In industrial and architectural applications, noise can be controlled using sound-absorbing materials. Natural materials are now gaining importance in the noise control engineering as they have advantages like low cost, eco-friendly, easy to produce, etc. Jute is one of such natural materials, which can be used as a sound-absorbing material. Micro-perforated panels along with three different types of jute felts are used in a multilayer sound absorber configuration to improve its sound absorption. The sound absorption performance of these multilayer sound absorbers is evaluated by using the transfer matrix method and experimental method. Dependence of sound absorption performance on the placement of micro-perforated panels in a multilayer sound absorber is also studied. It is observed that the sound absorption performance depends on the position of micro-perforated panels in a multilayer sound absorber.
Today many different natural materials are being effectively used in the acoustics and noise control domain. In this study, the acoustical characterization of three different types of natural jute felt material is performed by an experimental method and by using the Dunn and Davern model, along with an inverse characterization method. There are many empirical models available in the literature which describes the acoustical behavior of specific material accurately, as they are specially developed for that material. In this study, the possibility of using only the air flow resistivity based Delany–Bazley model and the Dunn–Davern model for acoustical performance prediction of jute material is tested. However, these two models do not show good matching with the experimental data throughout the frequency range of interest. Particularly in the low frequency region, the level of mismatch between experimental and model data is high. Therefore the inverse prediction of the coefficients [Formula: see text] in Dunn–Davern model using the particle swarm optimization (PSO) method is conducted, and new coefficients for jute material are found. These new coefficients better predict the acoustical performance of jute felts and reduce the mismatch level in the low-frequency region.
The objective of the present study is to investigate the electromechanical response of a piezoelectric boron nitride nanosheet reinforced nanobeam accounting for the surface and the flexoelectric effects using finite element analysis. The finite element model was developed by using the size-based Euler–Bernoulli beam model, modified piezoelectricity theory, and Galerkin's weighted residual method. The boron nitride nanosheet-reinforced nanobeam was loaded with uniformly distributed load and point-loading conditions. Three common boundary conditions for beams such as clamped-free, simply supported, and clamped-clamped have been considered here. The electromechanical behavior of the boron nitride nanosheet reinforced nanobeam has been studied under the pure surface, pure flexoelectric, as well as combined surface and flexoelectric effects. It is observed that the integrated surface and flexoelectric effects are mainly responsible for enhancing the electromechanical performance of the nanobeam. For the thickness H = 20 nm, the maximum deflection of the nanobeam was reduced by ∼50% when both the flexoelectricity and surface effects are combined together for all the support conditions. Moreover, the circular cross-section beam becomes ∼30% stiffer than the rectangular cross-section beam under the integrated effect of surface and flexoelectricity under all loading conditions. Hence, the highly size-dependent surface and flexoelectricity must be explored in the accurate electromechanical behavior of the nanostructure. Furthermore, beam stiffness is highly influenced by the flexoelectric effect irrespective of the beam boundary conditions whereas the surface effect is largely reliant on the beam boundary conditions. This research work provides a methodology to design efficient boron nitride nanosheet reinforced nanostructures that may potentially be applied in the design and development of several nanoelectromechanical systems such as force and pressure-based nanosensors and actuators.
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.