Application of generic algorithms in aerodynamic optimisation design procedures

2004 ◽  
Vol 108 (1090) ◽  
pp. 611-620 ◽  
Author(s):  
R. P. Clayton ◽  
R. F. Martinez-Botas
Keyword(s):  
Experimental Data ◽  
Gradient Method ◽  
Pressure Coefficient ◽  
Performance Measure ◽  
Direct Search ◽  
Generic Algorithm ◽  
Design Variables ◽  
Fixed Area ◽  
Truncated Newton ◽  
Search Approach

AbstractDirect optimisation techniques using different methods are presented and compared for the solution of two common flows: a two dimensional diffuser and a drag minimisation problem of a fixed area body. The methods studied are a truncated Newton algorithm (gradient method), a simplex approach (direct search method) and a genetic algorithm (stochastic method). The diffuser problem has a known solution supported by experimental data, it has one design performance measure (the pressure coefficient) and two design variables. The fixed area body also has one performance measure (the drag coefficient), but this time there are four design variables; no experimental data is available, this computation is performed to assess the speed/progression of solution.In all cases the direct search approach (simplex method) required significantly smaller number of evaluations than the generic algorithm method. The simplest approach, the gradient method (Newton) performed equally to the simplex approach for the diffuser problem but it was unable to provide a solution to the four-variable problem of a fixed area body drag minimisation. The level of robustness obtained by the use of generic algorithm is in principle superior to the other methods, but a large price in terms of evaluations has to be paid.

Influence of Perceived Job Enrichment and Goal Characteristics on Employees' Satisfaction, Motivation, and Performance

1984 ◽  
Vol 54 (1) ◽  
pp. 131-137 ◽  
Author(s):  
Léandre J. Maillet
Keyword(s):  
Work Performance ◽  
Work Motivation ◽  
Work Satisfaction ◽  
Performance Measure ◽  
Job Descriptive Index ◽  
Design Variables ◽  
Job Enrichment ◽  
And Performance ◽  
The Relationship ◽  
Goal Characteristics

This article describes (a) the relationship of goal setting and job enrichment with work satisfaction, intrinsic work motivation and performance, (b) the importance of growth need strength as a moderating variable, and (c) the evidence for a curvilinear association between job design variables and outcome measures. 117 penitentiary guards received the Job Diagnostic Survey of Hackman and Oldham, the Job Descriptive Index of Smith, et al., Steers' questionnaire on goal characteristics and a performance measure. Hierarchical multiple regression analyses showed that the specificity of goal and job enrichment were equally effective in the prediction of satisfaction and motivation, while difficulty of goals appears to be the best single predictor of work performance. Growth need strength moderated the relationship between difficulty of goals and work satisfaction. The curvilinear effect was nonsignificant.

A Pareto-Based Genetic Algorithm Search Approach to Handle Damped Natural Frequency Constraints in Turbo Generator Rotor System Design

2004 ◽  
Vol 126 (3) ◽  
pp. 619-625 ◽  
Author(s):  
Anders Angantyr ◽  
Jan Olov Aidanpa¨a¨
Keyword(s):  
Genetic Algorithm ◽  
Natural Frequencies ◽  
Design Criterion ◽  
Rotor System ◽  
Design Tool ◽  
Generator Rotor ◽  
System A ◽  
Turbo Generator ◽  
Design Variables ◽  
Search Approach

The detailed design of a turbo generator rotor system is highly constrained by feasible regions for the damped natural frequencies of the system. A major problem for the designer is to find a solution that fulfills the design criterion for the damped natural frequencies. The bearings and some geometrical variables of the rotor are used as the primary design variables in order to achieve a feasible design. This paper presents an alternative approach to search for feasible designs. The design problem is formulated as an optimization problem and a genetic algorithm (GA) is used to search for feasible designs. Then, the problem is extended to include another objective (i.e., multiobjective optimization) to show the potential of using the optimization formulation and a Pareto-based GA in this rotordynamic application. The results show that the presented approach is promising as an engineering design tool.

