Hui Yu

Large-scale hydroelectric projects play an essential role in sustainable energy infrastructure, yet their construction schedules are frequently disrupted by complex risk correlations and propagation effects. Traditional critical chain buffer management methods often rely on static presets, impeding dynamic allocation. This paper proposes a dynamic monitoring framework for critical chain buffers that enhances schedule resilience by accounting for risk interdependencies. The method employs a fuzzy DEMATEL-ISM-BN algorithm to identify risk propagation paths and quantify their impact on buffers; combines a WBS-RBS mapping matrix with fuzzy expert scoring to determine activity risk weights; uses a PSO-RF model to predict the actual activity completion times; and defines three buffer consumption scenarios based on the predictions to trigger dynamic reallocation. The approach is demonstrated through a case study of a pumped-storage power station in East China. The calculated project buffer was increased from 19.51 days under the root variance approach to 30.56 days after incorporating risk compensation, representing an increase of 56.6% and demonstrating the additional protection required when risk interdependencies are considered in buffer sizing. When critical activities encounter unexpected risks, the dynamic reallocation mechanism promptly redistributes buffers to compensate, preventing delays from propagating downstream along the critical chain. Under the case-study scenario, the total remaining buffer at project completion was 101.09 days. After accounting for the risk-induced extension of activity M, the resulting critical chain duration was 1940.05 days, which was 97.50 days (approximately 4.79%) shorter than the planned critical chain schedule of 2037.55 days. The proposed mechanism enables unused buffer from completed activities to be transferred to subsequent activities, thereby improving buffer utilization efficiency during project execution. Through a closed-loop mechanism of “risk quantification → buffer calculation → schedule forecasting → dynamic allocation,” the proposed framework transforms schedule management from static presetting to adaptive control, improves project resilience and resource utilization efficiency, and supports sustainable project delivery by improving schedule reliability and reducing unnecessary buffer allocation.

The composition elements of the earthwork allocation system (excavation project, filling project, transfer yard, waste disposal yard, and material yard) and the relationship between material flow were analyzed. Based on the construction of calculation models for soil and water conservation fees, landscape restoration fees, and road transportation intensity, a joint optimization model was constructed with the objectives of minimizing the total allocation cost and minimizing the peak transportation intensity of the road. By dynamically adjusting the volatility, setting penalty factors, and vectorizing NumPy arrays, the ant colony algorithm is improved and the optimization model is solved. Case analysis shows that considering the intensity of road transportation, the peak transportation intensity significantly decreases, and the proportion of directly filled earthwork increases to over 88% without exceeding the capacity of the intermediate transfer site. The total cost only increases by 0.91%, and the allocation plan is more in line with actual construction needs.

This research was based on the loss relationship diagrams of the linear term, quadratic term, and the cubic term losses in the quality gain–loss function (QGLF) for the larger-the-better characteristic (LBC) and the smaller-the-better characteristic (SBC). Limitations of ignoring the cubic term loss in the QGLF for the LBC and the SBC were analyzed. A QGLF model for LBC and SBC was proposed when considering the cubic term loss, using the threshold set at the ratio of the quadratic term loss to the cubic term loss. The calculation formulas for the coefficients of the linear term loss and the quadratic and cubic term losses in the QGLF for LBC and SBC when considering the cubic term were analyzed. By calculating and comparing the QGLF and the percentage discrepancy value of the continuous curing time of the concrete construction of dams and the temperature of the concrete pouring outlet, it was proved that directly ignoring the cubic term loss led to a discrepancy between the estimated quality loss value and the actual loss.