Improving Insertion Loss of Sonic Crystal Active Noise Barrier by Reinforcement Learning and Finite Difference Time Domain Simulations
David Ramírez-Solana,
Jaime Galiana-Nieves,
Javier Redondo
et al.
Abstract:Sonic crystal noise barriers (SCNB) have emerged as a promising solution for mitigating traffic noise pollution. These barriers utilize periodic structures to selectively reflect acoustic waves at specific target frequencies, offering the advantage of being permeable to light and wind. However, their installation and maintenance costs have hindered widespread adoption. In contrast, active noise control (ANC) systems leverage speakers and microphones to generate opposing sound waves that cancel out incoming noi… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.