Confidence-Based Design Optimization Under Data Uncertainty Using Most Probable Point-Based Approach

2019 ◽  
Author(s):  
Yongsu Jung ◽  
Hyunkyoo Cho ◽  
Ikjin Lee
Keyword(s):  
Statistical Model ◽  
Design Optimization ◽  
Performance Measure ◽  
Cumulative Distribution ◽  
Data Uncertainty ◽  
Normal Space ◽  
Most Probable Point ◽  
Input Distribution ◽  
Design Variables ◽  
Distribution Parameters

Abstract An accurate input statistical model has been assumed in most of reliability-based design optimization (RBDO) to concentrate on variability of random variables. However, only limited number of data are available to quantify the input statistical model in practical engineering applications. In other words, irreducible variability and reducible uncertainty due to lack of knowledge exist simultaneously in random design variables. Therefore, the uncertainty in reliability induced by insufficient data has to be accounted for RBDO to guarantee confidence of reliability. The uncertainty of input distributions is successfully propagated to a cumulative distribution function (CDF) of reliability under normality assumptions, but it requires a number of function evaluations in double-loop Monte Carlo simulation (MCS). To tackle this challenge, reliability measure approach (RMA) in confidence-based design optimization (CBDO) is proposed to handle the randomness of reliability following the idea of performance measure approach (PMA) in RBDO. Input distribution parameters are transformed to the standard normal space for most probable point (MPP) search with respect to reliability. Therefore, the reliability is approximated at MPP with respect to input distribution parameters. The proposed CBDO can treat confidence constraints employing the reliability value at the target confidence level that is approximated by MPP in P-space. In conclusion, the proposed method can significantly reduce the number of function evaluations by eliminating outer-loop MCS while maintaining acceptable accuracy.

Data centric nanocomposites design via mixed-variable Bayesian optimization

2020 ◽  
Vol 5 (8) ◽  
pp. 1376-1390
Author(s):  
Akshay Iyer ◽  
Yichi Zhang ◽  
Aditya Prasad ◽  
Praveen Gupta ◽  
Siyu Tao ◽  
...  
Keyword(s):  
Experimental Data ◽  
Computational Methods ◽  
Bayesian Optimization ◽  
Qualitative Design ◽  
Design Variables ◽  
Mixed Variable

Integrating experimental data with computational methods enables multicriteria design of nanocomposites using quantitative and qualitative design variables.

Effect of Turbulent Intensity and Axial Gap on Turbine Heat Transfer Using Steady and Harmonic Models

2013 ◽  
Author(s):  
Sridhar Murari ◽  
Sunnam Sathish ◽  
Ramakumar Bommisetty ◽  
Jong S. Liu
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Flow Field ◽  
Turbulence Intensity ◽  
Pressure Coefficient ◽  
Heat Transfer Characteristics ◽  
Complex Flow ◽  
Transfer Characteristics ◽  
Flow And Heat Transfer ◽  
Heat Loads

The knowledge of heat loads on the turbine is of great interest to turbine designers. Turbulence intensity and stator-rotor axial gap plays a key role in affecting the heat loads. Flow field and associated heat transfer characteristics in turbines are complex and unsteady. Computational fluid dynamics (CFD) has emerged as a powerful tool for analyzing these complex flow systems. Honeywell has been exploring the use of CFD tools for analysis of flow and heat transfer characteristics of various gas turbine components. The current study has two objectives. The first objective aims at development of CFD methodology by validation. The commercially available CFD code Fine/Turbo is used to validate the predicted results against the benchmark experimental data. Predicted results of pressure coefficient and Stanton number distributions are compared with available experimental data of Dring et al. [1]. The second objective is to investigate the influence of turbulence (0.5% and 10% Tu) and axial gaps (15% and 65% of axial chord) on flow and heat transfer characteristics. Simulations are carried out using both steady state and harmonic models. Turbulence intensity has shown a strong influence on turbine blade heat transfer near the stagnation region, transition and when the turbulent boundary layer is presented. Results show that a mixing plane is not able to capture the flow unsteady features for a small axial gap. Relatively close agreement is obtained with the harmonic model in these situations. Contours of pressure and temperature on the blade surface are presented to understand the behavior of the flow field across the interface.

