No abstract

The importance of multi-sensory perception in constructing human landscape experiences has been increasingly emphasized in contemporary urban life. The aim of this study is to explore aural-visual interaction attributes that may influence people’s perceived overall soundscape comfort in urban green spaces (UGSs). To achieve this, a total of 12 perceptive indicators were identified from the existing literature to evaluate people’s perceived visual and acoustic attributes and types of sound sources, and their relations to the perceived soundscape comfort. 268 responses were obtained in a questionnaire-based survey conducted in five UGSs in Chengdu Outer Ring Ecological Zone. This was done whilst a typical objective acoustic indicator, sound level, was used as a mediator for potential changes on these relations within different sound level ranges. Results suggested that a low level of environmental sound does not correspond to higher ratings on the overall soundscape comfort. It was also found that the environmental sound level of 77 dBA was a turning point in the relation between people’s soundscape comfort and its influential indicators in UGSs. A set of six models was then provided to describe the overall soundscape comfort and its contributing indicators in aural-visual interactions, respectively, in sound level ranges below and above 77dBA.

The unique construction of the dividing-wall column (DWC) has the potential for both energy and capital cost conservation. A sufficiently robust control strategy is needed to handle the DWC because it is a complex multivariable system with high process nonlinearity and time lag. In this paper, the single-factor, response surface methodology (RSM), and particle swarm optimization (PSO) optimizations are applied to the DWC, and the optimal operating parameters are obtained. Then, a sliding mode control (SMC) method is proposed for DWC. Specifically, the DWC is estimated by a first-order pure lag transfer function, and the SMC controller is developed with the aid of the Interpreted MATLAB Fcn of MATLAB/Simulink. Finally, the dynamic responses of both SMC controller and proportional-integral-derivative (PID) controller are analyzed using the disturbance in the feed flow rate (F). The results show that the settling time, oscillation, and steady-state deviation of the SMC controller are less than those of the PID controller. In this way, the SMC could present a better option for control of a complex distillation process, such as the DWC.

The inductive detection of wear debris in lubrication oil is an effective method to monitor the machine status. As the wear debris is usually micro scale, a micro inductive sensor is always used to detect them in research papers or high-tech products. However, the improvement of detection sensitivity for micro inductive sensors is still a great challenge, especially for early wear debris of 20 μm or smaller diameter. This paper proposes a novel method to improve the detection sensitivity of a micro inductive sensor. Regarding the magnetic powder surrounding the sensor, the magnetic field in the core of the sensor where the wear debris pass through would be enhanced due to the increased relative permeability. Thus, the inductive signal would be improved and the detection sensitivity would be increased. It is found that the inductive signal would linearly increase with increasing the concentration of the magnetic powder and this enhancement would also be effective for wear debris of different sizes. In addition, the detection limit of the micro inductive sensor used in our experiment could be extended to 11 μm wear debris by the proposed method.