Carbon transition efficiency and process cost in high-rate, large-area deposition of diamond films by DC arc plasma jet

A new DC plasma torch in which are jet states and deposition parameters can be regulated over a wide range has been built. It showed advantages in producing stable plasma conditions at a small gas flow rate. Plasma jets with and without magnetically rotated arcs could be generated. With straight are jet deposition, diamond films could be formed at a rate of 39 mu m/h on Mo substrates of Phi 25 mm, and the conversion rate of carbon in CH4 to diamond was less than 3%. Under magnetically rotated conditions, diamond films could be deposited uniformly in a range of Phi 40 mm at 30 mu m/h, with a quite low total gas flow rate and high carbon conversion rate of over 11%. Mechanisms of rapid and uniform deposition of diamond films with low gas consumption and high carbon transition efficiency are discussed.

Gasdynamic Heating Process Suitable for Manufacturing Ethene by Pyrolysis

对乙烷裂解制造乙烯的非平衡过程进行了分析,为了获得高的乙烯产率,需准确控制裂解停留时间并提高裂解反应温度,探讨了目前工业生产中普遍采用的管式裂解炉的特性及局限,这种管式裂解炉的性能虽己接近完善,但仍不能满足裂解工艺需求,对几种利用激波控制加热方法生产乙烯的发明及其不足进行了评述,提出新颖的反向超声速射流混合加热方法,该方法能满足裂解制造乙烯的要求。

Numerical simulation of rock failure and earthquake process on mesoscopic scale

On the basis of the lattice model of MORA and PLACE, Discrete Element Method, and Molecular Dynamics approach, another kind of numerical model is developed. The model consists of a 2-D set of particles linked by three kinds of interactions and arranged into triangular lattice. After the fracture criterion and rules of changes between linking states are given, the particle positions, velocities and accelerations at every time step are calculated using a finite-difference scheme, and the configuration of particles can be gained step by step. Using this model, realistic fracture simulations of brittle solid (especially under pressure) and simulation of earthquake dynamics are made.

3D simulation of the micro indentation process and relative problems research

In this paper the finite element method was used to simulate micro-scale indentation process. The several standard indenters were simulated with 3D finite element model. The emphasis of this paper was the differences between 2D axisymmetric cone model and

Sedimentation Process of Saturated Sand under Impact Loading

The initial small inhomogeneity of saturated sand could be amplified during the sedimentation process after liquefaction, and cracks could be observed in the sand column. Layers of fine sand could also be found at the exact place where cracks developed and disappeared. The phenomena and the whole process were experimentally shown by X-rays images. To account for the phenomena, a linearized stability analysis of the sedimentation of saturated sand was conducted; however, it did not produce a satisfactory result. A three-phase flow model describing the transportation of fine sand is presented in this paper. It is shown that such a kind of erosion/deposition model was qualitatively in good agreement with the experimental observation.

Molecular dynamics simulation on dislocation emission process

A correlative reference model for a computer simulation of molecular dynamics is proposed in this paper. Based on this model, a flexible displacement boundary scheme is naturally introduced and the dislocations emitted from a crack tip are presumed to continuously pass through the border of an inner discrete atomic region to pile up at an outer continuum region. The simulations for a Mo crystal show that the interaction between a crack and emitted dislocations results in the decrease in local stress intensity factor gradually.

An overview of air-sea interface process studies

Recent progress in the study of air-sea interface processes for momentum, heat, moisture and mass transfer are reviewed in the present article. Except for turbulent structure, we have analysed the other physical mechanisms occurring in the wave boundary layer, such as the roles of the sea surface state, droplets and bubbles due to wave breaking, which at least partly account for the existing discrepancies between theory and observations. The experiments, both over the ocean and in the laboratory, are described briefly. In conclusion, a few perspective trends in this area are suggested for further investigation.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

Moment Tensor Analysis of the Acoustic Emission Source in the Rock Damage Process

To further investigate the mechanism of acoustic emission (AE) in the rock fracture experiment, moment tensor analysis was carried out. The AE sources characterized by crack sizes, orientations and fracture modes, are represented by a time-dependent momen

Numerical Simulation of Transient Thermal Field in Laser Melting Process

Numerical simulation of thermal field was studied in laser processing. The 3-D finite element model of transient thermal calculation is given by thermal conductive equation. The effects of phase transformation latent are considered. Numerical example is given to verify the model. Finally the real example of transient thermal field is given.

Tractable nonparametric bayesian inference in poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finitedimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets. Copyright 2009.

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities

The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity. The combination of a Poisson process and GP is known as a Gaussian Cox process, or doubly-stochastic Poisson process. Likelihood-based inference in these models requires an intractable integral over an infinite-dimensional random function. In this paper we present the first approach to Gaussian Cox processes in which it is possible to perform inference without introducing approximations or finite-dimensional proxy distributions. We call our method the Sigmoidal Gaussian Cox Process, which uses a generative model for Poisson data to enable tractable inference via Markov chain Monte Carlo. We compare our methods to competing methods on synthetic data and apply it to several real-world data sets.