Proactive Safety Risk Control System for Deep Foundation Pit Construction: Situational Tailoring of Integrated Cybernetics and Dual-System Theory

Abstract

The frequent recurrence of falls, deflections, collapses, etc., emphasizes the urgent necessity for effective safety risk management in deep foundation pit construction (DFPC) projects. Innovative solutions to identify and control safety risks in DFPC projects before potential accidents occur are imperatively needed. This paper proposes a novel safety risk control system integrating cybernetics and dual-system theory, i.e., the PSRC-DFPC system, enhancing the proactive risk management cycle from risk identification to risk evaluation and rating, as well as the execution of preemptive control strategies and countermeasures. The proposed system provides a complete workflow designed to shift managerial focus from existing deviations to proactive risk anticipation and adopts evolutionary risk warning standards and risk precontrol decisions based on continuously monitored data for risk points. The practical applicability of this system is validated through its implementation in DFPC of the tunnel construction project, which significantly declined the managing project costs and mitigated potential risks, demonstrating enhancements in management effectiveness. Deep foundation pit construction (DFPC) involves complex and hazardous operations that frequently lead to accidents, highlighting a critical need for enhanced risk management. However, the current passive and reactive risk management methods are insufficient for effectively managing the risks associated with DFPC. This study develops a proactive safety risk control system to improve risk management efficiency and construction safety in DFPC. The system provides timely risk alerts and data-driven decision support, reducing potential accidents and better managing project costs. The implementation of the proposed system in a real-world project has proven its capability in high-risk construction contexts, providing implications for future practice regarding data-driven deviation checking, risk interval update iteration, and precise accident prediction. The proactive risk management mindset based on the application of this system and workflows can also contribute to project stakeholders’ and site participants’ safety awareness and efficiency in cooperation.