FITTING A PARAMETRIC MODEL TO A CLOUD OF POINTS VIA OPTIMIZATION METHODS

Computer Aided Design (CAD) is a powerful tool for designing parametric geometry. However, many CAD models of current configurations are constructed in previous generations of CAD systems, which represent the configuration simply as a collection of surfaces instead of as a parametrized solid model. But since many modern analysis techniques take advantage of a parametrization, one often has to re-engineer the configuration into a parametric model. The objective here is to generate an efficient, robust, and accurate method for fitting parametric models to a cloud of points. The process uses a gradient-based optimization technique, which is applied to the whole cloud, without the need to segment or classify the points in the cloud a priori. First, for the points associated with any component, a variant of the Levenberg-Marquardt gradient-based optimization method (ILM) is used to find the set of model parameters that minimizes the least-square errors between the model and the points. The efficiency of the ILM algorithm is greatly improved through the use of analytic geometric sensitivities and sparse matrix techniques. Second, for cases in which one does not know a priori the correspondences between points in the cloud and the geometry model\u27s components, an efficient initialization and classification algorithm is introduced. While this technique works well once the configuration is close enough, it occasionally fails when the initial parametrized configuration is too far from the cloud of points. To circumvent this problem, the objective function is modified, which has yielded good results for all cases tested. This technique is applied to a series of increasingly complex configurations. The final configuration represents a full transport aircraft configuration, with a wing, fuselage, empennage, and engines. Although only applied to aerospace applications, the technique is general enough to be applicable in any domain for which basic parametrized models are available

工业生态与节能——面向工业车间非均匀热环境营造的低碳空调系统

The problem of indoor heat supply in industrial workshops in high latitude areas in winter is complex. The energy consumption of air conditioners used in most workshops is huge. In this paper, an innovative industrial low carbon air conditioning design based on the concept of “nonuniform thermal environment” is proposed. Through orthogonal experiment and three-level evaluation, the best operating parameters and energy-saving effect of air conditioning are obtained

Dirac Fermion in Strongly-Bound Graphene Systems

It is highly desirable to integrate graphene into existing semiconductor technology, where the combined system is thermodynamically stable yet maintain a Dirac cone at the Fermi level. Firstprinciples calculations reveal that a certain transition metal (TM) intercalated graphene/SiC(0001), such as the strongly-bound graphene/intercalated-Mn/SiC, could be such a system. Different from free-standing graphene, the hybridization between graphene and Mn/SiC leads to the formation of a dispersive Dirac cone of primarily TM d characters. The corresponding Dirac spectrum is still isotropic, and the transport behavior is nearly identical to that of free-standing graphene for a bias as large as 0.6 V, except that the Fermi velocity is half that of graphene. A simple model Hamiltonian is developed to qualitatively account for the physics of the transfer of the Dirac cone from a dispersive system (e.g., graphene) to an originally non-dispersive system (e.g., TM).Comment: Apr 25th, 2012 submitte

Method based on fast fourier transform for calculating conical refraction of beams with noncircular symmetry

Conical refraction of optical beams with circular symmetry is often analyzed using Belsky-Khapalyuk-Berry (BKB) theory; however, for beams with noncircular symmetry, it is difficult to obtain analytical expressions for far-field diffraction patterns. We propose a method, based on fast Fourier transform (FFT), for calculating conical refraction of beams with noncircular symmetry and verify it experimentally using a quasi-plane wave passing through a square aperture and focusing lens. Excellent agreement between theoretical and experimental results has been achieved

Nodeless superconductivity in the presence of spin-density wave in pnictide superconductors: The case of BaFe2−x_{2-x}Nix_{x}As2_{2}

The characteristics of Fe-based superconductors are manifested in their electronic, magnetic properties, and pairing symmetry of the Cooper pair, but the latter remain to be explored. Usually in these materials, superconductivity coexists and competes with magnetic order, giving unconventional pairing mechanisms. We report on the results of the bulk magnetization measurements in the superconducting state and the low-temperature specific heat down to 0.4 K for BaFe$_{2-x}$Ni$_{x}$As$_{2}$ single crystals. The {electronic} specific heat displays a pronounced anomaly at the superconducting transition temperature and a small residual part {at low temperatures in the superconducting state}. The normal-state Sommerfeld coefficient increases with Ni doping for $x$ = 0.092, 0.096, and 0.10, which illustrates the competition between magnetism and superconductivity. Our analysis of the temperature dependence of the superconducting-state specific heat and the London penetration depth provides strong evidence for a two-band $s$-wave order parameter. Further, the data of the London penetration depth calculated from the lower critical field follow an exponential temperature dependence, characteristic of a fully gapped superconductor. These observations clearly show that the superconducting gap in the nearly optimally doped compounds is nodeless.Comment: 11 pages, 5 figure