21 resultados para Automobile driving at night.
Resumo:
We examine the fluid mechanics of night purging in a two-storey naturally ventilated atrium building. We develop a mathematical model of a simplified atrium building and focus on the rate at which warm air purges from each storey and the atrium by displacement ventilation into a still cool night environment of a constant temperature. To develop a first insight into how the geometry of the building influences the rate at which warm air purges from each storey via the atrium we neglect heat exchange with the fabric (so there is no thermal buffering) and furthermore assume that the warm air layers in each storey and the atrium are of uniform temperature. The plumes of warm air that rise from the storeys into the atrium, causing the atrium to fill with warm air, have a very strong influence on the night purge. Modelling these as axisymmetric turbulent plumes, we identify three forms of purging behaviour. Each purge is characterised by five key times identified in the progression of the night purge and physical rationale for these differing behaviours is given. An interface velocity deficit and volumetric purge deficit are introduced as measures of the efficiency of a night purge. © 2010 Elsevier Ltd.
Resumo:
The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.