John Mardaljevic

Useful daylight illuminance: a new paradigm for assessing daylight in buildings

This paper introduces a new paradigm to assess daylight in buildings called ‘useful daylight illuminance’, or UDI. The UDI paradigm preserves much of the interpretive simplicity of the conventional daylight factor approach. In contrast to daylight factors however, UDI is founded on an annual time-series of absolute values for illuminance predicted under realistic skies generated from standard meteorological datasets. Achieved UDI is defined as the annual occurrence of illuminances across the work plane where all the illuminances are within the range 100-2000 lux. These limits are based on reports of occupant preferences and behaviour in daylit offices with user-operated shading devices. The degree to which UDI is not achieved because illuminances exceed the upper limit is indicative of the potential for occupant discomfort. The relation between achieved UDI and annual energy consumption for lighting is examined.

Validation of a lighting simulation program under real sky conditions

The illuminance predictions from the lighting simulation program RADIANCE are compared with measurements taken in full-scale experimental rooms under real sky conditions for both overcast and clear skies. Results are presented for clear glazing and two types of light shelf. The model sky description is based on the real sky luminance distribution measured by a sky luminance mapping instrument. The sky luminance and room illuminance measurements are simultaneous allowing an extremely accurate representation of the real conditions in the model. Model representation of the measured sky brightness distribution is described.

Simulation of annual daylighting profiles for internal illuminance

A true measure of the long-term daylighting performance of a building must account for the illumination that results from a wide range of sky and sun conditions. This paper describes how to predict hourly internal daylight illuminances for a period of a full year using sky and sun conditions derived from meteorological time-series data. The technique is based on a refined implementation of the daylight coefficient approach. The analysis and the reduction of the large datasets that result from a daylight coefficient based evaluation are described. The new approach was validated under real sky condition using the BRE-IDMP dataset and shown to be highly accurate.

The BRE-IDMP dataset: a new benchmark for the validation of illuminance prediction techniques

Scale models are generally believed to be a reliable tool for illumination modelling and are often used to predict daylight factors. Recent work however has revealed that scale models generally over-predict illuminance by a significant margin for overcast skies. For nonovercast skies the divergence between model and real building performance is greater still. Advances in lighting simulation and physical modelling allow for the possibility of a daylighting evaluation that is based on a range of nonovercast sky luminance patterns including sun. Using either technique it is now a practical possibility to predict hourly internal illuminance levels for a full year under realistic sky and sun conditions. Illuminance predictions for these conditions need to be validated using the best possible data. The uncertainties associated with scale modelling suggest that the technique is insufficiently reliable for validation of predictions under non-overcast skies, and that a new benchmark is needed. The BRE-IDMP validation dataset contains simultaneous measurements of sky luminance patterns, solar illuminance and internal illuminance in two full-size mock offices. With this dataset it is possible to specify to an unprecedented degree of precision the conditions at the time of measurement. The dataset, believed to be the only one of its type in existence, is complex and does contain occurrences of potentially unreliable entries. These had to be identified so that a true assessment of the accuracy of the illuminance predictions can be made. This paper describes how this was achieved. Predictions from lighting simulation are validated using the dataset but the findings are also applicable to the validation of physical modelling approaches using the new generation of sky simulators.

A framework for predicting the non-visual effects of daylight – Part I: photobiology-based model

This paper investigates the formulation of a modelling framework for the non-visual effects of daylight, such as entrainment of the circadian system and maintenance of alertness. The body of empirical data from photobiology studies is now sufficient to start developing preliminary non-visual lighting evaluation methods for lighting design. Eventually, these non-visual effects have the potential to become a relevant quantity to consider when assessing the overall daylighting performance of a space. This paper describes the assumptions and general approach that were developed to propose a modeling framework for occupant exposure to non-visual effects of light, and presents a novel means of visualising the ‘circadian potential’ of a point in space. The proposed approach uses current outcomes of photobiology research to define – at this point static – threshold values for illumination in terms of spectrum, intensity and timing of light at the human eye. These values are then translated into goals for lighting simulation, based on vertical illuminance at the eye, that – ultimately – could become goals for building design. A new climate-based simulation model has been developed to apply these concepts to a residential environment. This will be described in Part 2 of this paper.

Irradiation mapping of complex urban environments: an image-based approach

Abstract This paper describes a novel approach for evaluating the total annual/monthly irradiation incident on building facades in urban settings. The analysis is founded on a physically-based rendering approach and uses data-visualisation techniques to generate ‘maps’ (i.e. false-colour images) of annual/monthly irradiation. The irradiation ‘maps’ are derived from hourly time-series data for 1 year and take accurate account of shading by, and inter-reflection from, other buildings and surfaces. The sun and sky irradiation images are evaluated separately. The sky contribution is calculated using realistic, non-isotropic models for the sky radiance distribution. The ‘maps’ can be used to confidently identify facade-locations where there is high irradiation, for example to aid the siting of photovoltaic (PV) panels. The technique can be applied to scenes of arbitrary complexity from a single building to fully ‘worked-up’ city models. The results of the analysis have been linked to a geographical information system (GIS)-based solar energy planning system. The system is targeted at city planners and one of its aims is to encourage the consideration of solar energy in the urban planning process.

