Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Prediction of drained weight in canned prawn under commercial conditions

A general formula for the prediction of drained weight of canned prawn processed under laboratory condition has been worked out earlier (Chaudhuri et al., 1978). Attempts were made in this communication to modify the general formula to predict the drained weight under commercial conditions of processing particularly blanching, as the moisture content of meat depends on the quantum of heat received during blanching (Govindan, 1975).

Longitudinal prediction of the operational energy use of buildings

Thus far most studies of operational energy use of buildings fail to take a longitudinal view, or in other words, do not take into account how operational energy use changes during the lifetime of a building. However, such a view is important when predicting the impact of climate change, or for long term energy accounting purposes. This article presents an approach to deliver a longitudinal prediction of operational energy use. The work is based on the review of deterioration in thermal performance, building maintenance effects, and future climate change. The key issues are to estimate the service life expectancy and thermal performance degradation of building components while building maintenance and changing weather conditions are considered at the same time. Two examples are presented to demonstrate the application of the deterministic and stochastic approaches, respectively. The work concludes that longitudinal prediction of operational energy use is feasible, but the prediction will depend largely on the availability of extensive and reliable monitoring data. This premise is not met in most current buildings. © 2011 Elsevier Ltd.

The role of adaptive thermal comfort in the prediction of the thermal performance of a modern mixed-mode office building in the UK under climate change

Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixedmode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change. © 2010 International Building Performance Simulation Association (IBPSA).

Trophic State Index, morphoedaphic index and fish yield prediction in a sub-tropical lake, Manchar (Sindh), Pakistan

Limnological factors of a sub-tropical lake Manchar were studied on seasonal basis. The mean values of various parameters were: transparency, (secchi disc reading): 90.5 cm, Orthophosphate: 0.257 mg/l, TDS: 3310,5 mg/l, Conductivity: 5232 µs/l, Total Chlorophyll (Planktonic): 31.3 µg/l Planktonic biomass: 5466 µg/l. Trophic state index (TSI) was calculated by using Carlson's (1977) equations. Mean TSI for transparency was 61, while for orthophosphate and chlorophyll, it was 82 and 64 respectively. TSI values indicate advanced eutrophic state of Manchar Lake. Morphoedaphic index (MEI) was also calculated on seasonal basis. The mean values were, TDS: 1103, conductivity: 1744, alkalinity: 60, transparency: 29 and biomass (plankton dry weight): 1746. Fish yield prediction for Manchar Lake (Z =3m, mean area=100 km²) was calculated by using MEI values. The results were quite different among various parameters. Conductivity (89.1mt/y), biomass (67.6 mt/y) and TDS (44.6 mt/y) were found to be good predictors of fish yield. Chlorophyll, transparency and alkalinity values gave very low estimate.