Application of transparent microperforated panels to acrylic partitions for desktop use: A case study by prototyping.

There are various measures currently in place to prevent the spread of coronavirus (COVID-19); however, in some cases, these can have an adverse effect on the acoustic environment in buildings. For example, transparent acrylic partitions are often used in eating establishments, meeting rooms, offices, etc., to prevent droplet infection. However, acrylic partitions are acoustically reflective; therefore, reflected sounds may cause acoustic problems such as difficulties in conversation or the leakage of conversation. In this study, we performed a prototyping of transparent acrylic partitions to which a microperforated panel (MPP) was applied for sound absorption while maintaining transparency. The proposed partition is a triple-leaf acrylic partition with a single acrylic sheet without holes between two MPP sheets, as including a hole-free panel is important to prevent possible droplet penetration. The sound absorption characteristics were investigated by measuring the sound absorption in a reverberation room. As the original prototype showed sound absorption characteristics with a gentle peak and low values due to the openings on the periphery, it was modified by closing the openings on the top and sides. The sound absorption performance was improved to some extent when the top and sides were closed, although there remains the possibility of further improvement. For this study, only the sound absorption characteristics were examined in the prototype experiments. The effects during actual use will be the subject of future study.

Modeling of driver's collision avoidance maneuver based on controller switching model.

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.