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.

Statistical gear health analysis which is robust to fluctuating loads and operating speeds

Condition-based maintenance is concerned with the collection and interpretation of data to support maintenance decisions. The non-intrusive nature of vibration data enables the monitoring of enclosed systems such as gearboxes. It remains a significant challenge to analyze vibration data that are generated under fluctuating operating conditions. This is especially true for situations where relatively little prior knowledge regarding the specific gearbox is available. It is therefore investigated how an adaptive time series model, which is based on Bayesian model selection, may be used to remove the non-fault related components in the structural response of a gear assembly to obtain a residual signal which is robust to fluctuating operating conditions. A statistical framework is subsequently proposed which may be used to interpret the structure of the residual signal in order to facilitate an intuitive understanding of the condition of the gear system. The proposed methodology is investigated on both simulated and experimental data from a single stage gearbox. © 2011 Elsevier Ltd. All rights reserved.

Study of spike and modal stall phenomena in a low-speed axial compressor

This paper presents a study of stall inception mechanisms a in low-speed axial compressor. Previous work has identified two common flow breakdown sequences, the first associated with a short lengthscale disturbance known as a `spike', and the second with a longer lengthscale disturbance known as a `modal oscillation'. In this paper the physical differences between these two mechanisms are illustrated with detailed measurements. Experimental results are also presented which relate the occurrence of the two stalling mechanisms to the operating conditions of the compressor. It is shown that the stability criteria for the two disturbances are different: long lengthscale disturbances are related to a two-dimensional instability of the whole compression system, while short lengthscale disturbances indicate a three-dimensional breakdown of the flow-field associated with high rotor incidence angles. Based on the experimental measurements, a simple model is proposed which explains the type of stall inception pattern observed in a particular compressor. Measurements from a single stage low-speed compressor and from a multistage high-speed compressor are presented in support of the model.