scholarly journals Robust Design of Compressor Fan Blades Against Erosion

2006 ◽  
Vol 128 (4) ◽  
pp. 864-873 ◽  
Author(s):  
Apurva Kumar ◽  
Andy J. Keane ◽  
Prasanth B. Nair ◽  
Shahrokh Shahpar
Keyword(s):  
Mean Shift ◽  
Optimal Solution ◽  
Compressor Blades ◽  
Geometry Modeling ◽  
Numerical Studies ◽  
Blade Section ◽  
Mean And Variance ◽  
The Mean ◽  
Computational Budget ◽  
Fan Blade

This paper is concerned with robust aerodynamic design of compressor blades against erosion. The proposed approach combines a multiobjective genetic algorithm with geometry modeling methods, high-fidelity computational fluid dynamics, and surrogate models to arrive at robust designs on a limited computational budget. The multiobjective formulation used here allows explicit trade-off between the mean and variance of the performance to be carried out. Detailed numerical studies are presented for robust geometric design of a typical compressor fan blade section to illustrate the proposed methodology. The performance of a selected robust optimal solution on the Pareto front is compared to a deterministic optimal solution to demonstrate that significant improvements in the mean shift and variance can be achieved.

scholarly journals Probabilistic Performance Analysis of Eroded Compressor Blades

2005 ◽  
Author(s):  
A. Kumar ◽  
P. B. Nair ◽  
A. J. Keane ◽  
S. Shahpar
Keyword(s):  
Probabilistic Analysis ◽  
Surrogate Model ◽  
Uncertainty Propagation ◽  
Navier Stokes ◽  
Cfd Simulations ◽  
Compressor Blades ◽  
Geometry Modeling ◽  
Blade Section ◽  
Computational Fluid Dynamics Cfd ◽  
Fan Blade

This paper presents a probabilistic analysis of the effect of erosion on the performance of compressor fan blades. A realistic parametric CAD model is developed to represent eroded blades. Design of Experiments (DOE) techniques are employed to generate a set of candidate points, which are combined with a parametric geometry modeling and grid generation routine to produce a hybrid mesh. A multigrid Reynolds-Averaged Navier Stokes (RANS) solver HYDRA with Spalart Allmaras turbulence model is used for Computational Fluid Dynamics (CFD) simulations. The data generated is used to create a surrogate model for efficient uncertainty propagation. This method is applied to a typical Rolls Royce compressor fan blade section. Monte Carlo Simulation, using the surrogate model, is executed for the probabilistic analysis of the compressor fan blade. Results show upto 5% increase in pressure loss for the eroded compressor fan blades.

scholarly journals Robust Design of Compressor Blades Against Manufacturing Variations

2006 ◽  
Author(s):  
Apurva Kumar ◽  
A. J. Keane ◽  
P. B. Nair ◽  
S. Shahpar
Keyword(s):  
Robust Design ◽  
Process Model ◽  
Design Space ◽  
Computational Effort ◽  
Gaussian Stochastic Process ◽  
Compressor Blades ◽  
Bayesian Monte Carlo ◽  
Mean And Variance ◽  
The Mean ◽  
Gaussian Stochastic Process Model

The aim of this paper is to develop and illustrate an efficient methodology to design blades with robust aerodynamic performance in the presence of manufacturing uncertainties. A novel geometry parametrization technique is developed to represent manufacturing variations due to tolerancing. A Gaussian Stochastic Process Model is trained using DOE techniques in conjunction with a high fidelity CFD solver. Bayesian Monte Carlo Simulation is then employed to obtain the statistics of the performance at each design point. A multiobjective optimizer is used to search the design space for robust designs. The multiobjective formulation allows explicit trade-off between the mean and variance of the performance. A design, selected from the robust design set is compared with a deterministic optimal design. The results demonstrate an effective method to obtain compressor blade designs which have reduced sensitivity to manufacturing variations with significant savings in computational effort.