Reliable and Accurate Prediction of Three-Dimensional Separation in Asymmetric Diffusers Using Large-Eddy Simulation

2009 ◽  
Author(s):  
Hayder Schneider ◽  
Dominic von Terzi ◽  
Hans-Jo¨rg Bauer ◽  
Wolfgang Rodi
Keyword(s):  
Experimental Data ◽  
Reverse Flow ◽  
Separation Bubble ◽  
Pressure Coefficient ◽  
Three Dimensional ◽  
Large Eddy Simulations ◽  
Navier Stokes ◽  
Eddy Simulation ◽  
Large Eddy ◽  
The Impact

Reynolds-Averaged Navier-Stokes (RANS) calculations and Large-Eddy Simulations (LES) of the flow in two asymmetric three-dimensional diffusers were performed. The numerical setup was chosen to be in compliance with previous experiments. The aim of the present study is to find the least expensive method to compute reliably and accurately the impact of geometric sensitivity on the flow. RANS calculations fail to predict both the extent and location of the three-dimensional separation bubble. In contrast, LES is able to determine the amount of reverse flow and the pressure coefficient within the accuracy of experimental data.

scholarly journals Euler Solutions for Transonic Oscillating Cascade Flows Using Dynamic Triangular Meshes

1993 ◽  
Author(s):  
C. J. Hwang ◽  
S. Y. Yang
Keyword(s):  
Experimental Data ◽  
Phase Angle ◽  
Transonic Flow ◽  
Lift Coefficient ◽  
Pressure Coefficient ◽  
Oscillation Amplitude ◽  
Time History ◽  
Present Approach ◽  
Instantaneous Pressure ◽  
Interblade Phase Angle

The modified total-variation-diminishing scheme and an improved dynamic triangular mesh algorithm are presented to investigate the transonic oscillating cascade flows. In a Cartesian coordinate system, the unsteady Euler equations are solved. To validate the accuracy of the present approach, transonic flow around single NACA 0012 airfoil pitching harmonically about the quarter chord is computed first. The calculated instantaneous pressure coefficient distributions during a cycle of motion compare well with the related numerical and experimental data. To further evaluate the present approach involving nonzero interblade phase angle, the calculations of transonic flow around oscillating cascade of two unstaggered NACA 0006 blades with interblade phase angle equal to 180 deg are performed. From the instantaneous pressure coefficient distributions and time history of lift coefficient, the present approach, where a simple spatial treatment is utilized on the periodic boundaries, gives satisfactory results. By using the above solution procedure, transonic flows around oscillating cascade of four biconvex blades with different oscillation amplitudes, reduced frequencies and interblade phase angles are investigated. From the distributions of magnitude and phase angle of the dynamic pressure difference coefficient, the present numerical results show better agreement with the experimental data than those from the linearized theory in most of the cases. For every quarter of one cycle, the pressure contours repeat and proceed one pitch distance in the upward or downward direction for interblade phase angle equal to −90 deg or 90 deg, respectively. The unsteady pressure wave and shock behaviors are observed. From the lift coefficient distributions, it is further confirmed that the oscillation amplitude, interblade phase angle and reduced frequency all have significant effects on the transonic oscillating cascade flows.

