The influence of mud type and content on the compressive strength of the unburned brick made with engineering residue soil is investigated and discussed. This experimental study reveals that the influence of mud on unburned brick’s compressive strength is negligible. However, excessively low mud content reduces brick compactness, impairs brick formation, and leads to lower compressive strength. Within the range of solidification, unburned brick’s compressive strength initially increases and then decreases with increasing mud content, with an optimal mud content of approximately 25%. As engineering residue soil often contains a high mud content, reducing it effectively enhances the compressive strength of unburned bricks. Through experiments and mechanism analysis, this research clarifies the impact of mud on the strength and performance of unburned residue soil bricks, providing important theoretical insights and practical guidance for the production of unburned products and promoting the efficient and environmentally friendly resource utilization of engineering residue soil.

This study evaluates the vertical stress transmission through a sand–tire mixture layer under impact, focusing on this innovative blended material that can impact underground structures such as tunnels or pipelines. By conducting consolidated undrained triaxial tests, the friction angle (φ) of the sand–tire mixture was determined, ranging from 29° for pure tire to 41° for pure sand. The vertical stress factor (α), representing the ratio of response load to applied load, was found to decrease significantly with increased tire content, with a reduction of up to 50% for mixtures containing 20% tire. Additionally, the vertical stress response decreased from 35 kPa for pure sand to as low as 15 kPa for mixtures with a high tire content under a consistent applied load of 65 kPa. This study not only presents a methodological advancement in analyzing sand–tire mixtures under dynamic loads but also suggests a sustainable approach to utilizing waste tire material in civil engineering projects, thereby contributing to environmental conservation and improved material performance in geotechnical applications.

The high permeability of gravel sand increases the risk of water spewing from the screw conveyor during earth pressure balance (EPB) shield tunnelling. The effectiveness of soil conditioning is a key factor affecting EPB shield tunnelling and construction safety. In this paper, using polymer, a foaming agent, and bentonite slurry as conditioning additives, the permeability coefficient tests of conditioned gravel sand are carried out under different injection conditions based on the factorial experiment design. The interactions between different concentrations of conditioning additives are analyzed. A prediction model for soil conditioning during shield tunneling based on particle swarm optimization (PSO) and relevance vector machine (RVM) algorithms is proposed to accurately and efficiently obtain the soil conditioning parameters in the water-rich gravel sand layer. The experimental results indicate that the improvement effect of the foaming agent on the permeability of the conditioned gravel sand gradually diminishes with the growing concentration of bentonite slurry. Under conditions of high polymer concentration, further increasing the concentration of bentonite slurry and foaming agent has a weak impact on the permeability coefficient when the concentration of bentonite slurry exceeds 10%. The significance of main effects, first-order interactions, and second-order interaction on the permeability of conditioned gravel sand are as follows: polymer concentration (A) > foaming agent concentration (B) > bentonite slurry concentration (C) > first-order interactions (A × B, A × C, B × C) > second-order interaction (A × B × C). The first-order interaction mainly manifests as a synergistic effect, while the second-order interaction primarily exhibits an antagonistic effect. Case studies show that the maximum relative error between predicted and experimental values is less than 3%. A field application of shield tunneling demonstrates the good performance of real-time optimization of soil conditioning parameters based on the PSO–RVM algorithm. This research provides a new method for evaluating the effectiveness of soil conditioning in the water-rich gravel sand layer.

The aim of this study is to introduce a protective layer to safeguard tunnel structures. In practice, one viable approach to create this protective layer between the tunnel structure and surrounding rocks is to pump the material during tunnel construction. The primary components of the proposed material are porous sand, rubber, and cement. Static and dynamic experiments were conducted to assess the unconfined compressive strength (UCS), flexural stiffness, and compaction resistance at various mixing ratios. The results indicate that the addition of porous sand decreases the UCS compared to the solid sand under similar mixing conditions. The addition of rubber offers the elasticity, thereby enhancing the compaction resistance. However, increasing the rubber content compromises UCS. Furthermore, this study presents a linear equation to predict the 7-day UCS, which can be used as a rapid estimation for UCS, flexural stiffness, and compaction resistance of the proposed material. It is important to note that this study only investigates the fundamental mechanical properties of the proposed material, and further comprehensive research is necessary to fully understand its workability, durability, and other behaviour before practical application.