Non-orientable surface-plus-one-relation groups

Recently Dicks–Linnell determined the L2-Betti numbers of the orientable surface-plus-one-relation groups, and their arguments involved some results that were obtained topologically by Hempel and Howie. Using algebraic arguments, we now extend all these results of Hempel and Howie to a larger class of two-relator groups, and we then apply the extended results to determine the L2-Betti numbers of the non-orientable surface-plus-one-relation group

Observations of Plasma Upflow in a Warm Loop with Hinode/EIS

A complete understanding of Doppler shift in active region loops can help probe the basic physical mechanism involved into the heating of those loops. Here we present observations of upflows in coronal loops detected in a range of temperature temperatures (log T=5.8 - 6.2). The loop was not discernible above these temperatures. The speed of upflow was strongest at the footpoint and decreased with height. The upflow speed at the footpoint was about 20 km/s in Fe VIII which decreased with temperature being about 13 km/s in Fe X, about 8 km/s in Fe XII and about 4 km/s in FeXIII. To the best of our knowledge this is the first observation providing evidence of upflow of plasma in coronal loop structures at these temperatures. We interpret these observations as evidence of chromospheric evaporation in quasi-static coronal loops.Comment: 14 pages, 5 figures, Accepted for Publication in The Astrophysical Journal Letter

Moment free energies for polydisperse systems

A polydisperse system contains particles with at least one attribute $\sigma$ (such as particle size in colloids or chain length in polymers) which takes values in a continuous range. It therefore has an infinite number of conserved densities, described by a density {\em distribution} $\rho(\sigma)$. The free energy depends on all details of $\rho(\sigma)$, making the analysis of phase equilibria in such systems intractable. However, in many (especially mean-field) models the {\em excess} free energy only depends on a finite number of (generalized) moments of $\rho(\sigma)$; we call these models truncatable. We show, for these models, how to derive approximate expressions for the {\em total} free energy which only depend on such moment densities. Our treatment unifies and explores in detail two recent separate proposals by the authors for the construction of such moment free energies. We show that even though the moment free energy only depends on a finite number of density variables, it gives the same spinodals and critical points as the original free energy and also correctly locates the onset of phase coexistence. Results from the moment free energy for the coexistence of two or more phases occupying comparable volumes are only approximate, but can be refined arbitrarily by retaining additional moment densities. Applications to Flory-Huggins theory for length-polydisperse homopolymers, and for chemically polydisperse copolymers, show that the moment free energy approach is computationally robust and gives new geometrical insights into the thermodynamics of polydispersity.Comment: RevTeX, 43 pages including figure

Hierarchical Knowledge-Gradient for Sequential Sampling

We consider the problem of selecting the best of a finite but very large set of alternatives. Each alternative may be characterized by a multi-dimensional vector and has independent normal rewards. This problem arises in various settings such as (i) ranking and selection, (ii) simulation optimization where the unknown mean of each alternative is estimated with stochastic simulation output, and (iii) approximate dynamic programming where we need to estimate values based on Monte-Carlo simulation. We use a Bayesian probability model for the unknown reward of each alternative and follow a fully sequential sampling policy called the knowledge-gradient policy. This policy myopically optimizes the expected increment in the value of sampling information in each time period. Because the number of alternatives is large, we propose a hierarchical aggregation technique that uses the common features shared by alternatives to learn about many alternatives from even a single measurement, thus greatly reducing the measurement effort required. We demonstrate how this hierarchical knowledge-gradient policy can be applied to efficiently maximize a continuous function and prove that this policy finds a globally optimal alternative in the limit

Nondestructive Testing Methods Aided Via Numerical Computation Models for Various Critical Aerospace Power Generation Systems

