Bayesian spline method for assessing extreme loads on wind turbines

This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine structure that the turbine would experience during its service lifetime. A wind turbine should be designed to resist such a high load to avoid catastrophic structural failures. To assess the extreme load, turbine structural responses are evaluated by conducting field measurement campaigns or performing aeroelastic simulation studies. In general, data obtained in either case are not sufficient to represent various loading responses under all possible weather conditions. An appropriate extrapolation is necessary to characterize the structural loads in a turbine's service life. This study devises a Bayesian spline method for this extrapolation purpose, using load data collected in a period much shorter than a turbine's service life. The spline method is applied to three sets of turbine's load response data to estimate the corresponding extreme loads at the roots of the turbine blades. Compared to the current industry practice, the spline method appears to provide better extreme load assessment.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS670 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Field theory in superfluid 3He: What are the lessons for particle physics, gravity and high-temperature superconductivity?

There are several classes of homogeneous Fermi-systems which are characterized by the topology of the energy spectrum of fermionic quasiparticles: (1) Gapless systems with a Fermi-surface; (2) Systems with a gap in their spectrum; (3) Gapless systems with topologically stable point nodes (Fermi points); and (4) Gapless systems with topologically unstable lines of nodes (Fermi lines). Superfluid 3He-A and electroweak vacuum belong to the universality Class (3). The fermionic quasiparticles (particles) in this class are chiral: they are left-handed or right-handed. The collective bosonic modes of systems of Class (3) are the effective gauge and gravitational fields. The great advantage of superfluid 3He-A is that we can perform experiments using this condensed matter and thereby simulate many phenomena in high energy physics, including axial anomaly, baryoproduction, and magnetogenesis. 3He-A textures induce a nontrivial effective metrics of the space, where the free quasiparticles move along geodesics. With 3He-A one can simulate event horizons, Hawking radiation, rotating vacuum, etc. High-temperature superconductors are believed to belong to Class (4). They have gapless fermionic quasiparticles with a "relativistic" spectrum close to gap nodes, which allows application of ideas developed for superfluid 3He-A.Comment: RevTex file, 8 pages, 5 figures, submitted to Proc. Nat. Ac. Sc. US, modified after referee reports, references are adde

Focused ion beam engraved phase-shifted Bragg grating microcavity resonator

A cavity with minimal-volume confinement was created in a microfiber engraving a high-contrast phase-shifted Bragg grating by focused ion beam. While waveguiding by the air/silica boundary provides a diffraction-limited 2D confinement, the grating introduces the third degree of confinement. Theoretical simulations verified the phase-shifted cavity confinement and showed a reasonable agreement with the experimental demonstration. This cavity can find a variety of applications ranging from sensing to quantum dynamic experiments

Atomically Sharp, Closed Bilayer Phosphorene Edges by Self-Passivation

Two-dimensional (2D) crystals' edge structures not only influence their overall properties but also dictate their formation due to edge-mediated synthesis and etching processes. Edges must be carefully examined because they often display complex, unexpected features at the atomic scale, such as reconstruction, functionalization, and uncontrolled contamination. Here, we examine atomic-scale edge structures and uncover reconstruction behavior in bilayer phosphorene. We use in situ transmission electron microscopy (TEM) of phosphorene/graphene specimens at elevated temperatures to minimize surface contamination and reduce e-beam damage, allowing us to observe intrinsic edge configurations. Bilayer zigzag (ZZ) edge was found the most stable edge configuration under e-beam irradiation. Through first-principles calculations and TEM image analysis under various tilting and defocus conditions, we find that bilayer ZZ edges undergo edge reconstruction and so acquire closed, self-passivated edge configurations. The extremely low formation energy of the closed bilayer ZZ edge and its high stability against e-beam irradiation are confirmed by first-principles calculations. Moreover, we fabricate bilayer phosphorene nanoribbons with atomically-sharp closed ZZ edges. The identified bilayer ZZ edges will aid in the fundamental understanding of the synthesis, degradation, reconstruction, and applications of phosphorene and related structures.Comment: 22 pages, 5 figure

