Kok-Kwang Phoon

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The possibility of making short-term prediction of rainfall is studied by investigating the existence of chaotic behavior in the rainfall data series. The minimum number of variables essential and the number of variables sufficient to model the dynamics of the rainfall process are identified. The behavior of rainfall over different record lengths is(More)
SUMMARY A random process can be represented as a series expansion involving a complete set of deterministic functions with corresponding random coeecients. Karhunen–Loeve (K–L) series expansion is based on the eigen-decomposition of the covariance function. Its applicability as a simulation tool for both stationary and non-stationary Gaussian random(More)
The non-Gaussian Karhunen–Loeve (K–L) expansion is very attractive because it can be extended readily to non-stationary and multi-dimensional fields in a unified way. However, for strongly non-Gaussian processes, the original procedure is unable to match the distribution tails well. This paper proposes an effective solution to this tail mismatch problem(More)
The feasibility of implementing Karhunen – Loeve (K– L) expansion as a practical simulation tool hinges crucially on the ability to compute a large number of K – L terms accurately and cheaply. This study presents a simple wavelet-Galerkin approach to solve the Fredholm integral equation for K – L simulation. The proposed method has significant(More)
SUMMARY This paper examines the performance of the Jacobi preconditioner when used with two Krylov subspace iterative methods. The number of iterations needed for convergence was shown to be different for drained, undrained and consolidation problems, even for similar condition number. The differences were due to differences in the eigenvalue distribution,(More)
A copula-based method is presented to investigate the impact of copulas for modeling bivariate distributions on system reliability under incomplete probability information. First, the copula theory for modeling bivariate distributions as well as the tail dependence of copulas are briefly introduced. Then, a general parallel system reliability problem is(More)
The series representation consisting of eigenfunctions as the orthogonal basis is called the Karhunen–Loeve expansion. This paper demonstrates that the determination of eigensolutions using a wavelet-Galerkin scheme for Karhunen–Loeve expansion is computationally equivalent to using wavelet directly for stochastic expansion and simulating the correlated(More)
This paper aims to propose a bootstrap method for characterizing the uncertainty in proba-bilistic models and its effect on geotechnical reliability. First, the copula theory is briefly introduced. Second, both the uncertainties in parameters and type of the best-fit marginal distributions and copulas are characterized by the bootstrap method. Finally, four(More)
This paper aims to propose a bootstrap method for characterizing the effect of uncertainty in shear strength parameters on slope reliability. The procedure for a traditional slope reliability analysis with fixed distributions of shear strength parameters is presented first. Then, the variations of the mean and standard deviation of shear strength parameters(More)