A method is developed to generate future design reference year (DRY) data from the United Kingdom Climate Impact Programme's 2009 (UKCP09) climate change projections for a variety of future time horizons and carbon emission assumptions. The method selects three near-extreme summer months and three near-extreme winter months and weaves them into an existing test reference year (TRY). Risk levels associated with the 85th percentile (broadly equivalent to existing Chartered Institution of Building Services Engineers [CIBSE] design summer years) of the cumulative distribution function of dry-bulb temperature and, for comparison, the 99th percentile are used. A comparison is made with DRYs generated using alternative methods from other research groups. The data are applied to future airconditioning (cooling) loads analysis for a wide range of non-domestic case study building types. Simulations using a control DRY set applied to these buildings are used to develop a simplified regression-based calculation method for predicting future air-conditioning loads. The simplified model is shown to be applicable to future weather data without loss of accuracy, which makes it possible to carry out large numbers of future cooling loads predictions without the need to perform extensive and complex energy simulations. Practical applications: It is becoming increasingly necessary to design energy and comfort services for buildings with a whole-life perspective. To assist with this, the CIBSE future weather years can be used for building simulations through to the 2080s. In June 2009, the UK's Department of the Environment, Food and Rural Affairs (Defra) with the support of the United Kingdom Climate Impacts Programme (UKCIP) published updated climate change projections using a probabilistic method. In future, the responsibility will rest with designers to select design data from a large number of probabilistic outcomes. This work develops a technique to select design weather data called a DRY at two alternative risk levels for use in building simulations through to the 2080s. A simplified method is also proposed to allow practitioners to generate large numbers of probabilistic design cooling loads without the need to perform extensive simulations.

Non-Newtonian fluid flow in noncircular ducts and microchannels is examined. A simple model is proposed for power law fluids based on the Rabinowitsch–Mooney formulation. By means of a new characteristic length scale, the square root of the cross-sectional area, it is shown that dimensionless wall shear stress can be made a weak function of duct shape. The proposed model is based on the solution for the rectangular duct and has an accuracy of ±10% or better. The current model eliminates the need for tabulated data or equations for several common shapes found in handbooks, namely, circular tube, elliptic tube, parallel channel, rectangular duct, isosceles triangular duct, circular annulus, and polygonal ducts.

In this study, test reference year (TRY) data for three UK cities are generated from the new UKCP09 climate change projections 1 for a variety of future time horizons and carbon emission scenario assumptions. The data are applied to the energy simulation of three commercial buildings and one house for the three city locations (London, Manchester and Edinburgh), three future time horizons in this century and three carbon emission scenarios. Results are compared with those generated using alternative TRYs from two other research groups who used UKCP09 1 as well as with the existing TRY data sets which form the CIBSE Future Weather Years 2 in order to produce robust results. Results of future simulations of peak summer operative temperatures, peak cooling demand, annual cooling energy, peak heating demand and annual heating energy are presented for the four building case studies benchmarked against control weather data for the period 1960–1989. The results show increasing internal operative temperatures (non-air-conditioned) and increasing air-conditioning demands (air-conditioned) throughout this century and though peak heating demands remain similar to control data, annual heating energy consumptions can be expected to fall sharply. Practical applications: Currently, practitioners can use Test Reference Years for use in building energy simulations. In 2009, the CIBSE released Future Weather Years, which go further by allowing practitioners to explore the thermal and comfort behaviour of buildings at future time horizons thus helping to ‘future proof’ a design. In 2009, the United Kingdom Climate Impacts Programme released a new generation of climate change scenario data (the UKCP09 climate change projections) using probabilistic methods. These are the most comprehensive data yet and provides a greater degree of detail than was available to generate the CIBSE Future Weather Years. It is therefore likely that the new data will gradually become the normal basis for investigating future building thermal and comfort response. In this study, a sample of TRY is generated from the UKCP09 data and applied to the simulation of a sample of ‘real’ buildings. The results are compared with both the existing CIBSE Future Weather Years as well as with Test Reference Years generated using UKCP09 by two other research groups. The results provide a robust way forward for simulating building thermal and comfort response using future weather data.

No abstract

This research investigates the overall heating energy consumptions using various control strategies, secondary heat emitters, and primary plant for a building. Previous research has successfully demonstrated that a dynamic distributed heat emitter model embedded within a simplified third-order lumped parameter building model is capable of achieving improved results when compared to other commercially available modelling tools. With the enhanced ability to capture transient effects of emitter thermal capacity, this research studies the influence of control strategies and primary plant configurations on the rate of energy consumption of a heating system. Four alternative control strategies are investigated: zone feedback; weather-compensated; a combination of both of these methods; and thermostatic control. The plant alternative configurations consist of conventional boilers, biomass boilers, and heat pumps supporting radiator heating and underfloor heating. The performance of the model is tested on a primary school building and can be applied to any residential or commercial building with a heating system. Results show that the new methods reported offer greater detail and rigor in the conduct of building energy modelling.