Empirical Models for Non-Deterministic Simulation-Based Robust Design

2007 ◽  
Author(s):  
Hae-Jin Choi ◽  
Janet K. Allen
Keyword(s):  
Robust Design ◽  
Cell Walls ◽  
Linear Models ◽  
Simulation Models ◽  
Simulation Based ◽  
Alloy Heat ◽  
Mean And Variance ◽  
The Mean ◽  
Uncertainty Analyses ◽  
Computationally Intensive

We propose a method for metamodeling non-deterministic computer intensive simulations for use in robust design. Generalized linear models for mean responses and heteroscadastic response variances are iteratively estimated in an integrated manner. Estimators that may be used for predicting the mean and variance models are introduced and metamodels of variance are developed. The usefulness of this metamodeling approach in efficient uncertainty analyses of non-deterministic, computationally-intensive simulation models for robust design methods is illustrated with the example of the design of a linear cellular alloy heat exchanger with randomly distributed cracks in the cell walls.

scholarly journals SIMULASI WAKTU TUNGGU MAHASISWA DAN DOSEN DI LAYANAN AKADEMIK UNIVERSITAS BUNDA MULIA

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Rudy Santosa Sudirga
Keyword(s):  
Response Time ◽  
Waiting Time ◽  
Operations Management ◽  
Heavy Traffic ◽  
Simulation Models ◽  
Operation Performance ◽  
Service Operation ◽  
Mean And Variance ◽  
The Mean ◽  
Time In Service

<p>The Management of Academic Service continues to be a major challenge for many college, high school and college organizations in providing better services with fewer resources. The allocation of service staffs and response-time in service involve many challenging issues, because the mean and variance of the response-time in service can be increased dramatically with the intensity of heavy traffic. This study discusses how to use simulation models to improve response time in service operation. Performance at the Academic Service as a whole can be considered very good and is still idle due to utilization of Academic Service, which is still equal to an average of 17%, or it can be said that the workload is not too excessive and deemed to be able to serve the students and lecturers. The performance of Academic Sevice University Bunda Mulia can be considered excellent in terms of operations management, as indicated by the average waiting time, which is very short at only 9.10 seconds.<br />Keywords: Queueing System, Waiting Time, and Simulation</p>

Applications of Polynomial Chaos-Based Cokriging to Simulation-Based Analysis and Design Under Uncertainty

2020 ◽  
Author(s):  
Jethro Nagawkar ◽  
Leifur Leifsson
Keyword(s):  
Robust Design ◽  
Ultrasonic Testing ◽  
Polynomial Chaos ◽  
Robust Design Optimization ◽  
High Fidelity ◽  
Analysis And Design ◽  
Simulation Based ◽  
The Mean ◽  
Design Case ◽  
Global Accuracy

Abstract This paper demonstrates the use of the polynomial chaos-based Cokriging (PC-Cokriging) on various simulation-based problems, namely an analytical borehole function, an ultrasonic testing (UT) case and a robust design optimization of an airfoil case. This metamodel is compared to Kriging, polynomial chaos expansion (PCE), polynomial chaos-based Kriging (PC-Kriging) and Cokriging. The PC-Cokriging model is a multi-variate variant of PC-Kriging and its construction is similar to Cokriging. For the borehole function, the PC-Cokriging requires only three high-fidelity samples to accurately capture the global accuracy of the function. For the UT case, it requires 20 points. Sensitivity analysis is performed for the UT case showing that the F-number has negligible effect on the output response. For the robust design case, a 75 and 31 drag count reduction is reported on the mean and standard deviation of the drag coefficient, respectively, when compared to the baseline shape.

Robust Design Through the Use of a Hybrid Genetic Algorithm

2002 ◽  
Author(s):  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Hybrid Genetic Algorithm ◽  
Design Parameters ◽  
Optimization Approach ◽  
Engineering Systems ◽  
Local Optima ◽  
Good Design ◽  
Mean And Variance ◽  
The Mean

In this paper we present a hybrid optimization approach to perform robust design. The motivation for this work is the fact that many realistic engineering systems are mutimodal in nature with multiple local optima, and moreover may have one or more uncertain design parameters. The approach that is presented utilizes both local and global optimization algorithms to find good design points more efficiently than either could alone. The mean and variance of the objective function at a design point is calculated using Monte Carlo simulation and is used to drive the optimization process. To demonstrate the usefulness of this approach a case study is considered involving the design of a beam with dimensional uncertainty.

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.

