In rockfall hazard management, the investigation and detection of potential rockfall source areas on rock cliffs by remote-sensing-based susceptibility analysis are of primary importance. However, when the rockfall analysis results are used as feedback to the fieldwork, the irregular slope surface morphology makes it difficult to objectively locate the risk zones of hazard maps on the real slopes, and the problem of straightforward on-site visualization of rockfall susceptibility remains a research gap. This paper presents some of the pioneering studies on the augmented reality (AR) mapping of geospatial information from cyberspace within 2D screens to the physical world for on-site visualization, which directly recognizes the rock mass and superimposes corresponding rock discontinuities and rockfall susceptibility onto the real slopes. A novel method of edge-based tracking of the rock mass target for mobile AR is proposed, where the model edges extracted from unmanned aerial vehicle (UAV) structure-from-motion (SfM) 3D reconstructions are aligned with the corresponding actual rock mass to estimate the camera pose accurately. Specifically, the visually prominent edges of dominant structural planes were first explored and discovered to be a robust visual feature of rock mass for AR tracking. The novel approaches of visual-geometric synthetic image (VGSI) and prominent structural plane (Pro-SP) were developed to extract structural planes with identified prominent edges as 3D template models which could provide a pose estimation reference. An experiment verified that the proposed Pro-SP template model could effectively improve the edge tracking performance and quality, and this approach was relatively robust to the changes of sunlight conditions. A case study was carried out on a typical roadcut cliff in the Mentougou District of Beijing, China. The results validate the scalability of the proposed mobile AR strategy, which is applicable and suitable for cliff-scale fieldwork. The results also demonstrate the feasibility, efficiency, and significance of the geoinformation AR mapping methodology for on-site zoning and locating of potential rockfalls, and providing relevant guidance for subsequent detailed site investigation.

Thermal conductivity is an important thermal parameter in engineering design in cold regions. By measuring the thermal conductivity of clay using a transient hot‐wire method in the laboratory, the influential factors of the thermal conductivity of soils during the freezing process were analyzed, and a predictive model of thermal conductivity was developed with an artificial neural network (ANN) technology. The results show that the variation of thermal conductivity can be divided into three stages with decreasing temperature, positive temperature stage, transition stage, and negative temperature stage. The thermal conductivity increases sharply in the transition stage. The difference between the thermal conductivity at positive and negative temperature is small when the dry density of the soil specimens is larger than the critical dry density, while the difference is large if the dry density is less than the critical dry density. As the negative temperature decreases, the larger the moisture content of the soil specimens, the larger the increase of thermal conductivity. The effect of initial moisture content on thermal conductivity is more significant than that of dry density and temperature. The change tendency of the thermal conductivity calculated by the established ANN model is basically consistent with that of the laboratory‐measured values, indicating that this model can be able to accurately predict the thermal conductivity of the soil specimens in the freezing process.

Winter construction in seasonally frozen soil areas is inevitable. The variation of ambient temperature causes the freeze‐thaw of the filling soils and its impact is significant, and whether the countermeasures can be effectively established and adopted is particularly important for the management and control of the construction quality of the project. This paper conducts systematic research based on the winter construction process of the dam core wall of the Lianghekou Hydropower Station, which is the third highest earth‐core rockfill dam in the world under construction. The results show that for the construction site in the seasonally frozen soil area, there is a development process of the short‐term frozen soils for the filling soils under the environment with low temperature in winter. The soil underwent a high‐frequency freeze‐thaw process wherein it was frozen at night and completely thawed during the day. During the freezing process, a large number of thin‐layered segregated ice developed inside the soil to form a thin‐layered or integral cryostructure, which will have an adverse effect on the engineering properties and the quality of the filling soils. And, the field tests demonstrate that the filling compaction degree of the frozen soils is difficult to meet the designed requirements. In order to effectively cope with the adverse effect of the freeze‐thaw on the construction quality during the construction process, based on the analysis of the freeze‐thaw characteristics of soils and its influence, and the energy exchange process of soils on‐site, the principles and methods for establishing the freeze prevention system during the winter construction process are established, and a comprehensive monitoring system suitable for on‐site is established in this paper. This research will provide an important reference for the scientific management and efficiency improvement of the winter construction process of the dams in cold regions.