The international roughness index (IRI) for roads is a crucial pavement design criterion in the Mechanistic-Empirical Pavement Design Guide (MEPDG). However, studies have shown that the IRI transfer function in the MEPDG is simply a linear combination of road parameters, so it cannot provide accurate predictions. To solve this issue, this research developed an AdaBoost regression (ABR) model to improve the prediction ability of IRI and compared it with the linear regression (LR) in MEPDG. The development of the ABR model is based on the Python programming language, using the 4265 records from the Long-Term Pavement Performance (LTPP) that include the pavement thickness, service age, average annual daily truck traffic (AADTT), gator cracks, etc., which are reliable data that are preserved after years of monitoring. The results reveal that the ABR model is significantly better than the LR because the correlation coefficient (R2) between the measured and predicted values in the testing set increased from 0.5118 to 0.9751, and the mean square error (MSE) decreased from 0.0245 to 0.0088. By analyzing the importance of variables, there are many additional crucial factors, such as raveling and bleeding, that affect IRI, which leads to the weak performance of the LR model.

The vertical stability analysis of the drilling shaft lining has long been a technical problem in the construction of underground space development projects. And the critical depth of vertical stability was a key parameter to judge its stability. To determine this parameter, a simple and practical computational method would be helpful. In this paper, a new vertical stability analysis model of shaft lining structure based on catastrophe theory was proposed. In accordance with the mechanical analysis, the catastrophic instability mechanics was analyzed and a new critical depth of drilling shaft lining was deduced. Further, the rationality and feasibility of the catastrophic calculation model was proved by the numerical simulation results in a case. And the sensitivity of the influencing parameters was also analyzed, which provided theoretic reference for optimization design and guiding security construction. The results implied that catastrophic calculation model, as an alternative method for shaft stability analysis, could be applied to theoretical analysis and guiding engineering practice in the study of drilling shaft lining’s vertical stability.

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To accelerate the resource utilization of coal gangue and meet the strategic requirements of carbon neutralization, alkali-activated, slag-cemented coal gangue is applied in the preparation of solid waste-based road stabilization materials. Here, the cementation characteristics and microstructure characteristics of alkali-activated, slag-cemented coal gangue road stabilization materials are studied using the alkali equivalent and coal gangue aggregate ratio as experimental variables. The results show that with the increase in alkali equivalent from 1% to 7%, the unconfined compressive strength of the alkali-activated coal gangue road stabilization material initially increases and then decreases, with 3% being the optimal group in terms of stabilization, the aggregate ratio of coal gangue increases from 70% to 85%, and the 7-day unconfined compressive strength of the stabilized material decreases approximately linearly from 8.16 to 1.68 MPa. At the same time, the porosity gradually increases but still meets the requirements of the specification. With the increase in hydration time, a large number of hydration products are formed in the alkali slag cementation system, and they are closely attached to the surface of and interweave with the coal gangue to fill the pores, resulting in the alkali slag slurry and coal gangue being brought closer together.

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