To establish the hysteresis model of EPS particles amended light weight soil under multi-step cyclic loading, the dynamic deformation characteristics of light weight soil were studied by consolidated undrained dynamic triaxial tests. The results showed that the backbone curve of light weight soil is hyperbolic and has strain hardening characteristics. With the increase of dynamic stress, the hysteresis curve shape of light weight soil gradually transforms from spindle-shaped to crescent-shaped, showing nonlinearity, hysteresis and strain accumulation. Based on the Hardin-Drnevich model and Masing rules, a modified unloading and reloading rule for the hysteresis model of light weight soil is proposed. The maximum dynamic shear modulus correction coefficient k1 and dynamic shear modulus attenuation coefficient k2 are introduced to establish the modified hysteresis model of light weight soil. Based on the modified hysteresis model, the physical meanings of k1 and k2 are defined. The influence of k1 and k2 values on the shape of hysteresis curve is discussed, and the empirical formulas of k1 and k2 about the dynamic shear strain are obtained. Through the verified dynamic triaxial tests of light weight soil by changing stress state, it is found that the relative error between the predicted values of modified hysteresis model and measured values is between 3.19% and 19.41%, which indicates that the model can describe closely the mechanical response process of light weight soil under complex dynamic conditions. The modified hysteresis model can predict the complex mechanical response mechanism in the progressive evolution of structural soil from convex to concave-convex hysteresis loop.

With global climate change and the deterioration of the ecological environment, the safety of hydraulic engineering faces severe challenges, among which soil-dwelling termite damage has become an issue that cannot be ignored. Reservoirs and embankments in China, primarily composed of earth and rocks, are often affected by soil-dwelling termites, such as Odontotermes formosanus and Macrotermes barneyi. Identifying soil-dwelling termite damage is crucial for implementing monitoring, early warning, and control strategies. This study developed an improved YOLOv8 model, named MCD-YOLOv8, for identifying traces of soil-dwelling termite activity, based on the Monte Carlo random sampling algorithm and a lightweight module. The Monte Carlo attention (MCA) module was introduced in the backbone part to generate attention maps through random sampling pooling operations, addressing cross-scale issues and improving the recognition accuracy of small targets. A lightweight module, known as dimension-aware selective integration (DASI), was added in the neck part to reduce computation time and memory consumption, enhancing detection accuracy and speed. The model was verified using a dataset of 2096 images from the termite damage survey in hydraulic engineering within Hubei Province in 2024, along with images captured by drone. The results showed that the improved YOLOv8 model outperformed four traditional or enhanced models in terms of precision and mean average precision for detecting soil-dwelling termite damage, while also exhibiting fewer parameters, reduced redundancy in detection boxes, and improved accuracy in detecting small targets. Specifically, the MCD-YOLOv8 model achieved increases in precision and mean average precision of 6.4% and 2.4%, respectively, compared to the YOLOv8 model, while simultaneously reducing the number of parameters by 105,320. The developed model is suitable for the intelligent identification of termite damage in complex environments, thereby enhancing the intelligent monitoring of termite activity and providing strong technical support for the development of termite control technologies.

Modern structures incorporating lightweight, low-stiffness floors face challenges for lowfrequency impact noise transmission. Using spring isolators or resilient layers (e.g., floating floors) to improve isolation in light weight floor can introduce variability over time and increase structural complexity, making the system more sensitive to construction errors. An alternative approach is reviewed in this work, using internal floor cavities that contain Granular Materials (GM). Previous studies describe GM particle dampers in different applications where large movements between particles result in significant energy losses. However, a review of the experimental methods used in those studies is needed to be able to quantify the energy losses in relation to the type and degree of impact excitation. Modelling approaches are reviewed comparing their computational demand and which properties of GM are included, motion regimes and container properties. These studies span both destructive and non-destructive testing methods and give some pointers to both the geometrical and mechanical properties of granules which influence dissipation. This review goes beyond structural damping to include airborne sound absorption provided by a granular bed. This additional attenuation can be significant over a wide frequency range. A small number of practical studies of GM integrated with light weight floors show improvement in impact sound insulation. However, the lack of more detailed knowledge of GM damping mechanisms and a better understanding of GM bed interactions with containers prevents optimization of their use for insulating floors against sound transmission. This review proposes a general framework for future GM research to guide the selection of appropriate GM and addresses what is needed for optimizing lightweight floor impact sound insulation.