The phase diagram of Yang-Mills theory with a compact extra dimension

We present a non-perturbative study of the phase diagram of SU(2) Yang-Mills theory in a five-dimensional spacetime with a compact extra dimension. The non-renormalizable theory is regularized on an anisotropic lattice and investigated through numerical simulations in a regime characterized by a hierarchy between the scale of low-energy physics, the inverse compactification radius, and the cutoff scale. We map out the structure of the phase diagram and the pattern of lines corresponding to fixed values of the ratio between the mass of the fifth component of the gauge field and the non-perturbative mass gap of the four-dimensional modes. We discuss different limits of the model, and comment on the implications of our findings.Comment: 17 pages, 9 figure

Carbon brainprint - An estimate of the intellectual contribution of research institutions to reducing greenhouse gas emissions

This is the accepted manuscript of a paper published in Process Safety and Environmental Protection (Chatterton J, et al., Process Safety and Environmental Protection, 2015, 96, 74-81, doi:10.1016/j.psep.2015.04.008). The final version is available at http://dx.doi.org/10.1016/j.psep.2015.04.008Research and innovation have considerable, currently unquantified potential to reduce greenhouse gas emissions by, for example, increasing energy efficiency. Furthermore, the process of knowledge transfer in itself can have a significant impact on reducing emissions, by promoting awareness and behavioural change. The concept of the ‘carbon brainprint’ was proposed to convey the intellectual contribution of higher education institutions to the reduction of greenhouse gas emissions by other parties through research and teaching/training activities. This paper describes an investigation of the feasibility of quantifying the carbon brainprint, through six case studies. The potential brainprint of higher education institutes is shown to be significant: up to 500 kt CO2e/year for one project. The most difficult aspect is attributing the brainprint among multiple participants in joint projects.The Carbon Brainprint project was supported by the Higher Education Funding Council for England (HEFCE) under its Leading Sustainable Development in Higher Education programme, with support for case studies from Santander Universities. HEFCE, Research Councils UK and the Carbon Trust were members of the Steering Committee, which provided guidance, but did not direct the research. The Carbon Trust also advised on best practice in carbon footprinting. We are grateful to the many university staff at Cranfield, Cambridge and Reading Universities who shared their work with us so enthusiastically. We also thank the external partners and clients for the projects on which these case studies are based: Rolls-Royce plc, the ETI NOVA consortium, IGD, the Environment Agency, Esso, Repsol YPF, Carnego Systems Ltd. and Newera Controls Ltd

THE EFFECT OF FOULING ON HEAT TRANSFER, PRESSURE DROP AND THROUGHPUT IN REFINERY PREHEAT TRAINS: OPTIMISATION OF CLEANING SCHEDULES

Optimising cleaning schedules for refinery preheat trains requires a robust and reliable simulator, reliable fouling models and the ability to handle the thermal and hydraulic impacts of fouling. The interaction between thermal and hydraulic effects is explored using engineering analyses and fouling rate laws based on the ‘threshold fouling’ concept; the potential occurrence of a new phenomenon, ‘thermo-hydraulic channeling’ in parallel heat exchangers, is identified. The importance of the foulant thermal conductivity is highlighted. We also report the development of a highly flexible preheat train simulator constructed in MATLAB&#;/Excel&#;. It is able to accommodate variable throughput, control valve operation and different cost scenarios. The simulator is demonstrated on a network of 14 heat exchangers, where the importance of optimising the flow split between parallel streams is illustrated

High-resolution mass models of dwarf galaxies from LITTLE THINGS

We present high-resolution rotation curves and mass models of 26 dwarf galaxies from LITTLE THINGS. LITTLE THINGS is a high-resolution Very Large Array HI survey for nearby dwarf galaxies in the local volume within 11 Mpc. The rotation curves of the sample galaxies derived in a homogeneous and consistent manner are combined with Spitzer archival 3.6 micron and ancillary optical U, B, and V images to construct mass models of the galaxies. We decompose the rotation curves in terms of the dynamical contributions by baryons and dark matter halos, and compare the latter with those of dwarf galaxies from THINGS as well as Lambda CDM SPH simulations in which the effect of baryonic feedback processes is included. Being generally consistent with THINGS and simulated dwarf galaxies, most of the LITTLE THINGS sample galaxies show a linear increase of the rotation curve in their inner regions, which gives shallower logarithmic inner slopes alpha of their dark matter density profiles. The mean value of the slopes of the 26 LITTLE THINGS dwarf galaxies is alpha =-0.32 +/- 0.24 which is in accordance with the previous results found for low surface brightness galaxies (alpha = -0.2 +/- 0.2) as well as the seven THINGS dwarf galaxies (alpha =-0.29 +/- 0.07). However, this significantly deviates from the cusp-like dark matter distribution predicted by dark-matter-only Lambda CDM simulations. Instead our results are more in line with the shallower slopes found in the Lambda CDM SPH simulations of dwarf galaxies in which the effect of baryonic feedback processes is included. In addition, we discuss the central dark matter distribution of DDO 210 whose stellar mass is relatively low in our sample to examine the scenario of inefficient supernova feedback in low mass dwarf galaxies predicted from recent Lambda SPH simulations of dwarf galaxies where central cusps still remain.Peer reviewe