Comparative life cycle assessment of composite structures incorporating uncertainty and global sensitivity analysis

Zhao, Menghan; Dong, You; Guo, Huizhen

doi:10.1016/j.engstruct.2021.112394

Cited by 27 publications

(10 citation statements)

References 98 publications

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“…Concrete production is susceptible to numerous uncertainties that can pose challenges to conducting a robust LCA, as highlighted by Zhao et al (2021). To address these uncertainties, a sensitivity analysis was conducted in this study to evaluate the impacts of some key factors such as high-temperature curing, emissions allocation scheme and PRAC formulation methods on the LCA outcomes.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Cleaner production of the precast concrete industry: comparative life cycle analysis of concrete using recycled aggregates from crushed precast rejects

Yong

Pacheco-Torgal

Zhao

et al. 2023

European Journal of Environmental and Civil Engineering

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The in-plant use of recycled aggregate concrete derived from precast rejects (termed PRAC herein) can promote a circular economy in the precast industry. However, the environmental implications associated with this practice remain poorly understood. A refined life cycle assessment (LCA) model was therefore developed to highlight the environmental benefits of using PRAC compared to natural aggregate concrete and conventional recycled aggregate concrete. Some key factors influencing PRAC's environmental performance were also examined. The results indicate that PRAC exhibits around 15% lower energy consumption and carbon dioxide emissions compared to other recycled materials. This reduction is attributed to the favourable quality of PRAC and the elimination of long-distance transport. However, emissions allocation and raw material prices play significant roles in determining the overall environmental impact of PRAC. The equivalent mortar volume mixing method is best suited for PRAC production, as it saves energy, reduces emissions, and maintains similar mechanical properties. Nevertheless, the high-temperature curing, which is often necessary in a precast factory setting, can be energy-intensive and thus diminishes the eco-friendliness of PRAC. Overall, the findings support the use of precast rework as recycled aggregate for cleaner production in the precast industry.

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Section: Sensitivity Analysismentioning

confidence: 99%

Cleaner production of the precast concrete industry: comparative life cycle analysis of concrete using recycled aggregates from crushed precast rejects

Yong

Pacheco-Torgal

Zhao

et al. 2023

European Journal of Environmental and Civil Engineering

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“…In the field of bridge engineering, there is a need to further specify and present the cost estimation process for maintenance work, which is achieved by considering specific defect types, measures, and the material volumes used. Zhao et al [11] defined it such that each maintenance operation involves replacing 10% of the original materials, and the maintenance cost is calculated based on the volume of material replacement. However, the cost of maintenance measures not only includes material costs, but also encompasses expenses related to labor, machinery, and other factors such as regional rates.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It does not follow the Weibull distribution. By substituting the Weibull parameters into Equation (11), the durations of the elements in each state can be obtained, as shown in the table. The durations in Table 8 represent the total time that bridge elements stay in multiple states without maintenance.…”

Section: Duration Of Each Statementioning

confidence: 99%

Modeling the Optimal Maintenance Strategy for Bridge Elements Based on Agent Sequential Decision Making

Xin,

Liang,

et al. 2023

Applied Sciences

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In addressing the issues of low efficiency in bridge maintenance decision making, the inaccurate estimation of maintenance costs, and the lack of specificity in decision making regarding maintenance measures for specific defects, this study utilizes data from regular bridge inspections. It employs a two-parameter Weibull distribution to model the duration variables of the states of bridge elements, thereby enabling the prediction of the duration time of bridge elements in various states. Referring to existing bridge maintenance and repair regulations, the estimation process of maintenance costs is streamlined. Taking into account the specific types and development state of bridge defects, as well as considering the adequacy of maintenance and the restorative effects of maintenance measures, an intelligent agent sequential decision-making model for bridge maintenance decisions is established. The model utilizes dynamic programming algorithms to determine the optimal maintenance and repair measures for elements in various states. The decision results are precise, all the way down to the specific bridge elements and maintenance measures for individual defects. In using the case of the regular inspection data of 222 bridges along a highway loop, this study further validates the effectiveness of the proposed research methods. By constructing an intelligent agent sequential decision-making model for bridge element maintenance, the optimal maintenance measures for 21 bridge elements in different states are obtained, thereby significantly enhancing the efficiency of actual bridge maintenance and the practicality of decision results.

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“…The most significant sources of uncertainties reported in the studies were uncertainty in model and process parameters, data variability, and uncertainty due to using different methodologies and databases. Uniform [34,41,57,65,70,95,110,113] Beta [57,96,116] Gamma [41,67] BETA-PERT […”

Section: Sources Of Uncertainty and Pdfsmentioning

confidence: 99%

Life Cycle Assessment under Uncertainty: A Scoping Review

Barahmand

Eikeland

2022

World

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Today, life cycle assessment (LCA) is the most widely used approach to model and calculate the environmental impacts of products and processes. The results of LCAs are often said to be deterministic, even though the real-life applications are uncertain and vague. The uncertainty, which may be simply ignored, is one of the key factors influencing the reliability of LCA outcomes. Numerous sources of uncertainty in LCA are classified in various ways, such as parameter and model uncertainty, choices, spatial variability, temporal variability, variability between sources and objects, etc. Through a scoping review, the present study aims to identify and assess the frequency with which LCA studies reflect the uncertainty and what are the tools to cope with the uncertainty to map the knowledge gaps in the field to reveal the challenges and opportunities to have a robust LCA model. It is also investigated which database, methodology, software, etc., have been used in the life cycle assessment process. The results indicate that the most significant sources of uncertainty were in the model and process parameters, data variability, and the use of different methodologies and databases. The probabilistic approach or stochastic modeling, using numerical methods such as Monte Carlo simulation, was the dominating tool to cope with the uncertainty. There were four dominant LCA methodologies: CML, ReCiPe, IMPACT 2002+, and TRACI. The most commonly used LCA software and databases were SimaPro® and Ecoinvent®, respectively.

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Comparative life cycle assessment of composite structures incorporating uncertainty and global sensitivity analysis

Cited by 27 publications

References 98 publications

Cleaner production of the precast concrete industry: comparative life cycle analysis of concrete using recycled aggregates from crushed precast rejects

Cleaner production of the precast concrete industry: comparative life cycle analysis of concrete using recycled aggregates from crushed precast rejects

Modeling the Optimal Maintenance Strategy for Bridge Elements Based on Agent Sequential Decision Making

Life Cycle Assessment under Uncertainty: A Scoping Review

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