Noise simulation model

Noise pollution is the most overlooked environmental pollution despite its adverse effects in humans and other living organisms [1]. It’s a global concern especially in modern cities like Singapore. Increasing populations and urbanisation contributes to raise in traffic demands which leads traffic n...

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Main Author: Lee, Cassidy Zi Hui
Other Authors: Lee Bu Sung, Francis
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/157173
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1571732022-05-11T06:23:39Z Noise simulation model Lee, Cassidy Zi Hui Lee Bu Sung, Francis School of Computer Science and Engineering EBSLEE@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Noise pollution is the most overlooked environmental pollution despite its adverse effects in humans and other living organisms [1]. It’s a global concern especially in modern cities like Singapore. Increasing populations and urbanisation contributes to raise in traffic demands which leads traffic noise in the environment. This project aims to find a way to model traffic noise against the traffic demands on roads in Singapore. A background study on noise and it’s modelling tools will be done to explore the noise modelling tools available for public use. In particular, the noise modelling tools studied in this project are OpeNoise and NoiseModelling. OpeNoise is an open source QGIS plugin for road traffic noise assessment [2]. NoiseModelling is an open source GIS tool that is able to produce environmental noise maps for assessment [3]. The chosen area of study is Clementi. The traffic noise within the roads in the area will be computed using both modelling tools. Separate computation would be done in accordance with two noise computation method, NMPB-96, and CNOSSOS-EU. The noise data computed was successfully visualised on QGIS, an open-source geographic information system application [4]. The computed noise data will be used to perform a comparison analysis on both noise modelling tools and the noise computation method to compare the difference in noise levels computed by each. The results of the comparison showed that the noise levels computed by the different tools and methods had only a small difference. This result was verified against another chosen area of study, Pasir Ris. Similarly, the results of the noise levels computed had only a small difference. Further validation of results was done, and the noise levels computed was compared against actual noise data captured in Clementi. The results showed an average difference of 8.77 dB when comparing the actual noise data with the computed noise data by the noise calculation tools. The final study explored the possibilities to compute traffic noise levels against simulated agent-based traffic based on traffic demands on roads. A study on MATSim will be done. MATSim is a Multi-Agent Transport Simulation software [5] that implements agent-based transport planning simulations. A smaller region within the focus area in Clementi was chosen for the simulation. To obtain a simulation using MATSim, a network of Clementi was generated using the MATSim plugin available on the JOSM (Java OpenStreetMap Editor), an open-source application for editing OpenStreetMap [6]. A facilities file was created to define the agent’s activity location. The traffic demand was manually created based on link from the generated network and the location of the agent’s activity from the created facilities file. These files will be defined as inputs in the MATSim configuration for the simulation. The output of the MATSim simulation was imported into Noisemodelling to get the noise propagation from the traffic data obtain from the simulation. A noise map was created to visualise the noise propagation and spectrum for each receiver points. Using these methods, modelling of computed traffic noise against the traffic demands on roads in Singapore can be used as a more cost-effective method to assist with future development planning. Bachelor of Engineering (Computer Science) 2022-05-11T06:23:39Z 2022-05-11T06:23:39Z 2022 Final Year Project (FYP) Lee, C. Z. H. (2022). Noise simulation model. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157173 https://hdl.handle.net/10356/157173 en SCSE21-0069 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
Lee, Cassidy Zi Hui
Noise simulation model
description Noise pollution is the most overlooked environmental pollution despite its adverse effects in humans and other living organisms [1]. It’s a global concern especially in modern cities like Singapore. Increasing populations and urbanisation contributes to raise in traffic demands which leads traffic noise in the environment. This project aims to find a way to model traffic noise against the traffic demands on roads in Singapore. A background study on noise and it’s modelling tools will be done to explore the noise modelling tools available for public use. In particular, the noise modelling tools studied in this project are OpeNoise and NoiseModelling. OpeNoise is an open source QGIS plugin for road traffic noise assessment [2]. NoiseModelling is an open source GIS tool that is able to produce environmental noise maps for assessment [3]. The chosen area of study is Clementi. The traffic noise within the roads in the area will be computed using both modelling tools. Separate computation would be done in accordance with two noise computation method, NMPB-96, and CNOSSOS-EU. The noise data computed was successfully visualised on QGIS, an open-source geographic information system application [4]. The computed noise data will be used to perform a comparison analysis on both noise modelling tools and the noise computation method to compare the difference in noise levels computed by each. The results of the comparison showed that the noise levels computed by the different tools and methods had only a small difference. This result was verified against another chosen area of study, Pasir Ris. Similarly, the results of the noise levels computed had only a small difference. Further validation of results was done, and the noise levels computed was compared against actual noise data captured in Clementi. The results showed an average difference of 8.77 dB when comparing the actual noise data with the computed noise data by the noise calculation tools. The final study explored the possibilities to compute traffic noise levels against simulated agent-based traffic based on traffic demands on roads. A study on MATSim will be done. MATSim is a Multi-Agent Transport Simulation software [5] that implements agent-based transport planning simulations. A smaller region within the focus area in Clementi was chosen for the simulation. To obtain a simulation using MATSim, a network of Clementi was generated using the MATSim plugin available on the JOSM (Java OpenStreetMap Editor), an open-source application for editing OpenStreetMap [6]. A facilities file was created to define the agent’s activity location. The traffic demand was manually created based on link from the generated network and the location of the agent’s activity from the created facilities file. These files will be defined as inputs in the MATSim configuration for the simulation. The output of the MATSim simulation was imported into Noisemodelling to get the noise propagation from the traffic data obtain from the simulation. A noise map was created to visualise the noise propagation and spectrum for each receiver points. Using these methods, modelling of computed traffic noise against the traffic demands on roads in Singapore can be used as a more cost-effective method to assist with future development planning.
author2 Lee Bu Sung, Francis
author_facet Lee Bu Sung, Francis
Lee, Cassidy Zi Hui
format Final Year Project
author Lee, Cassidy Zi Hui
author_sort Lee, Cassidy Zi Hui
title Noise simulation model
title_short Noise simulation model
title_full Noise simulation model
title_fullStr Noise simulation model
title_full_unstemmed Noise simulation model
title_sort noise simulation model
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157173
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