A numerical model for predicting the jump of lift force on an oscillating cylinder

The fluid force coefficients on a transversely oscillating cylinder are calculated by applying two- dimensional large eddy simulation method. Considering the ‘‘jump’’ phenomenon of the amplitude of lift coefficient is harmful to the security of the submarine slender structures, the characteristics of this ‘‘jump’’ are dissertated concretely. By comparing with experiment results, we establish a numerical model for predicting the jump of lift force on an oscillating cylinder, providing consultation for revising the hydrodynamic parameters and checking the fatigue life scale design of submarine slender cylindrical structures.

The Experimental and Numerical Studies on Gas Production from Hydrate Reservoir by Depressurization

A set of experimental system to study hydrate dissociation in porous media is built and some experiments on hydrate dissociation by depressurization are carried out. A mathematical model is developed to simulate the hydrate dissociation by depressurization in hydrate-bearing porous media. The model can be used to analyze the effects of the flow of multiphase fluids, the kinetic process and endothermic process of hydrate dissociation, ice-water phase equilibrium, the variation of permeability, convection and conduction on the hydrate dissociation, and gas and water productions. The numerical results agree well with the experimental results, which validate our mathematical model. For a 3-D hydrate reservoir of Class 3, the evolutions of pressure, temperature, and saturations are elucidated and the effects of some main parameters on gas and water rates are analyzed. Numerical results show that gas can be produced effectively from hydrate reservoir in the first stage of depressurization. Then, methods such as thermal stimulation or inhibitor injection should be considered due to the energy deficiency of formation energy. The numerical results for 3-D hydrate reservoir of Class 1 show that the overlying gas hydrate zone can apparently enhance gas rate and prolong life span of gas reservoir.

Numerical and Experimental Investigation On The Prevention of Co Deflagration

The exhaust gases from industrial furnaces contain a huge amount of heat and chemical enthalpy. However, it is hard to recover this energy since exhaust gases invariably contain combustible components such as carbon monoxide (CC). If the CO is unexpectedly ignited during the heat recovery process, deflagration or even detonation could occur, with serious consequences such as complete destruction of the equipment. In order to safely utilize the heat energy contained in exhaust gas, danger of its explosion must be fully avoided. The mechanism of gas deflagration and its prevention must therefore be studied. In this paper, we describe a numerical and experimental investigation of the deflagration process in a semi-opened tube. The results show that, upon ignition, a low-pressure wave initially spreads within the tube and then deflagration begins. For the purpose of preventing deflagration, an appropriate amount of nitrogen was injected into the tube at a fixed position. Both simulation and experimental results have shown that the injection of inert gas can successfully interrupt the deflagration process. The peak value of the deflagration pressure can thereby be reduced by around 50%. (C) 2008 Elsevier Ltd. All rights reserved.

Numerical methods for ill-posed, linear problems

A means of assessing the effectiveness of methods used in the numerical solution of various linear ill-posed problems is outlined. Two methods: Tikhonov' s method of regularization and the quasireversibility method of Lattès and Lions are appraised from this point of view.

In the former method, Tikhonov provides a useful means for incorporating a constraint into numerical algorithms. The analysis suggests that the approach can be generalized to embody constraints other than those employed by Tikhonov. This is effected and the general "T-method" is the result.

A T-method is used on an extended version of the backwards heat equation with spatially variable coefficients. Numerical computations based upon it are performed.

The statistical method developed by Franklin is shown to have an interpretation as a T-method. This interpretation, although somewhat loose, does explain some empirical convergence properties which are difficult to pin down via a purely statistical argument.

Numerical solution of parabolic equations by the box scheme

The box scheme proposed by H. B. Keller is a numerical method for solving parabolic partial differential equations. We give a convergence proof of this scheme for the heat equation, for a linear parabolic system, and for a class of nonlinear parabolic equations. Von Neumann stability is shown to hold for the box scheme combined with the method of fractional steps to solve the two-dimensional heat equation. Computations were performed on Burgers' equation with three different initial conditions, and Richardson extrapolation is shown to be effective.

Topics in randomized numerical linear algebra

This thesis studies three classes of randomized numerical linear algebra algorithms, namely: (i) randomized matrix sparsification algorithms, (ii) low-rank approximation algorithms that use randomized unitary transformations, and (iii) low-rank approximation algorithms for positive-semidefinite (PSD) matrices.

Randomized matrix sparsification algorithms set randomly chosen entries of the input matrix to zero. When the approximant is substituted for the original matrix in computations, its sparsity allows one to employ faster sparsity-exploiting algorithms. This thesis contributes bounds on the approximation error of nonuniform randomized sparsification schemes, measured in the spectral norm and two NP-hard norms that are of interest in computational graph theory and subset selection applications.

Low-rank approximations based on randomized unitary transformations have several desirable properties: they have low communication costs, are amenable to parallel implementation, and exploit the existence of fast transform algorithms. This thesis investigates the tradeoff between the accuracy and cost of generating such approximations. State-of-the-art spectral and Frobenius-norm error bounds are provided.

The last class of algorithms considered are SPSD "sketching" algorithms. Such sketches can be computed faster than approximations based on projecting onto mixtures of the columns of the matrix. The performance of several such sketching schemes is empirically evaluated using a suite of canonical matrices drawn from machine learning and data analysis applications, and a framework is developed for establishing theoretical error bounds.

In addition to studying these algorithms, this thesis extends the Matrix Laplace Transform framework to derive Chernoff and Bernstein inequalities that apply to all the eigenvalues of certain classes of random matrices. These inequalities are used to investigate the behavior of the singular values of a matrix under random sampling, and to derive convergence rates for each individual eigenvalue of a sample covariance matrix.