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Open AccessArticle

Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes

Institute of Construction Management, Zhejiang University, Zhejiang 310058, China
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Author to whom correspondence should be addressed.
Academic Editors: Albert P. C. Chan and Wen Yi
Int. J. Environ. Res. Public Health 2016, 13(8), 818; https://doi.org/10.3390/ijerph13080818
Received: 6 July 2016 / Revised: 7 August 2016 / Accepted: 8 August 2016 / Published: 12 August 2016
(This article belongs to the Special Issue Effecting a Safe and Healthy Environment in Construction)
Quantitative prediction of construction noise is crucial to evaluate construction plans to help make decisions to address noise levels. Considering limitations of existing methods for measuring or predicting the construction noise and particularly the equivalent continuous noise level over a period of time, this paper presents a discrete-event simulation method for predicting the construction noise in terms of equivalent continuous level. The noise-calculating models regarding synchronization, propagation and equivalent continuous level are presented. The simulation framework for modeling the noise-affected factors and calculating the equivalent continuous noise by incorporating the noise-calculating models into simulation strategy is proposed. An application study is presented to demonstrate and justify the proposed simulation method in predicting the equivalent continuous noise during construction. The study contributes to provision of a simulation methodology to quantitatively predict the equivalent continuous noise of construction by considering the relevant uncertainties, dynamics and interactions. View Full-Text
Keywords: equivalent continuous noise; construction processes; prediction; discrete-event simulation; simulation framework equivalent continuous noise; construction processes; prediction; discrete-event simulation; simulation framework
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Zhang, H.; Pei, Y. Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes. Int. J. Environ. Res. Public Health 2016, 13, 818.

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