Numerical optimisation of mechanical ring reinforcement for bulk high-temperature superconductors

The finite element method has been used extensively in recent years to solve various problems related to applied superconductivity and provides a useful tool for analysing and predicting experimental results. Based on a recently-developed modelling framework, implemented in the finite element software package COMSOL Multiphysics, investigations on the minimum ring reinforcement required to prevent mechanical failure in bulk high-temperature superconducting magnets have been carried out. Assuming homogeneous J$_{c}$(B,T) across the bulk sample irrespective of its dimensions, the maximum magnetic stresses experienced, and the minimum ring thickness required to prevent the hoop and radial stresses from exceeding the tensile strength of the bulk superconductor have been determined for varying values of the Young\u27s modulus, radius, height and temperature of a representative single-grain Ag-containing Gd-Ba-Cu-O bulk sample. This comprehensive analysis details the influence each of these key parameters has on the magnetic stress and hence their impact on the necessary ring thickness to prevent mechanical failure in any given system, i.e., for any combination of material properties and sample dimensions

Numerical optimisation of mechanical ring reinforcement for bulk high-temperature superconductors

Abstract: The finite element method has been used extensively in recent years to solve various problems related to applied superconductivity and provides a useful tool for analysing and predicting experimental results. Based on a recently-developed modelling framework, implemented in the finite element software package COMSOL Multiphysics, investigations on the minimum ring reinforcement required to prevent mechanical failure in bulk high-temperature superconducting magnets have been carried out. Assuming homogeneous Jc (B,T) across the bulk sample irrespective of its dimensions, the maximum magnetic stresses experienced, and the minimum ring thickness required to prevent the hoop and radial stresses from exceeding the tensile strength of the bulk superconductor have been determined for varying values of the Young’s modulus, radius, height and temperature of a representative single-grain Ag-containing Gd-Ba-Cu-O bulk sample. This comprehensive analysis details the influence each of these key parameters has on the magnetic stress and hence their impact on the necessary ring thickness to prevent mechanical failure in any given system, i.e., for any combination of material properties and sample dimensions

Common Scaling Patterns in Intertrade Times of U. S. Stocks

We analyze the sequence of time intervals between consecutive stock trades of thirty companies representing eight sectors of the U. S. economy over a period of four years. For all companies we find that: (i) the probability density function of intertrade times may be fit by a Weibull distribution; (ii) when appropriately rescaled the probability densities of all companies collapse onto a single curve implying a universal functional form; (iii) the intertrade times exhibit power-law correlated behavior within a trading day and a consistently greater degree of correlation over larger time scales, in agreement with the correlation behavior of the absolute price returns for the corresponding company, and (iv) the magnitude series of intertrade time increments is characterized by long-range power-law correlations suggesting the presence of nonlinear features in the trading dynamics, while the sign series is anti-correlated at small scales. Our results suggest that independent of industry sector, market capitalization and average level of trading activity, the series of intertrade times exhibit possibly universal scaling patterns, which may relate to a common mechanism underlying the trading dynamics of diverse companies. Further, our observation of long-range power-law correlations and a parallel with the crossover in the scaling of absolute price returns for each individual stock, support the hypothesis that the dynamics of transaction times may play a role in the process of price formation.Comment: 8 pages, 5 figures. Presented at The Second Nikkei Econophysics Workshop, Tokyo, 11-14 Nov. 2002. A subset appears in "The Application of Econophysics: Proceedings of the Second Nikkei Econophysics Symposium", editor H. Takayasu (Springer-Verlag, Tokyo, 2003) pp.51-57. Submitted to Phys. Rev. E on 25 June 200

Affordances, constraints and information flows as ‘leverage points’ in design for sustainable behaviour

Copyright @ 2012 Social Science Electronic PublishingTwo of Donella Meadows' 'leverage points' for intervening in systems (1999) seem particularly pertinent to design for sustainable behaviour, in the sense that designers may have the scope to implement them in (re-)designing everyday products and services. The 'rules of the system' -- interpreted here to refer to affordances and constraints -- and the structure of information flows both offer a range of opportunities for design interventions to in fluence behaviour change, and in this paper, some of the implications and possibilities are discussed with reference to parallel concepts from within design, HCI and relevant areas of psychology

An open source tool to infer epidemiological and immunological dynamics from serological data: Serosolver

We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and crossreaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk