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Noise Propagation in Urban Area from Chimneys of Thermal Power Plants

EasyChair Preprint no. 3276

8 pagesDate: April 28, 2020


Large energy facilities are noise sources of the adjacent to them urban buildings. In case of noise propagation from pipes, the assessment of the noise mode of the urban building area is a complex scientific-practical problem of building physics. The solution of the problem is carried out consistently in two stages. At first, the noise distribution in channels from ventilator to the mouth of the pipe is determined. Proposed calculation model takes into account sizes and shape of channel and pipe, noise insulation properties of the walls and the mirrored-diffuse nature of the sound reflection from the fences. For metal ducts, 95% of reflected sound energy is mirrored, and other 5% of it is diffusely. The distribution of emitted by pipe sound energy within urban building is found at the next stage. A new method is suggested for solution of this problem. It is based on received analytical dependence of the sound energy directivity factor from the mouth of pipe and integration of its diffraction. To implement the method a computer program is developed. The program makes it possible to assess the propagation of noise inside ducts and in an open space from the mouth of the pipe to various sites of buildings. To realize the method, an example of calculation of noise emitted by the chimney of a steam boiler of a thermal power plant in Moscow is given. The example shows the potential of suggested calculation model and its computer realization for the noise mode assessment of the adjacent to energy facilities urban buildings.

Keyphrases: calculation of noise in urban areas, chimney noise, noise

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Vladimir Gusev and Vladimir Ledenev and Aleksandr Antonov and Irina Matveeva},
  title = {Noise Propagation in Urban Area from Chimneys of Thermal Power Plants},
  howpublished = {EasyChair Preprint no. 3276},

  year = {EasyChair, 2020}}
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