A combined sound field prediction method in small classrooms. (July 2021)

• Record Type: Journal Article
• Authors: Yang, Da; Mak, Cheuk Ming
• Is Part Of: Building services engineering research & technology. Volume 42:Number 4(2021)
• Page Start: 375
• Page End: 388
• Publication Date: 2021-07
• Subjects: Combined prediction methods -- genetic algorithm -- optimization -- transition frequency; Buildings -- Environmental engineering -- Periodicals; Buildings -- Environmental engineering -- Research -- Periodicals; Sanitary engineering -- Periodicals; 696.05
• DOI: 10.1177/0143624421994229
• Languages: English
• ISSNs: 0143-6244

Abstract

In this paper, a new combination method for sound field prediction is proposed. An optimization approach based on the genetic algorithm is employed for optimizing the transition frequency of the combined sound field prediction method in classrooms. The selected optimization approach can identify the optimal transition frequency so that the combined sound field prediction can obtain more efficient and accurate prediction results. The proposed combined sound field prediction method consists of a wave-based method and geometric acoustic methods that are separated by the transition frequency. In low frequency domain (below the transition frequency), the sound field is calculated by the finite element method (FEM), while a hybrid geometric acoustic method is employed in the high frequency domain (above the transition frequency). The proposed combined prediction models are validated by comparing them with previous results and experimental measurements. The optimization approach is illustrated by several examples and compared with traditional combination results. Compared to existed sound field prediction simulations in classrooms, the proposed combination methods take the sound field in low frequencies into account. The results demonstrate the effectiveness of the proposed model. Practical applications: This study proposes a combined sound field prediction method separated by transition frequency. A genetic algorithm optimization method is employed for searching the optimal transition frequency. The outcomes of this paper are essential for acoustical designs and acoustical environmental assessments.