The high-temperature performance of well cement is critical for the construction of deep geothermal wells and high-temperature energy storage wells, where mechanical integrity and pore structure stability govern wellbore reliability. To address the strength degradation and structural deterioration of conventional cements under high temperature, the G-class cement was modified by ethylene-vinyl acetate (EVA) polymer and polypropylene fibers (PF), and their impact under various temperatures was explored. Results show that at 600 °C, the compressive strength of modified cement remains above 30 MPa. While the cumulative pore area decreases at 500 °C, a significant increase in larger pores and a major restructuring of the pore network occurs at 600 °C, reflecting the dual effects of high temperature on the pore structure. The modified cement retains structural integrity and excellent mechanical performance up to 400 °C with minimal strength loss, uniform strain distribution, and stable pore structure. At 500 °C and above, it still maintains load-bearing capacity and deformation adaptability, meeting the service requirements for geothermal wells and high-temperature energy storage wells. Even at 600 °C, the reinforcing effect of EVA and PF degradation products slow down crack propagation, ensuring durability in extreme conditions. The research findings lay the foundation for the development of well cement for high-temperature service environments.

It is imperative to conduct experimental studies on the seepage behavior of gas-bearing coal under cyclic dynamic loading conditions. This paper focuses on the evolution of coal permeability under the combined effects of dynamic loading, static loading, and gas adsorption. The principal conclusions are as follows: (1) As the frequency and amplitude of dynamic loading increase, the development of pore and fissure structures within the coal body becomes increasingly pronounced during dynamic loading cycles, resulting in a gradual rise in permeability. Notably, as the coal approaches its yielding stage, the permeability can increase by up to 47%. (2) The permeability curve is divided into four regions: the compaction reduction zone, the oscillation zone, the gradual recovery zone, and the abrupt failure increase zone. Ultimately, in the failure phase, the permeability surges dramatically, potentially reaching four to five times the initial permeability. (3) When the static loading stage and dynamic load are constant, the rate of change in coal permeability decreases with increasing adsorption amounts. When the adsorption amount is constant, the rate of change in permeability of the coal under dynamic loading increases with the increase in the static loading stress stage, with the maximum increase reaching 75.2%. It can be concluded from the rate of change in permeability and the dynamic loading sensitivity coefficient that the permeability of coal is highly sensitive to cyclic dynamic loading, with increased sensitivity associated with larger static loading stages and decreased sensitivity with greater adsorption amounts.

To address insufficient carbon integration, weakly verifiable quality constraints, and unstable Pareto-set generation in construction-stage green decision-making, this study develops a multi-objective optimization model for construction mode configuration and an engineering-oriented genetic algorithm (GA) framework for Pareto solution generation under hard feasibility constraints. In a construction organization scenario, duration, cost, and carbon emissions are formulated as parallel objectives, while a quality threshold, explicit process logic, and basic resource and workface-feasibility conditions are incorporated to ensure engineering implementability. Construction-stage carbon emissions are quantified using the emission factor method under an auditable activity-level accounting framework. The configured GA framework is compared with the conventional GA, the Non-dominated Sorting Genetic Algorithm II, and the Non-dominated Sorting Genetic Algorithm III through repeated-run statistics and multi-metric evaluation. On the main case, it achieves the highest mean hypervolume (0.723 ± 0.074, mean ± standard deviation), the lowest mean spacing (0.076 ± 0.207), and the smallest average convergence generation (18.49 ± 2.57). The Pareto results reveal a clear trade-off among duration, cost, and carbon emissions, in which high-load beam-and-slab formwork and concrete-related activities dominate cost and carbon variation, whereas schedule advantage mainly depends on stronger compression of critical-chain activities and inter-floor handover.