Effects of Variational Particle Restitution Characteristics on Turbomachinery Erosion

1993 ◽  
Author(s):  
Awatef Hamed ◽  
Timothy P. Kuhn
Keyword(s):  
Gas Turbines ◽  
Laser Doppler Velocimetry ◽  
Particle Trajectory ◽  
Particle Dynamics ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Sampling Techniques ◽  
Flow Conditions ◽  
Mean Values ◽  
Particle Velocities

This paper presents the results of an investigation to determine the effects of variational particle rebounding models on surface impacts and blade erosion patterns in gas turbines. The variance in the particle velocities after the surface impacts are modeled based on the experimental measurements using Laser Doppler Velocimetry (LDV) under varying flow conditions. The probabilistic particle trajectory computations simulate the experimental variance in the particle restitution characteristics using cumulative distribution functions and random sampling techniques. The results are presented for the particle dynamics through a gas turbine flow field and are compared to those obtained with deterministic rebound models based on experimental mean values.

Effects of Variational Particle Restitution Characteristics on Turbomachinery Erosion

1995 ◽  
Vol 117 (3) ◽  
pp. 432-440 ◽  
Author(s):  
A. Hamed ◽  
T. P. Kuhn
Keyword(s):  
Gas Turbines ◽  
Laser Doppler Velocimetry ◽  
Particle Trajectory ◽  
Particle Dynamics ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Sampling Techniques ◽  
Flow Conditions ◽  
Mean Values ◽  
Particle Velocities

This paper presents the results of an investigation to determine the effects of variational particle rebounding models on surface impacts and blade erosion patterns in gas turbines. The variance in the particle velocities after the surface impacts are modeled based on the experimental measurements using Laser-Doppler Velocimetry (LDV) under varying flow conditions. The probabilistic particle trajectory computations simulate the experimental variance in the particle restitution characteristics using cumulative distribution functions and random sampling techniques. The results are presented for the particle dynamics through a gas turbine flow field and are compared to those obtained with deterministic rebound models based on experimental mean values.

An Investigation in the Variance in Particle Surface Interactions and Their Effects in Gas Turbines

1992 ◽  
Vol 114 (2) ◽  
pp. 235-241 ◽  
Author(s):  
A. Hamed
Keyword(s):  
Gas Turbines ◽  
Laser Doppler Velocimetry ◽  
Particle Trajectory ◽  
Particle Surface ◽  
Axial Flow ◽  
Particle Dynamics ◽  
Surface Interactions ◽  
Distribution Functions ◽  
Particle Velocities ◽  
Trajectory Simulations

This work presents the results of a study conducted to investigate particle surface interaction characteristics and their effects on the particle dynamics and blade erosion in axial flow gas turbines. The particle restitution velocities measured experimentally using Laser Doppler Velocimetry in a special tunnel are analyzed using statistical methods. The resulting distribution functions of the rebounding particle velocities after surface impacts are introduced in the particle trajectory simulations through the turbine blade passages, using a methodology that combines particle dynamics computations in a probabilistic model. The presented results for the simulated ash particle dynamics demonstrate the effect of the experimentally measured variance in the particle restitution characteristics on the particle surface impacts, and the associated blade erosion in an axial flow turbine.

An Investigation in the Variance in Particle Surface Interactions and Their Effects in Gas Turbines

1991 ◽  
Author(s):  
A. Hamed ◽  
W. Tabakoff
Keyword(s):  
Gas Turbines ◽  
Laser Doppler Velocimetry ◽  
Particle Trajectory ◽  
Particle Surface ◽  
Axial Flow ◽  
Particle Dynamics ◽  
Surface Interactions ◽  
Distribution Functions ◽  
Particle Velocities ◽  
Trajectory Simulations

This work presents the results of a study conducted to investigate particle surface interaction characteristics and their effects on the particle dynamics and blade erosion in axial flow gas turbines. The particle restitution velocities measured experimentally using Laser Doppler Velocimetry in a special tunnel are analyzed using statistical methods. The resulting distribution functions of the rebounding particle velocities after surface impacts are introduced in the particle trajectory simulations through the turbine blade passages, using a methodology that combines particle dynamics computations in a probabilistic model. The presented results for the simulated ash particle dynamics demonstrate the effect of the experimentally measured variance in the particle restitution characteristics on the particle surface impacts, and the associated blade erosion in an axial flow turbine.

