Application of axial discontinuity factors for high conversion water reactors

The paper shows that generating cross sections using three-dimensional geometry and application of axial discontinuity factors are essential requirements for obtaining accurate prediction of criticality and zone average reaction rates in highly heterogeneous RBWR-type systems using computer codes based on diffusion theory approximation. The same methodology as presented here will be used to generate discontinuity factors for each axial interface between fuel assembly zones to ensure preservation of reaction rates in each zone and global multiplication factor. The use of discontinuity factors and three-dimensional cross sections may allow for a coarser energy group structure which is desirable to simplify and speed up transient calculations.

Axial discontinuity factors for the nodal diffusion analysis of high conversion BWR cores

High conversion LWRs concepts typically rely on a heterogeneous core configuration, where fissile zones are interspersed with fertile blanket zones in order to achieve a high conversion ratio. Modeling such a heterogeneous structure of these cores represents a significant challenge to the conventional reactor analysis methods. It was recently suggested to overcome such difficulties, in particular, for the case of axially heterogeneous reduced moderation BWRs, by introducing an additional set of discontinuity factors in axial direction at the interfaces between fissile and fertile fuel assembly zones. However, none of the existing nodal diffusion core simulators have the capability of accounting for discontinuity of homogeneous nodal fluxes in axial direction since the fuel composition of conventional LWRs is much more axially uniform. In this work, we modified the nodal diffusion code DYN3D by introducing such a capability. The new version of the code was tested on a series of reduced moderation BWR cases with Th-U233 and U-Pu-MA fuel. The library of few-group homogenized cross sections and the data required for the calculation of discontinuity factors were generated using the Monte Carlo transport code Serpent. The results obtained with the modified version of DYN3D were compared with the reference Monte Carlo solutions and were found to be in good agreement. The current analysis demonstrates that high conversion LWRs can in principle be modeled using existing nodal diffusion core simulators. © 2013 Elsevier Ltd. All rights reserved.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.

Free energy surface reconstruction from umbrella samples using Gaussian process regression

We demonstrate how the Gaussian process regression approach can be used to efficiently reconstruct free energy surfaces from umbrella sampling simulations. By making a prior assumption of smoothness and taking account of the sampling noise in a consistent fashion, we achieve a significant improvement in accuracy over the state of the art in two or more dimensions or, equivalently, a significant cost reduction to obtain the free energy surface within a prescribed tolerance in both regimes of spatially sparse data and short sampling trajectories. Stemming from its Bayesian interpretation the method provides meaningful error bars without significant additional computation. A software implementation is made available on www.libatoms.org.

Free energy surface reconstruction from umbrella samples using Gaussian process regression II: Multiple collective variables

We demonstrate how a prior assumption of smoothness can be used to enhance the reconstruction of free energy profiles from multiple umbrella sampling simulations using the Bayesian Gaussian process regression approach. The method we derive allows the concurrent use of histograms and free energy gradients and can easily be extended to include further data. In Part I we review the necessary theory and test the method for one collective variable. We demonstrate improved performance with respect to the weighted histogram analysis method and obtain meaningful error bars without any significant additional computation. In Part II we consider the case of multiple collective variables and compare to a reconstruction using least squares fitting of radial basis functions. We find substantial improvements in the regimes of spatially sparse data or short sampling trajectories. A software implementation is made available on www.libatoms.org.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

Geographic distribution of Pelteobagrus fulvidraco and Pelteobagrus vachelli in the Yangtze River based on mitochondrial DNA markers

Three populations of Pelteobagrus vachelli and Pelteobagrus fulvidraco of the Yangtze River were examined by PCR-RFLP analysis of mitochondrial DNA fragments. ND5/6 and D-loop fragments were digested by 10 restriction endonucleases. Significant geographic variations between upstream and mid-downstream populations in the haplotype frequencies and restriction patterns were revealed. This suggested that the diversity of P. vachelli was high; 11 haplotypes were obtained from all the samples. The upstream population shared seven haplotypes and the middle and downstream populations shared another four haplotypes. Among all of the haplotypes, one haplotype was shared in 30 samples of the populations from middle and downstream, but it was not found in the upstream population. Any haplotype found in the upstream population was not detected in the middle and downstream populations. Genetic diversity of P. fulvidraco was low and only five haplotyes were detected from all 60 samples. Phylogenic relationships also indicated that the fishes from upstream and mid-downstream were apparently divided into two populations.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

黄土丘陵区小流域表层土壤的有机碳密度及其空间分布

通过野外调查和室内分析,采用多元线性逐步回归和地理信息系统(GIS)相结合的方法,研究了黄土丘陵区燕沟流域表层(0~20 cm)土壤的有机碳密度、空间分布及其与土地利用类型和地形因子等的关系。结果表明,流域表层土壤有机碳密度平均为1.72 kg/m2,变幅为0.97~2.93 kg/m2;土地利用类型是影响土壤有机碳密度变化的首要因子;流域土壤有机碳密度呈镶嵌的树枝状和条带状空间分布格局,其高值斑块区与乔木林地和灌木林地的分布一致,中值斑块区与草地和川坝地的分布一致,低值斑块区与梯田、果园、坡耕地、疏林地和未成林地的分布一致。流域表层土壤有机碳总储量为76.81×103t。

CO2 Flux Estimation by Different Regression Methods from an Alpine Meadow on the Qinghai-Tibetan Plateau

National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381]; Chinese Academy of Sciences [KZCX2-YW-432]