Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Control theory & Artificial neural network. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Raman Spectroscopy of Nanocrystalline Ceria and Zirconia Thin Films

Abstract: The results of Raman-scattering studies of nanocrystalline CeO2 and ZrO2:16% Y (YSZ) thin films are presented. The relationship between the lattice disorder and the form of the Raman spectra is discussed and correlated with the microstructure. It is shown that the Raman line shape results from phonon confinement and spatial correlation effects and yields information about the material nonstoichiometry level.

Point-Collocation Nonintrusive Polynomial Chaos Method for Stochastic Computational Fluid Dynamics

Abstract: This paper describes a point-collocation nonintrusive polynomial chaos technique used for uncertainty propagation in computational fluid dynamics simulations. The application of point-collocation nonintrusive polynomial chaos to stochastic computational fluid dynamics is demonstrated with two examples: 1) a stochastic expansion-wave problem with an uncertain deflection angle (geometric uncertainty) and 2) a stochastic transonic-wing case with uncertain freestream Mach number and angle of attack. For each problem, input uncertainties are propagated with both the nonintrusive polynomial chaos method and Monte Carlo techniques to obtain the statistics of various output quantities. Confidence intervals for Monte Carlo statistics are calculated using the bootstrap method. For the expansion-wave problem, a fourth-degree polynomial chaos expansion, which requires five deterministic computational fluid dynamics evaluations, has been sufficient to predict the statistics within the confidence interval of 10,000 crude Monte Carlo simulations. In the transonic-wing case, for various output quantities of interest, it has been shown that a fifth-degree point-collocation nonintrusive polynomial chaos expansion obtained with Hammersley sampling was capable of estimating the statistics at an accuracy level of 1000 Latin hypercube Monte Carlo simulations with a significantly lower computational cost. Overall, the examples demonstrate that the point-collocation nonintrusive polynomial chaos has a promising potential as an effective and computationally efficient uncertainty propagation technique for stochastic computational fluid dynamics simulations.

Emerging trends in M-government

Abstract: Considering the advantages and implications of increased usage of wireless connectivity for governmental information and services.

Time-dependent reliability analysis with joint upcrossing rates

Abstract: In time-dependent reliability analysis, an upcrossing is defined as the event when a limit-state function reaches its failure region from its safe region. Upcrossings are commonly assumed to be independent. The assumption may not be valid for some applications and may result in large errors. In this work, we develop a more accurate method that relaxes the assumption by using joint upcrossing rates. The method extends the existing joint upcrossing rate method to general limit-state functions with both random variables and stochastic processes. The First Order Reliability Method (FORM) is employed to derive the single upcrossing rate and joint upcrossing rate. With both rates, the probability density of the first time to failure can be solved numerically. Then the probability density leads to an easy evaluation of the time-dependent probability of failure. The proposed method is applied to the reliability analysis of a beam and a mechanism, and the results demonstrate a significant improvement in accuracy.