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Deflection of resilient materials for reduction of floor impact sound.

ABSTRACT: Recently, many residents living in apartment buildings in Korea have been bothered by noise coming from the houses above. In order to reduce noise pollution, communities are increasingly imposing bylaws, including the limitation of floor impact sound, minimum thickness of floors, and floor soundproofing solutions. This research effort focused specifically on the deflection of resilient materials in the floor sound insulation systems of apartment houses. The experimental program involved conducting twenty-seven material tests and ten sound insulation floating concrete floor specimens. Two main parameters were considered in the experimental investigation: the seven types of resilient materials and the location of the loading point. The structural behavior of sound insulation floor floating was predicted using the Winkler method. The experimental and analytical results indicated that the cracking strength of the floating concrete floor significantly increased with increasing the tangent modulus of resilient material. The deflection of the floating concrete floor loaded at the side of the specimen was much greater than that of the floating concrete floor loaded at the center of the specimen. The Winkler model considering the effect of modulus of resilient materials was able to accurately predict the cracking strength of the floating concrete floor.

SUBMITTER: Lee JY

PROVIDER: S-EPMC4276361 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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Project description:Cross-modal interactions between auditory and haptic perception manifest themselves in language, such as sound symbolic words: crunch, splash, and creak. Several studies have shown strong associations between sound symbolic words, shapes (e.g., Bouba/Kiki effect), and materials. Here, we identified these material associations in Turkish sound symbolic words and then tested for their effect on softness perception. First, we used a rating task in a semantic differentiation method to extract the perceived softness dimensions from words and materials. We then tested whether Turkish onomatopoeic words can be used to manipulate the perceived softness of everyday materials such as honey, silk, or sand across different dimensions of softness. In the first preliminary study, we used 40 material videos and 29 adjectives in a rating task with a semantic differentiation method to extract the main softness dimensions. A principal component analysis revealed seven softness components, including Deformability, Viscosity, Surface Softness, and Granularity, in line with the literature. The second preliminary study used 27 onomatopoeic words and 21 adjectives in the same rating task. Again, the findings aligned with the literature, revealing dimensions such as Viscosity, Granularity, and Surface Softness. However, no factors related to Deformability were found due to the absence of sound symbolic words in this category. Next, we paired the onomatopoeic words and material videos based on their associations with each softness dimension. We conducted a new rating task, synchronously presenting material videos and spoken onomatopoeic words. We hypothesized that congruent word-video pairs would produce significantly higher ratings for dimension-related adjectives, while incongruent word-video pairs would decrease these ratings, and the ratings of unrelated adjectives would remain the same. Our results revealed that onomatopoeic words selectively alter the perceived material qualities, providing evidence and insight into the cross-modality of perceived softness.

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Deflection of resilient materials for reduction of floor impact sound.

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