Life cycle dynamic sustainability maintenance strategy optimization of fly ash RC beam based on Monte Carlo simulation. (1st June 2022)

• Record Type: Journal Article
• Authors: Wang, Jingjing; Wang, Yuanfeng; Zhang, Yurong; Liu, Yinshan; Shi, Chengcheng
• Is Part Of: Journal of cleaner production. Volume 351(2022)
• Publication Date: 2022-06-01
• Subjects: Small and medium span bridges -- Maintenance -- Reliability -- Carbon dioxide -- Cost -- Time effect; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.131337
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Small and medium span bridges account for 86% of the bridges in China, and maintenance is necessary to ensure their safety and serviceability. The infrastructure sector causes substantial CO2 emissions, and it is one of the most polluting sectors. Fly ash (FA) is often used in bridges to reduce CO2 emissions. Moreover, the lack of temporal information is an important limitation of the life cycle CO2 assessment of bridges. Taking the upper structure of small and medium span bridges as the research object, this paper proposes a Monte Carlo simulation-based life cycle multi-objective dynamic maintenance strategy optimization model to analyze the life-cycle carbon emissions, costs, and life cycle reliability of different preventive maintenance (PM) and essential maintenance (EM) methods of FA reinforced concrete (RC) beams. Considering the continuous effect of carbon emissions and the net present value of the cost, the time effect of carbon emissions and costs of maintenance and reinforcement at different times is analyzed. Through 50, 000 simulations of the case beam, the parameter characteristics of different optimal reinforcement schemes and the relationship between the reliability, life cycle CO2 emissions, and costs are studied. When introducing the discount rate, the essential maintenance with higher carbon emissions and costs has a marginal effect, i.e., the longer that future carbon emissions and costs occur, the smaller the net present value. The proposed method is demonstrated to be effective at supporting decision making for bridge managers. It would be helpful for identifying the effectiveness of PM and EM, selecting optimal maintenance time interval, and providing a rational estimate of the CO2 emissions and costs of bridges. Highlights: A Multi-objective dynamic maintenance strategy optimization model is proposed. The time effects of carbon emissions and costs are analyzed. The parameter characteristics of the optimal maintenance of a T-beam are found.