Influence of a building's integrated-photovoltaics on heating and cooling loads

Building integrated photovoltaics (BIPV) has the potential to become a major source of renewable energy in the urban environment. BIPV has significant influence on the heat transfer through the building envelope because of the change of the thermal resistance by adding or replacing the building elements. Four different roofs are used to assess the impacts of BIPV on the building's heating-and-cooling loads; namely ventilated air-gap BIPV, non-ventilated (closed) air-gap BIPV, closeroof mounted BIPV, and the conventional roof with no PV and no air gap. One-dimensional transient models of four cases are derived to evaluate the PV performances and building cooling-and-heating loads across the different roofs in order to select the appropriate PV building integration method in Tianjin, China. The simulation results show that the PV roof with ventilated air-gap is suitable for the application in summer because this integration leads to the low cooling load and high PV conversion efficiency. The PV roof with ventilation air-gap has a high time lag and small decrement factor in comparison with other three roofs and has the same heat gain as the cool roof of absorptance 0.4. In winter, BIPV of non-ventilated air gap is more appropriate due to the combination of the low heating-load through the PV roof and high PV electrical output. © 2005 Elsevier Ltd. All rights reserved.

Recovering 3D Structure of Poorly Textured Infrastructure Scenes Using Point and Line Features

Most of the existing automated machine vision-based techniques for as-built documentation of civil infrastructure utilize only point features to recover the 3D structure of a scene. However it is often the case in man-made structures that not enough point features can be reliably detected (e.g. buildings and roofs); this can potentially lead to the failure of these techniques. To address the problem, this paper utilizes the prominence of straight lines in infrastructure scenes. It presents a hybrid approach that benefits from both point and line features. A calibrated stereo set of video cameras is used to collect data. Point and line features are then detected and matched across video frames. Finally, the 3D structure of the scene is recovered by finding 3D coordinates of the matched features. The proposed approach has been tested on realistic outdoor environments and preliminary results indicate its capability to deal with a variety of scenes.