Efficient Genetic Algoritm Based Robust Design Method for Compressor Fan Blades

2005 ◽  
Author(s):  
Apurva Kumar ◽  
A. J. Keane ◽  
P. B. Nair ◽  
S. Shahpar
Keyword(s):  
Genetic Algorithm ◽  
Robust Design ◽  
Design Method ◽  
Navier Stokes ◽  
Gaussian Stochastic Process ◽  
Nsga Ii ◽  
Pressure Losses ◽  
Geometry Modeling ◽  
Mean And Variance ◽  
Fan Blade

This paper presents an efficient genetic algorithm based methodology for robust design that produces compressor fan blades tolerant against erosion. A novel geometry modeling method is employed to create eroded compressor fan blade sections. A multigrid Reynolds-Averaged Navier Stokes (RANS) solver HYDRA with Spalart Allmaras turbulence model is used for CFD simulations to calculate the pressure losses. This is used in conjunction with Design of Experiment techniques to create Gaussian stochastic process surrogate models to predict the mean and variance of the performance. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed for the multiobjective optimization to find the global Pareto-optimal front. This enables the designer to trade off between mean and variance of performance to propose robust designs.

scholarly journals Weighted statistical binary patterns for facial feature representation

2021 ◽  
Author(s):  
Hung Phuoc Truong ◽  
Thanh Phuong Nguyen ◽  
Yong-Guk Kim
Keyword(s):  
Comprehensive Evaluation ◽  
Facial Feature ◽  
Input Image ◽  
Feature Representation ◽  
Illumination Variation ◽  
Straight Line ◽  
Mean And Variance ◽  
The Mean ◽  
Face Datasets ◽  
Degraded Images

AbstractWe present a novel framework for efficient and robust facial feature representation based upon Local Binary Pattern (LBP), called Weighted Statistical Binary Pattern, wherein the descriptors utilize the straight-line topology along with different directions. The input image is initially divided into mean and variance moments. A new variance moment, which contains distinctive facial features, is prepared by extracting root k-th. Then, when Sign and Magnitude components along four different directions using the mean moment are constructed, a weighting approach according to the new variance is applied to each component. Finally, the weighted histograms of Sign and Magnitude components are concatenated to build a novel histogram of Complementary LBP along with different directions. A comprehensive evaluation using six public face datasets suggests that the present framework outperforms the state-of-the-art methods and achieves 98.51% for ORL, 98.72% for YALE, 98.83% for Caltech, 99.52% for AR, 94.78% for FERET, and 99.07% for KDEF in terms of accuracy, respectively. The influence of color spaces and the issue of degraded images are also analyzed with our descriptors. Such a result with theoretical underpinning confirms that our descriptors are robust against noise, illumination variation, diverse facial expressions, and head poses.

scholarly journals Groups and Individuals: Optical Flow Patterns of Broiler Chicken Flocks Are Correlated with the Behavior of Individual Birds

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 568
Author(s):  
Sabine G. Gebhardt-Henrich ◽  
Ariane Stratmann ◽  
Marian Stamp Dawkins
Keyword(s):  
Optical Flow ◽  
Broiler Chicken ◽  
Average Length ◽  
Flow Patterns ◽  
Group Level ◽  
Positive Correlation ◽  
Water Test ◽  
Mean And Variance ◽  
The Mean

Group level measures of welfare flocks have been criticized on the grounds that they give only average measures and overlook the welfare of individual animals. However, we here show that the group-level optical flow patterns made by broiler flocks can be used to deliver information not just about the flock averages but also about the proportion of individuals in different movement categories. Mean optical flow provides information about the average movement of the whole flock while the variance, skew and kurtosis quantify the variation between individuals. We correlated flock optical flow patterns with the behavior and welfare of a sample of 16 birds per flock in two runway tests and a water (latency-to-lie) test. In the runway tests, there was a positive correlation between the average time taken to complete the runway and the skew and kurtosis of optical flow on day 28 of flock life (on average slow individuals came from flocks with a high skew and kurtosis). In the water test, there was a positive correlation between the average length of time the birds remained standing and the mean and variance of flock optical flow (on average, the most mobile individuals came from flocks with the highest mean). Patterns at the flock level thus contain valuable information about the activity of different proportions of the individuals within a flock.

