Information Preservation Modeling of Rayleigh-Benard Transition from Thermal Conduction to Convection

Onset and evolution of the Rayleigh-Benard (R-B) convection are investigated using the Information Preservation (IP) method. The information velocity and temperature are updated using the Octant Flux Splitting (OFS) model developed by Masters & Ye based on the Maxwell transport equation suggested by Sun & Boyd. Statistical noise inherent in particle approaches such as the direct simulation Monte Carlo (DSMC) method is effectively reduced by the IP method, and therefore the evolutions from an initial quiescent fluid to a final steady state are shown clearly. An interesting phenomenon is observed: when the Rayleigh number (Ra) exceeds its critical value, there exists an obvious incubation stage. During the incubation stage, the vortex structure clearly appears and evolves, whereas the Nusselt number (Nu) of the lower plate is close to unity. After the incubation stage, the vortex velocity and Nu rapidly increase, and the flow field quickly reaches a steady, convective state. A relation of Nu to Ra given by IP agrees with those given by DSMC, the classical theory and experimental data.

Rarefied gas dynamics: fundamentals, simulations and micro flows

Kinetic studies of gas flows

Our recent studies on kinetic behaviors of gas flows are reviewed in this paper. These flows have a wide range of background, but share a common feature that the flow Knudsen number is larger than 0.01. Thus kinetic approaches such as the direct simulation Monte Carlo method are required for their description. In the past few years, we studied several micro/nano-scale flows by developing novel particle simulation approach, and investigated the flows in low-pressure chambers and at high altitude. In addition, the microscopic behaviors of a couple of classical flow problems were analyzed, which shows the potential for kinetic approaches to reveal the microscopic mechanism of gas flows.

Two-phase flow and pool boiling heat transfer in microgravity

Researches on two-phase flow and pool boiling heat transfer in microgravity, which included groundbased tests, flight experiments, and theoretical analyses, were conducted in the National Microgravity Laboratory/CAS. A semi-theoretical Weber number model was proposed to predict the slug-to-annular flow transition of two-phase gas–liquid flows in microgravity, while the influence of the initial bubble size on the bubble-to-slug flow transition was investigated numerically using the Monte Carlo method. Two-phase flow pattern maps in microgravity were obtained in the experiments both aboard the Russian space station Mir and aboard IL-76 reduced gravity airplane. Mini-scale modeling was also used to simulate the behavior of microgravity two-phase flow on the ground. Pressure drops of two-phase flow in microgravity were also measured experimentally and correlated successfully based on its characteristics. Two space experiments on pool boiling phenomena in microgravity were performed aboard the Chinese recoverable satellites. Steady pool boiling of R113 on a thin wire with a temperature-controlled heating method was studied aboard RS-22, while quasi-steady pool boiling of FC-72 on a plate was studied aboard SJ-8. Ground-based experiments were also performed both in normal gravity and in short-term microgravity in the drop tower Beijing. Only slight enhancement of heat transfer was observed in the wire case, while enhancement in low heat flux and deterioration in high heat flux were observed in the plate case. Lateral motions of vapor bubbles were observed before their departure in microgravity. The relationship between bubble behavior and heat transfer on plate was analyzed. A semi-theoretical model was also proposed for predicting the bubble departure diameter during pool boiling on wires. The results obtained here are intended to become a powerful aid for further investigation in the present discipline and development of two-phase systems for space applications.

Multiscale model reduction methods for deterministic and stochastic partial differential equations

Partial differential equations (PDEs) with multiscale coefficients are very difficult to solve due to the wide range of scales in the solutions. In the thesis, we propose some efficient numerical methods for both deterministic and stochastic PDEs based on the model reduction technique.

For the deterministic PDEs, the main purpose of our method is to derive an effective equation for the multiscale problem. An essential ingredient is to decompose the harmonic coordinate into a smooth part and a highly oscillatory part of which the magnitude is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is smooth, and could be resolved on a regular coarse mesh grid. Furthermore, we provide error analysis and show that the solution to the effective equation plus a correction term is close to the original multiscale solution.

