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      • SCOPUSKCI등재

        Urban road traffic noise on human exposure assessment using geospatial technology

        Pachaivannan Partheeban,Krishnamurthy Karthik,Partheeban Navin Elamparithi,Krishnan Somasundaram,Baskaran Anuradha 대한환경공학회 2022 Environmental Engineering Research Vol.27 No.5

        The sounds produced by humans, industries, transport and animals in the atmosphere that pose a threat to the health of humans or animals can be characterized as noise pollution. Adverse effects due to noise exposure can involve speech communication interference and declining learning skills of children. Highway traffic noise contributes to 80% of all noise. It has grown to a massive scale because of growth in population along the roads leading to a rapid change in land use and has evolved into a common reality in various Indian cities. The main objective of this work is to develop a road traffic noise prediction model using ArcGIS 10.3 for the busy corridors of Chennai. The collected data includes traffic volume, speed, and noise level in lateral and vertical directions. Noise levels were measured in 9 locations using a noise level meter. It is observed that the noise levels vary from 50 dB to 96 dB. It is found that the noise problem is severe in 18% of the area, and 6.3% of people are exposed to the traffic noise problem. The results obtained in this study show that the city is affected by severe noise pollution due to road traffic.

      • Study on self-compacting polyester fiber reinforced concrete and strength prediction using ANN

        Chella Gifta Christopher,Partheeban Pachaivannan,P. Navin Elamparithi Techno-Press 2023 Advances in concrete construction Vol.15 No.2

        The characteristics of self-compacting concrete (SCC) made with fly ash and reinforced with polyester fibers were investigated in this research. Polyester fibers of 12 mm long and 15 micrometer diameters were utilized in M40 grade SCC mixtures at five different volume fractions 0.025%, 0.05%, 0.075%, 0.1%, 0.3% as a fiber reinforcement. To understand the influence of polyester fibers on passing ability, flowability, segregate resistance the J ring, L box, V funnel, slump flow and U box tests were performed. Polyester fibers have a direct influence, with a maximum of 0.075% polyester fibers producing excellent characteristics. ANN models were constructed using the testing data as inputs to anticipate the fresh and hardened characteristics as targeted outputs. The research revealed that R<sup>2</sup> values ranging from 0.900 to 0.997 appears to be a good correlation. The performance of ANN models and regression models for predicting the new characteristics of SCC is also evaluated.

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