Postbuckling behaviour of beams with discrete nonlinear restraints

A beam with nonlinearly ‐ elastic lateral restraints attached at discrete points along its span is investigated via analytical and numerical methods. Previous results for the critical moment and the deflected shape based on an eigenvalue analysis of a similar beam with linearly ‐ elastic restraints are discussed, along with a validation of these results against an equivalent finite element model and results from numerical continuation. A beam with nonlinearly ‐ elastic restraints is then analysed with treatments for both quadratic and cubic restraint force–displacement relationships being provided. After formulation of the potential energy functionals, the governing differential equations of the system are derived via the calculus of variations and appropriate boundary conditions are applied. The equations are then solved using the numerical continuation software AUTO ‐ 07p for a standard I ‐ section beam. The variation in elastic critical buckling moment with the linear component of the restraint stiffness is tracked via a two ‐ parameter numerical continuation, allowing determination of the stiffness values at which the critical buckling modes changes qualitatively. Using these stiffness values, subsequent analyses are conducted to examine the influence of the nonlinear component of the restraint stiffness, from which post ‐ buckling equilibrium paths and deformation modes are extracted. The results of these analyses are then compared with an equivalent Rayleigh–Ritz formulation whereby the displacement components are represented by Fourier series. Equilibrium equations are derived by minimizing the potential energy functional with respect to the amplitudes of the constituent harmonics of the Fourier series. The amplitudes are solved for in the post ‐ buckling range by AUTO ‐ O7p and equilibrium paths are produced and compared to the equivalent solutions of the differential equations, with good agreement observed

Individual differences in human annoyance response to noise

Individual variations in annoyance and in susceptibility to noise were studied to establish a finer definition of the ingredients of the human annoyance response. The study involved interactions among a heterogeneous sample of human subjects, various noise stimuli, and different physical environments of exposure. Significant differences in annoyance ratings among the six noise stimuli, all equated for peak sound pressure level, were found

Structure of neutron stars with unified equations of state

We present a set of three unified equations of states (EoSs) based on the nuclear energy-density functional (EDF) theory.These EoSs are based on generalized Skyrme forces fitted to essentially all experimental atomic mass data and constrained to reproduce various properties of infinite nuclear matter as obtained from many-body calculations using realistic two- and three-body interactions. The structure of cold isolated neutron stars is discussed in connection with some astrophysical observations.Comment: 4 pages, to appear in the proceedings of the ERPM conference, Zielona Gora, Poland, April 201

Symmetry energy: nuclear masses and neutron stars

We describe the main features of our most recent Hartree-Fock-Bogoliubov nuclear mass models, based on 16-parameter generalized Skyrme forces. They have been fitted to the data of the 2012 Atomic Mass Evaluation, and favour a value of 30 MeV for the symmetry coefficient J, the corresponding root-mean square deviation being 0.549 MeV. We find that this conclusion is compatible with measurements of neutron-skin thickness. By constraining the underlying interactions to fit various equations of state of neutron matter calculated {\it ab initio} our models are well adapted to a realistic and unified treatment of all regions of neutron stars. We use our models to calculate the composition, the equation of state, the mass-radius relation and the maximum mass. Comparison with observations of neutron stars again favours a value of J = 30 MeV.Comment: 10 pages, 9 figures, to appear in EPJA special volume on symmetry energ

Identifying Galaxy Mergers in Observations and Simulations with Deep Learning

Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any differences between these two classifications. With one of the main difficulties of merger studies being the lack of a truth sample, we can use our method to test biases in visually identified merger catalogues. A convolutional neural network architecture was developed and trained in two ways: one with observations from SDSS and one with simulated galaxies from EAGLE, processed to mimic the SDSS observations. The SDSS images were also classified by the simulation trained network and the EAGLE images classified by the observation trained network. The observationally trained network achieves an accuracy of 91.5% while the simulation trained network achieves 65.2% on the visually classified SDSS and physically classified EAGLE images respectively. Classifying the SDSS images with the simulation trained network was less successful, only achieving an accuracy of 64.6%, while classifying the EAGLE images with the observation network was very poor, achieving an accuracy of only 53.0% with preferential assignment to the non-merger classification. This suggests that most of the simulated mergers do not have conspicuous merger features and visually identified merger catalogues from observations are incomplete and biased towards certain merger types. The networks trained and tested with the same data perform the best, with observations performing better than simulations, a result of the observational sample being biased towards conspicuous mergers. Classifying SDSS observations with the simulation trained network has proven to work, providing tantalizing prospects for using simulation trained networks for galaxy identification in large surveys.Comment: Submitted to A&A, revised after first referee report. 20 pages, 22 figures, 14 tables, 1 appendi