For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities.

For both the deterministic and stochastic PDEs, numerical results are presented to demonstrate the accuracy and robustness of the methods. We also show the computational time cost reduction in the numerical examples.

蒙特卡罗模拟四极阱中原子的参变激发

在中性原子的磁囚禁实验中,磁阱线圈的电流噪声会激发磁阱中的原子运动,势必对原子团的温度和寿命产生不可忽视的影响。对于非简谐阱,这种激发具有能量选择特性,它又取决于电流噪声的频谱分布。选择了实验中常用的四极阱为研究对象,用直接模拟蒙特卡罗方法来模拟四极阱中原子运动的参变激发现象,得到了原子温度与原子数损失随激发频率的变化关系,并进一步计算了两个共振峰处原子温度随调制时间和调制深度的变化曲线。此外,还研究了弹性碰撞速率对参变激发过程中原子温度上升的影响。这些结果对四极阱参变激发的实验有较好的参考价值。

光通过纳米颗粒随机散射体透射光强的计算及分析

光通过随机散射体后透射光强的估算,对于提取散射体内部无法直接测量或者无法直接观察的信息至关重要。在分析平行光束通过纳米圆形颗粒随机散射体出射面上光强组成的基础上推导了透射光强的计算公式,并指出多重散射理论、一阶多重散射理论和朗伯比尔定律在一定近似程度上可以相对精确地估算透射光强。这三种方法的估算结果之间会出现四种相对关系。根据这些相对关系,分析了光在散射体内部传输时散射过程的特征以及各种散射过程对出射面光强的贡献大小。

Desenvolvimento de um simulador para espectrometria por fluorescência de raios X usando computação distribuída

A Física das Radiações é um ramo da Física que está presente em diversas áreas de estudo e se relaciona ao conceito de espectrometria. Dentre as inúmeras técnicas espectrométricas existentes, destaca-se a espectrometria por fluorescência de raios X. Esta também possui uma gama de variações da qual pode-se dar ênfase a um determinado subconjunto de técnicas. A produção de fluorescência de raios X permite (em certos casos) a análise das propriedades físico-químicas de uma amostra específica, possibilitando a determinação de sua constituiçõa química e abrindo um leque de aplicações. Porém, o estudo experimental pode exigir uma grande carga de trabalho, tanto em termos do aparato físico quanto em relação conhecimento técnico. Assim, a técnica de simulação entra em cena como um caminho viável, entre a teoria e a experimentação. Através do método de Monte Carlo, que se utiliza da manipulação de números aleatórios, a simulação se mostra como uma espécie de alternativa ao trabalho experimental.Ela desenvolve este papel por meio de um processo de modelagem, dentro de um ambiente seguro e livre de riscos. E ainda pode contar com a computação de alto desempenho, de forma a otimizar todo o trabalho por meio da arquitetura distribuída. O objetivo central deste trabalho é a elaboração de um simulador computacional para análise e estudo de sistemas de fluorescência de raios X desenvolvido numa plataforma de computação distribuída de forma nativa com o intuito de gerar dados otimizados. Como resultados deste trabalho, mostra-se a viabilidade da construção do simulador através da linguagem CHARM++, uma linguagem baseada em C++ que incorpora rotinas para processamento distribuído, o valor da metodologia para a modelagem de sistemas e a aplicação desta na construção de um simulador para espectrometria por fluorescência de raios X. O simulador foi construído com a capacidade de reproduzir uma fonte de radiação eletromagnética, amostras complexas e um conjunto de detectores. A modelagem dos detectores incorpora a capacidade de geração de imagens baseadas nas contagens registradas. Para validação do simulador, comparou-se os resultados espectrométricos com os resultados gerados por outro simulador já validado: o MCNP.