Temperature Effect on Particle Dynamics and Erosion in Radial Inflow Turbine

1988 ◽  
Vol 110 (2) ◽  
pp. 258-264 ◽  
Author(s):  
W. Tabakoff ◽  
A. Hamed
Keyword(s):  
Temperature Effect ◽  
Gas Turbines ◽  
Particle Dynamics ◽  
Flow Conditions ◽  
Inlet Flow ◽  
Cold Flow ◽  
Erosion Rates ◽  
Radial Inflow Turbine ◽  
Turbine Rotors

This paper presents the results of an investigation of the particle dynamics and the resulting blade erosion in radial inflow turbine rotors. In order to determine the influence of the temperature, the computations were performed for cold and hot inlet flow conditions. The results indicate that the trajectories of these small 5-μm ash particles are quite sensitive to the flow temperatures. In addition, gas turbines operating under hot flow are subjected to higher local blade erosion rates compared to cold flow conditions.

Application of Bayesian Forecasting to Change Detection and Prognosis of Gas Turbine Performance

2009 ◽  
Author(s):  
Holger Lipowsky ◽  
Stephan Staudacher ◽  
Michael Bauer ◽  
Klaus-Juergen Schmidt
Keyword(s):  
Change Detection ◽  
Probability Density ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Alternative Model ◽  
Linear Models ◽  
Current Model ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Bayesian Forecasting

This paper presents a novel technique for automatic change detection of the performance of gas turbines. In addition to change detection the proposed technique has the ability to perform a prognosis of measurement values. The proposed technique is deemed to be new in the field of gas turbine monitoring and forms the basic building block of a patent pending filed by the authors [1]. The technique used is called Bayesian Forecasting and is applied to Dynamic Linear Models (DLMs). The idea of Bayesian Forecasting is based on Bayes’ Theorem, which enables the calculation of conditional probabilities. In combination with DLMs (which break down the chronological sequence of the observed parameter into mathematical components like value, gradient, etc.) Bayesian Forecasting can be used to calculate probability density functions prior to the next observation, so called forecast distributions. The change detection is carried out by comparing the current model with an alternative model which mean value is shifted by a prescribed offset. If the forecast distribution of the alternative model better fits the actual observation, a potential change is detected. To determine whether the respective observation is a single outlier or the first observation of a significant change, a special logic is developed. Studies have shown that a confident change detection is possible for a change height of only 1.5 times the standard deviation of the observed signal. In terms of prognostic abilities the proposed technique not only estimates the point of time of a potential limit exceedance of respective parameters, but also calculates confidence bounds as well as probability density and cumulative distribution functions for the prognosis.

scholarly journals Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

2020 ◽  
Vol 501 (1) ◽  
pp. 994-1001
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey ◽  
Snehasish Bhattacharjee
Keyword(s):  
Spatial Distribution ◽  
Mutual Information ◽  
Local Density ◽  
Statistical Significance ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Host Galaxy ◽  
Data Sets ◽  
Data Set ◽  
Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

scholarly journals Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Radiometric Calibration ◽  
Climate Data ◽  
Error Statistics ◽  
Spatiotemporal Resolution

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.

Probabilistic finite element analysis in heat transfer to a nuclear fuel rod bumper support

2004 ◽  
Vol 218 (12) ◽  
pp. 1499-1505
Author(s):  
Rama Subba Reddy Gorla
Keyword(s):  
Heat Transfer ◽  
Finite Element ◽  
Nuclear Fuel ◽  
Cost Effective ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Element Analysis ◽  
Transfer Rates ◽  
Fuel Rod ◽  
Design Variables

Heat transfer from a nuclear fuel rod bumper support was computationally simulated by a finite element method and probabilistically evaluated in view of the several uncertainties in the performance parameters. Cumulative distribution functions and sensitivity factors were computed for overall heat transfer rates due to the thermodynamic random variables. These results can be used to identify quickly the most critical design variables in order to optimize the design and to make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in heat transfer and to the identification of both the most critical measurements and the parameters.

scholarly journals Some new Simpson-type inequalities for generalized p-convex function on fractal sets with applications

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Thabet Abdeljawad ◽  
Saima Rashid ◽  
Zakia Hammouch ◽  
İmdat İşcan ◽  
Yu-Ming Chu
Keyword(s):  
Convex Functions ◽  
Fractional Derivatives ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Auxiliary Result ◽  
Fractal Sets ◽  
Different Types ◽  
Novel Applications ◽  
Class Of Functions ◽  
Harmonically Convex Functions

Abstract The present article addresses the concept of p-convex functions on fractal sets. We are able to prove a novel auxiliary result. In the application aspect, the fidelity of the local fractional is used to establish the generalization of Simpson-type inequalities for the class of functions whose local fractional derivatives in absolute values at certain powers are p-convex. The method we present is an alternative in showing the classical variants associated with generalized p-convex functions. Some parts of our results cover the classical convex functions and classical harmonically convex functions. Some novel applications in random variables, cumulative distribution functions and generalized bivariate means are obtained to ensure the correctness of the present results. The present approach is efficient, reliable, and it can be used as an alternative to establishing new solutions for different types of fractals in computer graphics.

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