Ray model and ray-wave correspondence in coupled optical microdisks

We introduce a ray model for coupled optical microdisks, in which we select coupling-efficient rays among the splitting rays. We investigate the resulting phase-space structure and report island structures arising from the ray-coupling between the two microdisks. We find the microdisks's refractive index to influence the phase-space structure and calculate the stability and decay rates of the islands. Turning to ray-wave correspondence, we find many resonances to be directly related to the presence of these islands. We study the relation between the (ray-picture originating) island structures and the (wave-picture originating) spectral properties of resonances, especially the leakiness of the resonances which is represented as the imaginary part of the complex wave vector.Comment: 9 pages, 8 figure

Load management of heat pumps using phase change heat storage

In the UK, heat pumps are often promoted as the means to provide low-carbon space heating and hot water for future dwellings as the electricity supply decarbonises. However, a major issue with growing heat pump use would be the additional load that this could place on the electrical network at times of peak heat and power demand. A means to alleviate potential demand problems is to stagger the operating times of heat pumps by integrating them with thermal buffering. However, focusing on the domestic sector, substantial volumes of thermal storage would be required to achieve the necessary level of operational flexibility in heat pumps and this poses a particular problem in the UK where the floor areas of urban dwellings are small. Thermal storage featuring phase change material (PCM) offers the potential of more volumetrically efficient heat buffering, which may be more suitable for integration into domestic heating systems. In this paper, the potential to shift the operating time of heat pumps integrated with phasechange- material-enhanced thermal storage is assessed and compared to conventional hot water storage, where the limits of flexible operation are determined by the comfort and hot water needs of the end-user. The results indicate that the use of PCM-enhanced thermal storage can reduce the volume of the buffering required for load shifting by up to 3 times. However, thermal buffering with load shifting can increase heat pump energy demand and (at present) in the UK results in increased emissions and cost penalties for the end user

Geospatial Big Data analytics to model the long-term sustainable transition of residential heating worldwide

Geospatial big data analytics has received much attention in recent years for the assessment of energy data. Globally, spatial datasets relevant to the energy field are growing rapidly every year. This research has analysed large gridded datasets of outdoor temperature, end-use energy demand, end-use energy density, population and Gros Domestic Product to end with usable inputs for energy models. These measures have been recognised as a means of informing infrastructure investment decisions with a view to reaching sustainable transition of the residential sector. However, existing assessments are currently limited by a lack of data clarifying the spatio-temporal variations within end-use energy demand. This paper presents a novel Geographical Information Systems (GIS)-based methodology that uses existing GIS data to spatially and temporally assess the global energy demands in the residential sector with an emphasis on space heating. Here, we have implemented an Unsupervised Machine Learning (UML)-based approach to assess large raster datasets of 165 countries, covering 99.6% of worldwide energy users. The UML approach defines lower and upper limits (thresholds) for each raster by applying GIS-based clustering techniques. This is done by binning global high-resolution maps into re-classified raster data according to the same characteristics defined by the thresholds to estimate intranational zones with a range of attributes. The spatial attributes arise from the spatial intersection of re-classified layers. In the new zones, the energy demand is estimated, so-called energy demand zones (EDZs), capturing complexity and heterogeneity of the residential sector. EDZs are then used in energy systems modelling to assess a sustainable scenario for the long-term transition of space heating technology and it is compared with a reference scenario. This long-term heating transition is spatially resolved in zones with a range of spatial characteristics to enhance the assessment of decarbonisation pathways for technology deployment in the residential sector so that global climate targets can be more realistic met

A small-scale process for manufacturing woodwool/cement slabs in developing countries

Woodwool/cement slabs are made from a mixture of shredded timber (woodwool) and cement, shaped or formed by pressure into required thicknesses and sizes. They are a well-known product already used in many countries around the world. This bulletin outlines the work undertaken by the Natural Resources Institute (NRI) on the development of a low-cost woodwool/cement slab manufacturing process appropriate for conditions in developing countries. Typically, 500 slabs (35m3 ) can be produced per week on a single shift employing 25 people. Demonstration plants have been introduced into Malawi and Zambia. Included in the bulletin are historical background information, details and test data on assessing the suitability of timbers, a description of the process developed and the reasons for the processing techniques employed. Methods of handling and the use of the slabs in the construction industry, particularly in relation to the lower-cost housing market in Zambia, are also outlined. One of the main attractions of the NRI small-scale wood wool/ cement slab process plant is the relatively low initial capita! investment required compared with larger, less labour-intensive processes used in Europe a0d'elsewhere. The principal aim has been to develop a low capital cost, labour-intensive plant which could largely be constructed using local manufacturing and craft skills, and operated and maintained on a routine basis by trained personnel

Clustered spatially and temporally resolved global heat and cooling energy demand in the residential sector

Climatic conditions, population density, geography, and settlement structure all have a strong influence on the heating and cooling demand of a country, and thus on resulting energy use and greenhouse gas emissions. In particular, the choice of heating or cooling system is influenced by available energy distribution infrastructure, where the cost of such infrastructure is strongly related to the spatial density of the demand. As such, a better estimation of the spatial and temporal distribution of demand is desirable to enhance the accuracy of technology assessment. This paper presents a Geographical Information System methodology combining the hourly NASA MERRA-2 global temperature dataset with spatially resolved population data and national energy balances to determine global high-resolution heat and cooling energy density maps. A set of energy density bands is then produced for each country using K-means clustering. Finally, demand profiles representing diurnal and seasonal variations in each band are derived to capture the temporal variability. The resulting dataset for 165 countries, published alongside this article, is designed to be integrated into a new integrated assessment model called MUSE (ModUlar energy systems Simulation Environment)but can be used in any national heat or cooling technology analysis. These demand profiles are key inputs for energy planning as they describe demand density and its fluctuations via a consistent method for every country where data is available

Hierarchy of Temporal Responses of Multivariate Self-Excited Epidemic Processes

We present the first exact analysis of some of the temporal properties of multivariate self-excited Hawkes conditional Poisson processes, which constitute powerful representations of a large variety of systems with bursty events, for which past activity triggers future activity. The term "multivariate" refers to the property that events come in different types, with possibly different intra- and inter-triggering abilities. We develop the general formalism of the multivariate generating moment function for the cumulative number of first-generation and of all generation events triggered by a given mother event (the "shock") as a function of the current time $t$. This corresponds to studying the response function of the process. A variety of different systems have been analyzed. In particular, for systems in which triggering between events of different types proceeds through a one-dimension directed or symmetric chain of influence in type space, we report a novel hierarchy of intermediate asymptotic power law decays $\sim 1/t^{1-(m+1)\theta}$ of the rate of triggered events as a function of the distance $m$ of the events to the initial shock in the type space, where $0 < \theta <1$ for the relevant long-memory processes characterizing many natural and social systems. The richness of the generated time dynamics comes from the cascades of intermediate events of possibly different kinds, unfolding via a kind of inter-breeding genealogy.Comment: 40 pages, 8 figure