星载激光对水下目标通信可行性研究

The characteristics of media in communication channel are analyzed briefly and the reasonable optical parameters of media are adopted. With certain communication system parameters the temporal and spatial distributions of the received signal from submerged platform are simulated using Monte Carlo method. The upper limit of the ratio of Monte Carlo estimated error to averaged value is about 0.3%. From the simulated results, the optimized sampling timing of receiver and field of view of telescope are obtained. Also the signal-to-noise ratio of the receiver is calculated. Based on this, the error probability of the communication system is deduced from laser pulse position modulation and maximum likelihood detection. The results show that under severe environment robust laser communication from a satellite to a submerged platform can be achieved.

Extended bidirectional reflectance distribution function for polarized light scattering from subsurface defects under a smooth surface

By introducing the scattering probability of a subsurface defect (SSD) and statistical distribution functions of SSD radius, refractive index, and position, we derive an extended bidirectional reflectance distribution function (BRDF) from the Jones scattering matrix. This function is applicable to the calculation for comparison with measurement of polarized light-scattering resulting from a SSD. A numerical calculation of the extended BRDF for the case of p-polarized incident light was performed by means of the Monte Carlo method. Our numerical results indicate that the extended BRDF strongly depends on the light incidence angle, the light scattering angle, and the out-of-plane azimuth angle. We observe a 180 degrees symmetry with respect to the azimuth angle. We further investigate the influence of the SSD density, the substrate refractive index, and the statistical distributions of the SSD radius and refractive index on the extended BRDF. For transparent substrates, we also find the dependence of the extended BRDF on the SSD positions. (c) 2006 Optical Society of America.

The effect of diffusion and overhangs/vacancies on the microstructure of zig-zag thin film

Basing on some growth models of thin film, we have investigated the growth mechanism of glancing angle deposition (GLAD) film. The simulation verifies that the overhangs/vacancies also contribute to the columnar growth as well as the self-shadowing effect for GLAD thin film. Besides, we have studied the effect of the deposition rate, surface and bulk diffusions on the microstructure of thin film using the time-dependent Monte Carlo method. The results show that the surface and bulk diffusions can significantly enhance the packing density of thin film in GLAD growth, and the increase of the deposition rate induce the moderate decrease of the packing density. (c) 2006 Elsevier B.V. All rights reserved.

Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Bayesian inference of population expansions in domestic bovines

< p > The past population dynamics of four domestic and one wild species of bovine were estimated using Bayesian skyline plots, a coalescent Markov chain Monte Carlo method that does not require an assumed parametric model of demographic history. Four dom

Robust airfoil design with respect to boundary layer transition

In order to disign an airfoil of which maximum lift coefficient (CL max) is not sensitive to location of forced top boundary layer transition. Taking maximizing mean value of CL max and minimizing standard deviation as biobjective, leading edge radius, manximum thickness and its location, maximum camber and its location as deterministic design variables, location of forced top boundary layer transition as stochastic variable, XFOIL as deterministic CFD solver, non-intrusive polynomial chaos as substitute of Monte Carlo method, we completed a robust airfoil design problem. Results demonstrate performance of initial airfoil is enhanced through reducing standard deviation of CL max. Besides, we also know maximum thickness has the most dominating effect on mean value of CL max, location of maximum thickness has the most dominating effect on standard deviation of CL max, maximum camber has a little effect on both mean value and standard deviation, and maximum camber is the only element of which increase can lead increase of mean value and standard deviation at the same time. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment

In this paper, we consider Bayesian interpolation and parameter estimation in a dynamic sinusoidal model. This model is more flexible than the static sinusoidal model since it enables the amplitudes and phases of the sinusoids to be time-varying. For the dynamic sinusoidal model, we derive a Bayesian inference scheme for the missing observations, hidden states and model parameters of the dynamic model. The inference scheme is based on a Markov chain Monte Carlo method known as Gibbs sampler. We illustrate the performance of the inference scheme to the application of packet-loss concealment of lost audio and speech packets. © EURASIP, 2010.