A current critical necessity for all industries which utilize various equipment that operates in high temperature and extreme environments, is the ability to collect and analyze data via non destructive testing (NDT) methods. Operational conditions and material health must be constantly monitored if components are to be implemented precisely to increase the overall performance and efficiency of the process. Currently in both aerospace and power generation systems there are many methods that are being employed to gather several necessary properties and parameters of a given system. This work will focus primarly on two of these NDT methods, with the ultimate goal of contributing to not only the method itself, but also the role of numerical computation to increase the resolution of a given technique. Numerical computation can attribute knowledge onto the governing mechanics of these NDT methods, many of which are currently being utilized in industry. An increase in the accuracy of the data gathered from NDT methods will ultimately lead to an increase in operational efficiency of a given system. The first method to be analyzed is a non destructive emmision technique widely referred to as accoustic ultrasonic thermography. This work will investigate the mechanism of heat generation in acoustic thermography using a combination of numerical computational analysis and physical experimentation. Many of the challenges typical of this type of system are addressed in this work. The principal challenges among them are crack detection threshold, signature quality and the effect of defect interactions. Experiments and finite element based numerical simulations are employed, in order to evaluate the proposed method, as well as draw conclusions on the viability for future extension and integration with other digital technologies for health monitoring. A method to determine the magnitude of the different sources of heat generation during an acoustic excitation is also achieved in this work. Defects formed through industrial operation as well as defects formed through artificial manufacturing methods were analyzed and compared. The second method is a photoluminescence piezospectroscopic (PLPS) for composite materials. The composite studied in this work has one host material which does not illuminate or have photoluminescence properties, the second material provides the luminescence properties, as well as additional overall strength to the composite material. Understanding load transfer between the reinforcements and matrix materials that constitute these composites hold the key to elucidating their mechanical properties and consequent behavior in operation. Finite element simulations of loading effects on representative embedded alumina particles in a matrix were investigated and compared with experimental results. The alumina particles were doped with chromium in order to achieve luminscence capability, and therefore take advantage of the piezospectrscopic measurement technique. Mechanical loading effects on alumina nanoparticle composites can be captured with Photo stimulated luminescent spectroscopy, where spectral shifts from the particles are monitored with load. The resulting piezospectroscopic (PS) coefficients are then used to calculate load transfer between the matrix and particle. The results from the simulation and experiments are shown to be in general agreement of increase in load transferred with increasing particle volume fraction due to contact stresses that are dominant at these higher volume fractions. Results from this work present a combination of analytical and experimental insight into the effect of particle volume fraction on load transfer in ceramic composites that can serve to determine properties and eventually optimize various parameters such as particle shape, size and dispersion that govern the design of these composites prior to manufacture and testing

Uptake of Micro-generation among Small Organisations in the Camden Climate Change Alliance

The recent introduction of feed-in tariffs and renewable heat incentives in the UK has provided a new financial incentive for the installation of micro-generation, but so far there has been limited research on its uptake in small organisations. Our research starts to fill that gap by presenting a unique case study of the Camden Climate Change Alliance (CCCA) of small organisations to explore the perceived barriers and incentives to installation among members. We assess how micro-generation is viewed in the context of wider environmental measures to discover that ‘green marketing’ provides a strong incentive while upfront costs remain the primary barrier. Participants in the study prioritise energy efficiency over micro-generation due to shorter paybacks, which leads us to propose an Energy Hierarchy Framework model as a useful tool towards the adoption of micro-generation in SMEs and other small organisations. The CCCA is successful at enabling small organisations to participate in environmental management by offering free workshops, audits and events. As a large proportion of UK carbon emissions derive from small organisations, reductions could be achieved through the setting up of similar climate change alliances by local authorities in other areas of the country

A New Optimal Stepsize For Approximate Dynamic Programming

Approximate dynamic programming (ADP) has proven itself in a wide range of applications spanning large-scale transportation problems, health care, revenue management, and energy systems. The design of effective ADP algorithms has many dimensions, but one crucial factor is the stepsize rule used to update a value function approximation. Many operations research applications are computationally intensive, and it is important to obtain good results quickly. Furthermore, the most popular stepsize formulas use tunable parameters and can produce very poor results if tuned improperly. We derive a new stepsize rule that optimizes the prediction error in order to improve the short-term performance of an ADP algorithm. With only one, relatively insensitive tunable parameter, the new rule adapts to the level of noise in the problem and produces faster convergence in numerical experiments.Comment: Matlab files are included with the paper sourc

A Participational Managerial Method to Implement and Evaluate Information Security within a Healthcare Organizaton

The use of participational approaches to system design has been debated for a number of years. In some situations it seems that participational approaches are not a suitable or practical method by which to design an Information System or to analyse a problem. Within this paper we describe a framework in which participation plays an active and effective role and describe a method that was used to effectively design information systems and implement computer security countermeasures