This study systematically investigated the effects of four supplementary cementitious materials (SCMs), namely ferronickel slag (FNS), lithium slag (LS), steel slag (SS), and ground granulated blast furnace slag (GBFS), on various properties of autoclaved cementitious materials. Cement pastes and mortars with 0% and 30% replacement levels were prepared to examine their impacts on early age hydration products and mechanical properties, with comparisons made to specimens under standard 28-day curing. Key findings reveal that autoclaving promoted the formation of tobermorite, crystalline calcium aluminosilicate hydrate (CASH), gypsum and hydrogarnet, with the latter two phases potentially compromising concrete durability. Autoclave curing significantly enhanced SCM reactivity, as evidenced by thermogravimetric analysis: the mass loss below 200 °C (mainly from C–S–H gels decomposition) in SCM-incorporated pastes ranged from 87.0% (SS) to 104.6% (GBFS) of the control value, while the portlandite (Ca(OH)₂) content decreased to between 47.7% (LS) and 82.4% (GBFS) of the control. Among the SCMs studied, autoclaving exhibited the most pronounced activation effect on LS, which also showed superior potential as a GBFS alternative in autoclaved concrete products. However, the low CaO content and acidic nature of LS limited its use to low replacement levels unless supplementary sources of alkalinity and CaO were provided.

Accurate characterization of underground geological conditions is essential for gas control, geological hazard assessment, and safe coal mining operations. However, conventional geological interpretation methods often suffer from limited spatial accuracy due to borehole deviation, sparse geological control, and insufficient integration of multi-source borehole data. To address these limitations, this study proposes an integrated geological characterization framework combining resistivity-based image logging, borehole trajectory correction, and BIM-based three-dimensional geological modeling using 135 gas extraction boreholes from the Coal Seam 15-21050 working face of Pingdingshan No. 8 Coal Mine, China. Multi-parameter logging data, including natural gamma, apparent resistivity, natural potential, and borehole image observations, were used to identify coal seam lithology, stratigraphic interfaces, and structural characteristics. Borehole trajectory analysis revealed systematic deviation patterns controlled by borehole inclination, lithological heterogeneity, and drilling conditions, highlighting the necessity of trajectory correction for accurate spatial positioning. Trajectory-corrected borehole coordinates were subsequently integrated into a BIM-based three-dimensional geological reconstruction workflow using spatial interpolation methods. The resulting model successfully reproduced coal seam geometry, interburden distribution, and localized concealed structural anomalies. Coal Seam 15 exhibited thicknesses ranging from 2.69 to 3.47 m, while Coal Seam 16–17 ranged from 1.51 to 2.38 m. The proposed workflow improved the reliability of geological interpretation and the accuracy of spatial characterization, providing an effective technical basis for gas drainage optimization, geological hazard assessment, and intelligent underground coal mining.