Suppression of spin-pumping by a MgO tunnel-barrier

Spin-pumping generates pure spin currents in normal metals at the ferromagnet (F)/normal metal (N) interface. The efficiency of spin-pumping is given by the spin mixing conductance, which depends on N and the F/N interface. We directly study the spin-pumping through an MgO tunnel-barrier using the inverse spin Hall effect, which couples spin and charge currents and provides a direct electrical detection of spin currents in the normal metal. We find that spin-pumping is suppressed by the tunnel-barrier, which is contrary to recent studies that suggest that the spin mixing conductance can be enhanced by a tunnel-barrier inserted at the interface

De-blending Deep Herschel Surveys: A Multi-wavelength Approach

Cosmological surveys in the far infrared are known to suffer from confusion. The Bayesian de-blending tool, XID+, currently provides one of the best ways to de-confuse deep Herschel SPIRE images, using a flat flux density prior. This work is to demonstrate that existing multi-wavelength data sets can be exploited to improve XID+ by providing an informed prior, resulting in more accurate and precise extracted flux densities. Photometric data for galaxies in the COSMOS field were used to constrain spectral energy distributions (SEDs) using the fitting tool CIGALE. These SEDs were used to create Gaussian prior estimates in the SPIRE bands for XID+. The multi-wavelength photometry and the extracted SPIRE flux densities were run through CIGALE again to allow us to compare the performance of the two priors. Inferred ALMA flux densities (F$^i$), at 870$\mu$m and 1250$\mu$m, from the best fitting SEDs from the second CIGALE run were compared with measured ALMA flux densities (F$^m$) as an independent performance validation. Similar validations were conducted with the SED modelling and fitting tool MAGPHYS and modified black body functions to test for model dependency. We demonstrate a clear improvement in agreement between the flux densities extracted with XID+ and existing data at other wavelengths when using the new informed Gaussian prior over the original uninformed prior. The residuals between F$^m$ and F$^i$ were calculated. For the Gaussian prior, these residuals, expressed as a multiple of the ALMA error ($\sigma$), have a smaller standard deviation, 7.95$\sigma$ for the Gaussian prior compared to 12.21$\sigma$ for the flat prior, reduced mean, 1.83$\sigma$ compared to 3.44$\sigma$, and have reduced skew to positive values, 7.97 compared to 11.50. These results were determined to not be significantly model dependent. This results in statistically more reliable SPIRE flux densities.Comment: 8 pages, 7 figures, 3 tables. Accepted for publication in A&

Giant Pulsar Glitches and the Inertia of Neutron-Star Crusts

Giant pulsar frequency glitches as detected in the emblematic Vela pulsar have long been thought to be the manifestation of a neutron superfluid permeating the inner crust of a neutron star. However, this superfluid has been recently found to be entrained by the crust, and as a consequence it does not carry enough angular momentum to explain giant glitches. The extent to which pulsar-timing observations can be reconciled with the standard vortex-mediated glitch theory is studied considering the current uncertainties on dense-matter properties. To this end, the crustal moment of inertia of glitching pulsars is calculated employing a series of different unified dense-matter equations of state.Comment: 11 pages, 6 figures, submitted to PR

Effects of noise upon human information processing

Studies of noise effects upon human information processing are described which investigated whether or not effects of noise upon performance are dependent upon specific characteristics of noise stimulation and their interaction with task conditions. The difficulty of predicting noise effects was emphasized. Arousal theory was considered to have explanatory value in interpreting the findings of all the studies. Performance under noise was found to involve a psychophysiological cost, measured by vasoconstriction response, with the degree of response cost being related to scores on a noise annoyance sensitivity scale. Noise sensitive subjects showed a greater autonomic response under noise stimulation