关键词: 固废材料, 声屏障, 机器学习, 配比优化, 结构设计, 声学性能

Abstract: The use of solid waste materials to manufacture noise barriers contribute to the two environmental protection fields of noise prevention and solid waste treatment, so has received increasing attention. This study proposed a solid waste traffic noise barrier unit panel made from waste soil generated during highway construction, and carried out related material research and development, structural design, and performance testing, including: based on machine learning technology, the mix proportion of frame material and sound absorption screen material was optimized respectively; the finite element software was used to analyze the stress of different structural schemes of the noise barrier unit panel; the acoustic performance of the trial-produced sound barrier unit panel sample was tested. The results show that through mix proportion optimization, the 28 d compressive strength of frame work material reaches 57.40 MPa, the 28 d flexural strength reaches 8.71 MPa, and the waste soil content reaches 18.00% (mass fraction). The sound absorption coefficient of the sound absorption screen material reaches 0.70, the weighted sound insulation index reaches 37.56 dB, and the waste soil content reaches 31.40% (mass fraction). Both materials achieve a high level of in performance and waste soil utilization at the same time. The grid-patterned structure exhibits optimal mechanical properties in both vertical and horizontal compressive strength. The noise barrier unit panel meets or exceeds the relevant national standards in both acoustic performance and durability.

Key words: solid waste material, noise barrier, machine learning, mix proportion optimization, structure design, acoustic performance