Study of materials performance model for aircraft interiors

A demonstration version of an aircraft interior materials computer data library was developed and contains information on selected materials applicable to aircraft seats and wall panels, including materials for the following: panel face sheets, bond plies, honeycomb, foam, decorative film systems, seat cushions, adhesives, cushion reinforcements, fire blocking layers, slipcovers, decorative fabrics and thermoplastic parts. The information obtained for each material pertains to the material's performance in a fire scenario, selected material properties and several measures of processability

New Tetrahedral Global Minimum for the 98-atom Lennard-Jones Cluster

A new atomic cluster structure corresponding to the global minimum of the 98-atom Lennard-Jones cluster has been found using a variant of the basin-hopping global optimization algorithm. The new structure has an unusual tetrahedral symmetry with an energy of -543.665361, which is 0.022404 lower than the previous putative global minimum. The new LJ_98 structure is of particular interest because its tetrahedral symmetry establishes it as one of only three types of exceptions to the general pattern of icosahedral structural motifs for optimal LJ microclusters. Similar to the other exceptions the global minimum is difficult to find because it is at the bottom of a narrow funnel which only becomes thermodynamically most stable at low temperature.Comment: 3 pages, 2 figures, revte

Simulations and cosmological inference: A statistical model for power spectra means and covariances

We describe an approximate statistical model for the sample variance distribution of the non-linear matter power spectrum that can be calibrated from limited numbers of simulations. Our model retains the common assumption of a multivariate Normal distribution for the power spectrum band powers, but takes full account of the (parameter dependent) power spectrum covariance. The model is calibrated using an extension of the framework in Habib et al. (2007) to train Gaussian processes for the power spectrum mean and covariance given a set of simulation runs over a hypercube in parameter space. We demonstrate the performance of this machinery by estimating the parameters of a power-law model for the power spectrum. Within this framework, our calibrated sample variance distribution is robust to errors in the estimated covariance and shows rapid convergence of the posterior parameter constraints with the number of training simulations.Comment: 14 pages, 3 figures, matches final version published in PR

Arch Stiffness Does Not Determine Running Economy in Recreational Runners

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Unbiased Global Optimization of Lennard-Jones Clusters for N <= 201 by Conformational Space Annealing Method

We apply the conformational space annealing (CSA) method to the Lennard-Jones clusters and find all known lowest energy configurations up to 201 atoms, without using extra information of the problem such as the structures of the known global energy minima. In addition, the robustness of the algorithm with respect to the randomness of initial conditions of the problem is demonstrated by ten successful independent runs up to 183 atoms. Our results indicate that the CSA method is a general and yet efficient global optimization algorithm applicable to many systems.Comment: revtex, 4 pages, 2 figures. Physical Review Letters, in pres

Realizing Opportunities in Forest Growth Modelling

The world is continually changing: the emergence of new technology and new demands for pertinent information pose new challenges and possibilities for forest management. Are forest growth models keeping up with client needs? To remain relevant, modelers need to anticipate client needs, gauge the data needed to satisfy these demands, develop the tools to collect and analyze these data efficiently, and resolve how best to deliver the resulting models and other findings. Researchers and managers should jointly identify and articulate anticipated needs for the future, and initiate action to satisfy them. New technology that offers potential for innovation in forest growth modelling include modelling software, automated data collection, and animation of model outputs. New sensors in the sky and on forest machines can routinely provide data previously considered unattainable (e.g., tree coordinates, crown dimensions), as census rather than sample data. What does this revolution in data availability imply for forest growth models, especially for our choice of driving variables

Superconducting Rebalance Accelerometer

A multi-axis accelerometer which utilizes a magnetically-suspended, high-TC proof mass is under development. The design and performance of a single axis device which is stabilized actively in the axial direction but which utilizes ring magnets for passive radial stabilization is discussed. The design of a full six degree-of-freedom device version is also described

Thermodynamics of C incorporation on Si(100) from ab initio calculations

We study the thermodynamics of C incorporation on Si(100), a system where strain and chemical effects are both important. Our analysis is based on first-principles atomistic calculations to obtain the important lowest energy structures, and a classical effective Hamiltonian which is employed to represent the long-range strain effects and incorporate the thermodynamic aspects. We determine the equilibrium phase diagram in temperature and C chemical potential, which allows us to predict the mesoscopic structure of the system that should be observed under experimentally relevant conditions.Comment: 5 pages, 3 figure

Polytetrahedral Clusters

By studying the structures of clusters bound by a model potential that favours polytetrahedral order, we find a previously unknown series of `magic numbers' (i.e. sizes of special stability) whose polytetrahedral structures are characterized by disclination networks that are analogous to hydrocarbons.Comment: 4 pages, 4 figure

The Reputational Consequences of Failed Replications and Wrongness Admission among Scientists

Scientists are dedicating more attention to replication efforts. While the scientific utility of replications is unquestionable, the impact of failed replication efforts and the discussions surrounding them deserve more attention. Specifically, the debates about failed replications on social media have led to worry, in some scientists, regarding reputation. In order to gain data-informed insights into these issues, we collected data from 281 published scientists. We assessed whether scientists overestimate the negative reputational effects of a failed replication in a scenario-based study. Second, we assessed the reputational consequences of admitting wrongness (versus not) as an original scientist of an effect that has failed to replicate. Our data suggests that scientists overestimate the negative reputational impact of a hypothetical failed replication effort. We also show that admitting wrongness about a non-replicated finding is less harmful to one’s reputation than not admitting. Finally, we discovered a hint of evidence that feelings about the replication movement can be affected by whether replication efforts are aimed one’s own work versus the work of another. Given these findings, we then present potential ways forward in these discussions