Designing MEMS Disk Resonator Based Biological Mass Sensors Under Fabrication Uncertainty

2009 ◽  
Author(s):  
Amir Heidari ◽  
Hae-Jin Choi
Keyword(s):  
Optimum Design ◽  
Robust Design ◽  
Simulation Models ◽  
Design Solution ◽  
Disk Resonator ◽  
Disk Diameter ◽  
Mass Sensitivity ◽  
Mass Sensors ◽  
Main Challenge ◽  
The Mean

A radial-contour mode disk resonator has its own advantages, less energy loss and less airflow damping, over existing counterparts such as surface acoustic wave (SAW) resonators and quartz crystal microbalance (QCM) sensors. Taking these advantages of the disk resonators, we design a biological mass sensor in this paper. One of the important challenges in the design of biological mass sensors is inherent uncertainties of MEMS fabrication processes that may strongly affect to the disk resonator performances. Parameters of main effect on the sensor performance (i.e., mass sensitivity, Sm) are identified among many inputs based on response surface method screening process. The shape of the circular disk deviates from a desired perfect circle due to the fabrication uncertainty. Degree of deviation from perfect circularity significantly affects to the disk frequency. In addition, because of the presence of electrodes in sides, the disk rotation angle must be considered as a parameter that can affect the frequency. In this work, the disk resonator is designed to perform robust to the geometric parameter variations. A series of simulation models is developed to obtain natural frequency and mass sensitivity because analytical solutions cannot predict the resonant frequency variation originated such geometric variances. A non-deterministic metamodeling technique is introduced to replace the time consuming simulation models and used for the efficient local sensitivity analysis which is the main challenge of simulation based robust design. The design problem is to find the mean disk diameter in-between 800 μm and 1400μm to achieve robust maximum Sm. A mathematical construct, Error Margin Index (EMI) combining performance mean and deviation, is employed in the solution search algorithm to find a robust optimum design. Our design solution is the mean disk diameter of 1280 μm. The difference of mean mass sensitivity between traditional optimum design and our robust design is about 0.7μm2/ng. The standard deviation of mass sensitivity at optimal design is high (0.68 μm2/ng) and that of our design is low (0.39 μm2/ng).

scholarly journals Performance Analysis of Amplitude Comparison Monopulse Direction-of-Arrival Estimation

2020 ◽  
Vol 10 (4) ◽  
pp. 1246 ◽  
Author(s):  
Do-Jin An ◽  
Joon-Ho Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Taylor Series Expansion ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Simulation Based ◽  
The Mean ◽  
Computationally Intensive

Amplitude-comparison monopulse radar in tracking radar uses the tracking scheme of a monopulse radar to estimate the angle components of a target. The performance of the amplitude comparison monopulse radar under measurement uncertainty is analysed. Measurement noises are modelled as Gaussian random variables. Taylor series expansion is adopted to get analytic expression of the mean square error (MSE). Estimation accuracy, in terms of the MSEs for estimate the direction-of-arrival (DOA) estimation algorithm, is usually obtained from the Monte Carlo simulation, which can be computationally intensive especially for large number of repetitions in the Monte Carlo simulation. To get reliable MSE in the Monte Carlo simulation, the number of repetitions should be very large, which implies that there is a trade-off between reliability of the MSE and computational burden in the Monte Carlo simulation. This paper shows the performance of amplitude comparison monopulse radar by linear approximation of nonlinear equations to estimate the DOA. The performance of amplitude comparison monopulse radar is quantitatively analysed via the MSEs, and the derived expression is validated by comparing the analytic MSEs with the simulation based MSEs. In addition, it is shown in the numerical results that analytically derived MSE is much less computationally intensive in comparison with the Monte Carlo simulation-based MSE, which implies that the proposed scheme in this paper results in drastic reduction in computational complexity for evaluation of the MSE.

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.

Study on Association between Height, Weight, Iodine Supplementation and Thyroid Volume

2021 ◽  
pp. 1-25
Author(s):  
Lanchun Liu ◽  
Lixiang Liu ◽  
Ming Li ◽  
Yang Du ◽  
Peng Liu ◽  
...  
Keyword(s):  
Iodine Deficiency ◽  
Linear Models ◽  
Thyroid Volume ◽  
Salt Iodization ◽  
Iodine Supplementation ◽  
Random Pairing ◽  
Level Data ◽  
The Mean ◽  
Salt Iodine ◽  
The Difference

Abstract The policy of Universal Salt Iodization (USI) could reduce population’s thyroid volume (TVOL) in iodine deficiency areas. Conversely, the improved growth and developmental status of children might increase the TVOL accordingly. Whether the decreased TVOL by USI conceals the increase effect of height and weight on TVOL is unclear. The aim of this study was to analyse the association between height, weight, iodine supplementation and TVOL. Five national Iodine Deficiency Disorder surveys were matched into four pairs according to the purpose of analysis. County-level data of both detected by paired surveys were incorporated, 1: 1 random pairing method was used to match counties or individuals. The difference of TVOL between different height, weight, different iodine supplementation measures groups and the association between TVOL and them were studied. The mean height and weight of children aged 8-10 years increased from 129.9cm and 26.9kg in 2002 to 136.2cm and 32.1kg in 2019; while the median TVOL decreased from 3.10ml to 2.61ml. Iodine supplementation measures can affect TVOL; after exclude iodine effects, the median TVOL was increased with the height and weight. On the other side, after excluding the influence of height and weight, the median TVOL remained decreased. Only age, weight and salt iodine were significant associated with TVOL in multiple linear models. Development of height and weight in children is the evidence of improved nutrition. The decreased TVOL caused by iodized salt measures conceals the increase effect of height and weight on TVOL. Age, weight, and salt iodine affect TVOL significantly.

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.

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