Predictive simulation of construction site noise emissions from heavy equipment
Abstract
Purpose
Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as long-term auditory impairments for construction workers. The limited effectiveness of passive noise control measures due to the close proximity of the construction site to surrounding neighborhoods often results in complaints and eventually lawsuits. These can then lead to delays and cost overruns for the construction projects.
Design/methodology/approach
The paper proposes a novel approach to integrating construction noise as an additional dimension into scheduling construction works. To achieve this, a building information model, including the three-dimensional construction site layout object geometry, resource allocation and schedule information, is utilized. The developed method explores further project data that are typically available, such as the assigned equipment to a task, its precise location, and the estimated duration of noisy tasks. This results in a noise prediction model by using noise mapping techniques and suggesting less noisy alternative ways of construction. Finally, noise data obtained from sensors in a case study contribute real values for validating the proposed approach, which can be used later to suggest solutions for noise mitigation.
Findings
The results of this study indicate that the proposed approach can accurately predict construction noise given a few available parameters from digital project planning and sensors installed on a construction site. Proactively integrating construction noise control measures into the planning process has benefits for both residents and construction managers, as it reduces construction noise-related disturbances, prevents unexpected legal issues and ensures the health and well-being of the workforce.
Originality/value
While previous research has concentrated on real-time data collection using sensors, a more effective solution would also involve addressing and mitigating construction noise during the pre-construction work planning phase.
Keywords
Acknowledgements
The Bauhaus-Universität Weimar granted the first author a scholarship within the framework of the “Thüringer Graduiertenförderung.” The Danish Environmental Protection Agency (MUDP) sponsored the data collection as part of the efforts of the Technical University of Denmark (DTU) in the project “MUDP: Future Green Construction Site.” The authors would also like to express their gratitude to the Chair of Building Physics at Bauhaus-Universität Weimar for providing the license for the CadnaA software.
Citation
Babazadeh, N., Teizer, J., Bargstädt, H.-J. and Melzner, J. (2024), "Predictive simulation of construction site noise emissions from heavy equipment", Smart and Sustainable Built Environment, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/SASBE-08-2023-0226
Publisher
:Emerald Publishing Limited
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