Deep excavation clearly impacts existing underlying subway tunnels and threatens their operational safety. The prediction of existing tunnel deformation induced by nearby excavation is a major concern for urban construction. This research presents an analytical calculation method for predicting tunnel deformation induced by upside excavation and also discusses the role of dewatering in the deformation mechanism. First, the existing tunnel is assumed to be nonexistent in the soil, and the vertical unloading stress at the location of the existing tunnel caused by the upper excavation and associated dewatering is calculated. Second, the existing underlying tunnel is simplified as an elastic beam on a Pasternak foundation to calculate its vertical deformation. The proposed method was verified by the good agreement found between the predictions and the field measurements of the construction in the Shenzhen Chegongmiao hub project. Such an analytical method can provide fast and accurate evaluation resul...

Soil clogging occurred in the early construction stage of Nanchang Metro Line 1, China, when an earth balance pressure (EPB) shield passed through the argillaceous siltstone with a total content of clay minerals of 40.5%. This paper presents a new scheme for determining soil conditioning parameters to avoid the occurrence of soil clogging, taking both the slump value and the liquidity index of the soil into account. As indicated by the results of slump tests, the optimum slump value for the soil conditioning ranged from 17 to 20 cm, and a fitting function of slump value against foam injection ratio (FIR) and water content (w) was obtained. Considering the requirement for a liquidity index equal to ∼0.4–0.75 to ensure the stability of the excavation face, a chart was proposed for the soil conditioning. Based on the chart, the optimum FIR and w for the soil conditioning for tunneling in argillaceous siltstone were determined to be ∼19.2–23.2% and ∼14.2–36.6%, respectively. Taking shield parameters, ...

Agricultural mechanization is crucial in enhancing production efficiency, alleviating labor demands, reducing costs, improving agricultural product quality, and promoting sustainable development. However, wear and tear are inevitable when using agricultural machinery. The failure of critical wear-resistant parts is responsible for over 50% of rural machinery breakdowns. For instance, a domestic combine harvester typically only operates trouble-free for 20 to 30 h, and the service life of a rotary plow knife is approximately 80 h. Investigating the wear performance of key farm machinery components reinforces machinery design and maintenance strategies, extends machinery lifespans, enhances agricultural production efficiency, and advances agrarian sustainability. This paper provides a comprehensive overview of the latest research on the wear resistance of crucial agricultural machinery components. It delves into the factors influencing the wear resistance of these components and explores current effective measures to address wear-related issues. Additionally, it also summarizes the challenges and opportunities in researching the wear performance of key components in agricultural machinery and future development directions.

The effect and mechanism of grain sizes on the tribological behavior of CoCrFeMnNi high entropy alloy (HEA) were studied by friction experiments and wear morphology analysis. Under normal low load and low sliding speed, the primary wear mechanism of the HEA samples is adhesive wear. With the increase in sliding speed, the wear mechanisms of the samples are adhesive wear and oxidation wear. The oxide layer formed under the action of friction heat of the coarse grain (CG) sample is easy to break due to the softening of the CG. With the increase of normal load and sliding speed, the wear mechanisms of the HEA samples are mainly adhesive wear, oxidation wear, and plastic deformation. The oxide layer of CG sample has many cracks, and the worn surface also has plastic deformation, which leads to the increase of friction coefficient and specific wear rate and the decrease of wear resistance. Therefore, the fine grain size HEA sample has better wear resistance than the CG sample due to its high surface strength.