Study on the Influence of High Speed Bridge-Borne Noise on Indoor Noise of Buildings Along the Line
To investigate the influence of the bridge-borne noise on indoor noise of buildings when high-speed trains pass through the railway line,a model for predicting bridge and building noise is established based on the vehicle-track-bridge coupled dynamics theory,the finite element and acoustics boundary element methods.The characteristic of building's indoor noise under the conditions with or without consideration of ground reflection were compared when the train passes over the bridge at the speed of 350 km/h.Moreover,the effect of the distance between the bridge and building on the indoor noise is studied.The results indicate that the dominant frequency of indoor noise was around 63～88 Hz,which was consistent with the main frequency of bridge sound power.The reflection and su-perposition of sound waves in the chamber form standing waves,which results in the accumulation of sound pressure around the back wall and central areas at dominant frequencies.The radiated noise between the bridge and the build-ing forms standing waves bythe reflection of walls,and the sound pressure was accumulated significantly outside the front wall.The distribution locations of sound pressure accumulation zone at indoor sound fields were less affected by the ground reflection and the lateral distance between bridges and buildings,but the sound pressure near the outside wall increases significantly by multiple reflections of sound waves from the ground and building,which resulting in an overall increase in the sound pressure level,with a maximum increase of 13.5 dB,considering the ground reflec-tion.The maximum SPL decreased with the increase of distance between bridges and buildings,and the decrement of SPLs was about 1～2 dB with every 5 m increase of distance in the frequency ranges below 16 Hz and between the 31.5 Hz and 80 Hz.
high-speed railwaystructure-borne noisebuildings along the railway lineacoustic radiation noiseboundary element method
万方数据
维普