Verification of program accuracy for illuminance modelling: assumptions, methodology and an examination of conflicting findings

,!This paper examines the role of assumptions commonly made in validation studies for lighting simulation programs and quantifies the sensitivity of results to uncertainties in key model parameters such as sky conditions and surface reflectivity. Actually occurring overcast skies are often taken to approximate the CIE standard overcast sky for the purpose of comparing predictions against measurements in real buildings. The validity of this assumption is tested against measurements of the sky luminance distribution for real skies. Illuminance predictions are particularly sensitive to the assigned reflectance of surfaces when the direct component of illumination is small. A number of confounding factors that can lead to imprecise estimates of surface reflectivity for building facades are identified and a methodology to minimize their effect is proposed. This study reveals that commonly made assumptions with respect to sky conditions and moderate imprecision in model parameters can lead to erroneous assessments of program accuracy. The degree to which existing validation findings can be extrapolated to very different application scenarios is discussed in the context of reported conflicting assessments of program accuracy.

Modelling the population dynamics of Calanus in the Fair Isle Current off northern Scotland

The population dynamics of a marine zooplankton species in the Fair Isle Current off northern Scotland have been investigated by modelling and field study. An age- and weight-structured model of a population of the copepods Calanus finmarchicus and Calanus helgolandicus was embedded in a biomass based ecosystem model comprising nutrients, phytoplankton, and other non-Calanus zooplankton. The model was configured to represent a Lagrangian water column drifting in the Fair Isle Current off the north of Scotland during June 1988, with physical characteristics derived from the results of a three-dimensional hydrodynamic model of the northwest European shelf. The time-series results from the model were compared to data from a semi-synoptic field study by assuming the system to be short-term steady state and transposing the spatially resolved field observations into pseudo-time series along the modelled column drift track. The hydrodynamic model correctly reproduced the general physical characteristics of the system which were destratification of an initially stratified water column as a result of advection through a tidally energetic mixing zone, and subsequent re-establishment of stratification with distance downstream. The biological components of the model were broadly successful at reproducing the main features of the phytoplankton biomass response to the physical processes. The field data indicated that, despite the short-term changes in phytoplankton abundance along the drift track, the stage composition and biomass of the Calanus population was relatively stable. However, the model revealed that the main diagnostic features of the response were at the individual level, reflected in the weight at age distribution and reproductive output. The study highlights the difficulty of obtaining adequate data for testing complex models of zooplankton responses to short-term spatio-temporal variations in physical forcing.

Quantification of parallax errors in sky simulator domes for clear sky conditions

Scale model illuminance measurements in sky simulator domes are inherently subject to parallax errors. The magnitude of these errors under a number of Commission Internationale de l’É clairage (CIE) clear sky configurations is quantified using computer simulation techniques. In practical operation of a sky simulator dome, a second parallax error in the normalization measurements for horizontal illuminance is likely to compound the parallax error in the other illuminance measurements. This additional parallax error is accounted for in the simulations. The concept of a parallax-bounded volume is introduced. This is the volume of the dome which, on the basis of parallax alone, must contain a scale model if it is not to be subject to errors in the measurement of illuminance beyond a given tolerance. The findings indicate that, on the basis of a credible design goal for the sky simulator dome, high accuracy illuminance predictions (610%) are practically unattainable.

Sky model blends for predicting internal illuminance: a comparison founded on the BRE-IDMP dataset

The BRE-IDMP validation dataset contains simultaneous measurements of sky luminance patterns and internal illuminances in two full-size office spaces. This benchmark dataset has been applied previously to test the illuminance predictions from a lighting simulation program under real sky conditions. Sky luminance patterns were mapped into the lighting simulation so that the absolute accuracy of the program could be evaluated without the uncertainties that are introduced when sky models are used. For this follow-on study, the BRE-IDMP dataset is now used to quantify the divergence between the sky model generated luminance patterns and the actually occurring conditions based on the resulting internal daylight illuminances. The internal illuminances were predicted using three ‘narrow-range’ models (CIE overcast, CIE clear and intermediate) and the Perez All-Weather model. Predictions from the narrow-range models were used to investigate formulations for sky model blends. The illuminance effect of arbitrary sky model blends is reproduced in a post-process of the illuminance predictions from the ‘narrow-range’ sky model types. The determination of an optimum sky model blend is described. The findings show that relatively simple blends of just two pure sky models (e.g. CIE overcast and intermediate) may be adequate for the prediction of time-varying illuminances founded on climatic test reference year data.