The capability-affordance model: a method for analysis and modelling of capabilities and affordances

Existing capability models lack qualitative and quantitative means to compare business capabilities. This paper extends previous work and uses affordance theories to consistently model and analyse capabilities. We use the concept of objective and subjective affordances to model capability as a tuple of a set of resource affordance system mechanisms and action paths, dependent on one or more critical affordance factors. We identify an affordance chain of subjective affordances by which affordances work together to enable an action and an affordance path that links action affordances to create a capability system. We define the mechanism and path underlying capability. We show how affordance modelling notation, AMN, can represent affordances comprising a capability. We propose a method to quantitatively and qualitatively compare capabilities using efficiency, effectiveness and quality metrics. The method is demonstrated by a medical example comparing the capability of syringe and needless anaesthetic systems.

Teleconnections between Ethiopian summer rainfall and sea surface temperature: part I. Observation and modelling

In this study, the oceanic regions that are associated with anomalous Ethiopian summer rains were identified and the teleconnection mechanisms that give rise to these associations have been investigated. Because of the complexities of rainfall climate in the horn of Africa, Ethiopia has been subdivided into six homogeneous rainfall zones and the influence of SST anomalies was analysed separately for each zone. The investigation made use of composite analysis and modelling experiments. Two sets of composites of atmospheric fields were generated, one based on excess/deficit rainfall anomalies and the other based on warm/cold SST anomalies in specific oceanic regions. The aim of the composite analysis was to determine the link between SST and rainfall in terms of large scale features. The modelling experiments were intended to explore the causality of these linkage. The results show that the equatorial Pacific, the midlatitude northwest Pacific and the Gulf of Guinea all exert an influence on the summer rainfall in various part of the country. The results demonstrate that different mechanisms linked to sea surface temperature control variations in rainfall in different parts of Ethiopia. This has important consequences for seasonal forecasting models which are based on statistical correlations between SST and seasonal rainfall totals. It is clear that such statistical models should take account of the local variations in teleconnections.

Introduction. Stochastic physics and climate modelling

Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.

A general-method for tracking analysis and its application to meteorological data

Recent interest in the validation of general circulation models (GCMs) has been devoted to objective methods. A small number of authors have used the direct synoptic identification of phenomena together with a statistical analysis to perform the objective comparison between various datasets. This paper describes a general method for performing the synoptic identification of phenomena that can be used for an objective analysis of atmospheric, or oceanographic, datasets obtained from numerical models and remote sensing. Methods usually associated with image processing have been used to segment the scene and to identify suitable feature points to represent the phenomena of interest. This is performed for each time level. A technique from dynamic scene analysis is then used to link the feature points to form trajectories. The method is fully automatic and should be applicable to a wide range of geophysical fields. An example will be shown of results obtained from this method using data obtained from a run of the Universities Global Atmospheric Modelling Project GCM.

Monitoring and modelling the three-dimensional flow of water under drip irrigation

The interpretation of soil water dynamics under drip irrigation systems is relevant for crop production as well as on water use and management. In this study a three-dimensional representation of the flow of water under drip irrigation is presented. The work includes analysis of the water balance at point scale as well as area-average, exploring uncertainties in water balance estimations depending on the number of locations sampled. The water flow was monitored by detailed profile water content measurements before irrigation, after irrigation and 24 h later with a dense array of soil moisture access tubes radially distributed around selected drippers. The objective was to develop a methodology that could be used on selected occasions to obtain 'snap shots' of the detailed three-dimensional patterns of soil moisture. Such patterns are likely to be very complex, as spatial variability will be induced for a number of reasons, such as strong horizontal gradients in soil moisture, variations between individual sources in the amount of water applied and spatial variability is soil hydraulic properties. Results are compared with a widely used numerical model, Hydrus-2D. The observed dynamic of the water content distribution is in good agreement with model simulations, although some discrepancies concerning the horizontal distribution of the irrigation bulb are noted due to soil heterogeneity. (c) 2006 Elsevier B.V. All rights reserved.

Crumpet structures: experimental and modelling studies

Crumpets are made by heating fermented batter on a hot plate at around 230°C. The characteristic structure dominated by vertical pores develops rapidly: structure has developed throughout around 75% of the product height within 30s, which is far faster than might be expected from transient heat conduction through the batter. Cooking is complete within around 3 min. Image analysis based on results from X-ray tomography shows that the voidage fraction is approximately constant and that there is continual coalescence between the larger pores throughout the product although there is also a steady level of small bubbles trapped within the solidified batter. We report here experimental studies which shed light on some of the mechanisms responsible for this structure, together with some models of key phenomena.Three aspects are discussed here: the role of gas (carbon dioxide and nitrogen) nuclei in initiating structure development; convective heat transfer inside the developing pores; and the kinetics of setting the batter into an elastic solid structure. It is shown conclusively that the small bubbles of carbon dioxide resulting from the fermentation stage play a crucial role as nuclei for pore development: without these nuclei, the result is not a porous structure, but rather a solid, elastic, inedible, gelatinized product. These nuclei are also responsible for the tiny bubbles which are set in the final product. The nuclei form the source of the dominant pore structure which is largely driven by the, initially explosive, release of water vapour from the batter together with the desorption of dissolved carbon dioxide. It is argued that the rapid evaporation, transport and condensation of steam within the growing pores provides an important mechanism, as in a heat pipe, for rapid heat transfer, and models for this process are developed and tested. The setting of the continuous batter phase is essential for final product quality: studies using differential scanning calorimetry and on the kinetics of change in the visco-elastic properties of the batter suggest that this process is driven by the kinetics of gelatinization. Unlike many thermally driven food processes the rates of heating are such that gelatinization kinetics cannot be neglected. The implications of these results for modelling and for the development of novel structures are discussed.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.

Measurements and modelling of airflows in houses using passive sampling and HAM software

Passive samplers have been predominantly used to monitor environmental conditions in single volumes. However, measurements using a calibrated passive sampler- Solid Phase Microextraction (SPME) fibre, in three houses with cold pitched roof, successfully demonstrated the potential of the SPME fibre as a device for monitoring air movement in two volumes. The roofs monitored were pitched at 15° - 30° with insulation thickness varying between 200-300 mm on the ceiling. For effective analysis, two constant sources of volatile organic compounds were diffused steadily in the house. Emission rates and air movement from the house to the roof was predicted using developed algorithms. The airflow rates which were calibrated against conventional tracer gas techniques were introduced into a HAM software package to predict the effects of air movement on other varying parameters. On average it was shown from the in situ measurements that about 20-30% of air entering the three houses left through gaps and cracks in the ceiling into the roof. Although these field measurements focus on the airflows, it is associated with energy benefits such that; if these flows are reduced then significantly energy losses would also be reduced (as modelled) consequently improving the energy efficiency of the house. Other results illustrated that condensation formation risks were dependent on the airtightness of the building envelopes including configurations of their roof constructions.

Analysis and modeling of active occupancy of the residential sector in Spain: an indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.