Analytical Gradients for Projection-Based Wavefunction-in-DFT Embedding

Projection-based embedding provides a simple, robust, and accurate approach for describing a small part of a chemical system at the level of a correlated wavefunction method while the remainder of the system is described at the level of density functional theory. Here, we present the derivation, implementation, and numerical demonstration of analytical nuclear gradients for projection-based wavefunction-in-density functional theory (WF-in-DFT) embedding. The gradients are formulated in the Lagrangian framework to enforce orthogonality, localization, and Brillouin constraints on the molecular orbitals. An important aspect of the gradient theory is that WF contributions to the total WF-in-DFT gradient can be simply evaluated using existing WF gradient implementations without modification. Another simplifying aspect is that Kohn-Sham (KS) DFT contributions to the projection-based embedding gradient do not require knowledge of the WF calculation beyond the relaxed WF density. Projection-based WF-in-DFT embedding gradients are thus easily generalized to any combination of WF and KS-DFT methods. We provide numerical demonstration of the method for several applications, including calculation of a minimum energy pathway for a hydride transfer in a cobalt-based molecular catalyst using the nudged-elastic-band method at the CCSD-in-DFT level of theory, which reveals large differences from the transition state geometry predicted using DFT.Comment: 15 pages, 4 figure

Electron correlation and Fermi surface topology of Nax_xCoO2_2

The electronic structure of Na$_x$CoO$_2$ revealed by recent photoemission experiments shows important deviations from band theory predictions. The six small Fermi surface pockets predicted by LDA calculations have not been observed as the associated $e_g^\prime$ band fails to cross the Fermi level for a wide range of sodium doping concentration $x$. In addition, significant bandwidth renormalizations of the $t_{2g}$ complex have been observed. We show that these discrepancies are due to strong electronic correlations by studying the multi-orbital Hubbard model in the Hartree-Fock and strong-coupling Gutzwiller approximation. The quasiparticle dispersion and the Fermi surface topology obtained in the presence of strong local Coulomb repulsion are in good agreement with experiments.Comment: 5 pages, 4 figures, revtex4; minor changes, to be published in Phys. Rev. Let

Optimizing Neural Networks with Gradient Lexicase Selection

One potential drawback of using aggregated performance measurement in machine learning is that models may learn to accept higher errors on some training cases as compromises for lower errors on others, with the lower errors actually being instances of overfitting. This can lead to both stagnation at local optima and poor generalization. Lexicase selection is an uncompromising method developed in evolutionary computation, which selects models on the basis of sequences of individual training case errors instead of using aggregated metrics such as loss and accuracy. In this paper, we investigate how lexicase selection, in its general form, can be integrated into the context of deep learning to enhance generalization. We propose Gradient Lexicase Selection, an optimization framework that combines gradient descent and lexicase selection in an evolutionary fashion. Our experimental results demonstrate that the proposed method improves the generalization performance of various widely-used deep neural network architectures across three image classification benchmarks. Additionally, qualitative analysis suggests that our method assists networks in learning more diverse representations. Our source code is available on GitHub: https://github.com/ld-ing/gradient-lexicase.Comment: ICLR 202

Molecular Dynamics Study of Bamboo-like Carbon Nanotube Nucleation

MD simulations based on an empirical potential energy surface were used to study the nucleation of bamboo-like carbon nanotubes (BCNTs). The simulations reveal that inner walls of the bamboo structure start to nucleate at the junction between the outer nanotube wall and the catalyst particle. In agreement with experimental results, the simulations show that BCNTs nucleate at higher dissolved carbon concentrations (i.e., feedstock pressures) than those where non-bamboolike carbon nanotubes are nucleated

Comparing empowering, transformational, and transactional leadership on supervisory coaching and job performance: A multilevel perspective.

Caul read and publishWith a leader being able to possess different types of leadership styles, there is a lack of literature investigating which leadership style best facilitates supervisory coaching behavior. The current study aimed to investigate which leadership style would exhibit supervisory coaching behavior, and if supervisory coaching behavior would mediate the relationship between leadership styles and job performance. The study compared the effects of three leadership styles-transformational, transactional, and empowering leadership-on supervisory coaching behavior, which has been reported to influence job performance. A multilevel approach was adopted in this study using 500 employees from 65 organizations within Malaysia. The study found that only empowering and transactional leadership styles exhibited supervisory coaching behavior, which in turn mediated their relationships with job performance. Overall, the findings suggest the importance of leadership styles that prioritize employee development, as these would lead to improved job performance in employees.Publishe