Robust Compressor Blades for Desensitizing Operational Tip Clearance Variations

2014 ◽  
Author(s):  
Pranay Seshadri ◽  
Shahrokh Shahpar ◽  
Geoffrey T. Parks
Keyword(s):  
Robust Design ◽  
Total Pressure ◽  
Pressure Rise ◽  
Side Surface ◽  
Tip Clearance ◽  
Design Parameters ◽  
Compressor Blades ◽  
Robust Designs ◽  
Multi Objective ◽  
Mean And Variance

Robust design is a multi-objective optimization framework for obtaining designs that perform favorably under uncertainty. In this paper robust design is used to redesign a highly loaded, transonic rotor blade with a desensitized tip clearance. The tip gap is initially assumed to be uncertain from 0.5 to 0.85% span, and characterized by a beta distribution. This uncertainty is then fed to a multi-objective optimizer and iterated upon. For each iteration of the optimizer, 3D-RANS computations for two different tip gaps are carried out. Once the simulations are complete, stochastic collocation is used to generate mean and variance in efficiency values, which form the two optimization objectives. Two such robust design studies are carried out: one using 3D blade engineering design parameters (axial sweep, tangential lean, re-cambering and skew) and the other utilizing suction and pressure side surface perturbations (with bumps). A design is selected from each Pareto front. These designs are robust: they exhibit a greater mean efficiency and lower variance in efficiency compared to the datum blade. Both robust designs were also observed to have significantly higher aft and reduced fore tip loading. This resulted in a weaker clearance vortex, wall jet and double leakage flow, all of which lead to reduced mixed-out losses. Interestingly, the robust designs did not show an increase in total pressure at the tip. It is believed that this is due to a trade-off between fore-loading the tip and obtaining a favorable total pressure rise and higher mixed-out losses, or aft-loading the tip, obtaining a lower pressure rise and lower mixed-out losses.

scholarly journals A New Model for the Stochastic Point Reactor: Development and Comparison with Available Models

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 955
Author(s):  
Alamir Elsayed ◽  
Mohamed El-Beltagy ◽  
Amnah Al-Juhani ◽  
Shorooq Al-Qahtani
Keyword(s):  
Kinetic Model ◽  
Differential Equations ◽  
Test Cases ◽  
System Of Differential Equations ◽  
Reactor Model ◽  
Time System ◽  
New Model ◽  
Reactor Dynamics ◽  
Mean And Variance ◽  
The Mean

The point kinetic model is a system of differential equations that enables analysis of reactor dynamics without the need to solve coupled space-time system of partial differential equations (PDEs). The random variations, especially during the startup and shutdown, may become severe and hence should be accounted for in the reactor model. There are two well-known stochastic models for the point reactor that can be used to estimate the mean and variance of the neutron and precursor populations. In this paper, we reintroduce a new stochastic model for the point reactor, which we named the Langevin point kinetic model (LPK). The new LPK model combines the advantages, accuracy, and efficiency of the available models. The derivation of the LPK model is outlined in detail, and many test cases are analyzed to investigate the new model compared with the results in the literature.

A model for random instantaneous growth on an interval

1991 ◽  
Vol 28 (3) ◽  
pp. 529-538
Author(s):  
M. P. Quine
Keyword(s):  
Asymptotic Normality ◽  
Instantaneous Growth ◽  
Mean And Variance ◽  
The Mean

Points arrive in succession on an interval and immediately ‘cover' a region of length ½ to each side (less if they are close to the boundary or to a covered part). The location of a new point is uniformly distributed on the uncovered parts. We study the mean and variance of the total number of points ever formed, in particular as a → 0, in which case we also establish asymptotic normality.

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