Near-Bed Flow Mechanisms Around a Circular Marine Pipeline Close to a Flat Seabed in the Subcritical Flow Regime Using a k-ɛ Model

2011 ◽  
Vol 134 (2) ◽  
Author(s):  
Muk Chen Ong ◽  
Torbjørn Utnes ◽  
Lars Erik ◽  
Dag Myrhaug ◽  
Bjørnar Pettersen
Keyword(s):  
Experimental Data ◽  
Boundary Layer ◽  
Flow Regime ◽  
Boundary Layer Thickness ◽  
Friction Velocity ◽  
Lift Coefficient ◽  
Pressure Coefficient ◽  
Mean Pressure ◽  
Flow Mechanisms ◽  
The Mean

Flow mechanisms around a two-dimensional (2D) circular marine pipeline close to a flat seabed have been investigated using the 2D unsteady Reynolds-averaged Navier–Stokes (URANS) equations with a standard high Reynolds number k-ɛ model. The Reynolds number (based on the free stream velocity and cylinder diameter) ranges from 1 × 104 to 4.8 × 104 in the subcritical flow regime. The objective of the present study is to show a thorough documentation of the applicability of the k-ɛ model for engineering design within this flow regime by means of a careful comparison with available experimental data. The inflow boundary layer thickness and the Reynolds numbers in the present simulations are set according to published experimental data, with which the simulations are compared. Detailed comparisons with the experimental data for small gap ratios are provided and discussed. The effects of the gap to diameter ratio and the inflow boundary layer thickness have been studied. Although under-predictions of the essential hydrodynamic quantities (e.g., time-averaged drag coefficient, time-averaged lift coefficient, root-mean-square fluctuating lift coefficient, and mean pressure coefficient at the back of the pipeline) are observed due to the limitation of the turbulence model, the present approach is capable of providing good qualitative agreement with the published experimental data. The vortex shedding mechanisms have been investigated, and satisfactory predictions are obtained. The mean pressure coefficient and the mean friction velocity along the flat seabed are predicted reasonably well as compared with published experimental and numerical results. The mean seabed friction velocity at the gap is much larger for small gaps than for large gaps; thus, the bedload sediment transport is much larger for small gaps than for large gaps.

Experimental and CFD Evaluation of a Bubble Column Reactor

2010 ◽  
Author(s):  
Sean M. McGuffie ◽  
Mike A. Porter ◽  
Dennis H. Martens
Keyword(s):  
Experimental Data ◽  
Bubble Column ◽  
Scale Up ◽  
Bubble Column Reactor ◽  
Column Reactor ◽  
Cfd Models ◽  
Design Variables ◽  
Input Parameters ◽  
Multi Phase Flow ◽  
Multi Phase

During the scale-up design of a slurry bubble column reactor from a pilot demonstration facility to a production reactor, the design team used computational fluid dynamics (CFD) as a tool to quantify design variables, such as gas holdup and liquid velocities/structural pressures within the reactor. At the time of the analysis, all available physics models for modeling the multi-phase flow had significant limitations that would require “tuning” of the CFD input parameters to ensure confidence in the results. The authors initially conducted a literature search to find data that could be used to calibrate the model. While a wide variety of literature is available, none provided the exact data required for model calibration. For this reason, the authors constructed a test column and performed experiments to derive data for tuning the CFD models. Statistical analysis of the experimental data provided distributions on the input parameters of interest. CFD studies were then used to tune the CFD input parameters to match the experimental data. A correlation was developed, tested and verified. This correlation was then used to provide confidence in the results of the design analysis performed on the scaled up reactor.

Optimization of Jacket Type Offshore-Tower Under Uncertainties

2009 ◽  
Author(s):  
V. Togan ◽  
H. Karadeniz ◽  
A. T. Daloglu
Keyword(s):  
Performance Measure ◽  
Environmental Data ◽  
Probabilistic Constraints ◽  
Reliability Based Design Optimization ◽  
Performance Measure Approach ◽  
Reliability Based Design ◽  
Economical Design ◽  
Design Variables ◽  
Index Approach ◽  
And Performance

In this work, economical design implementation of a jacket tower, which is subjected to some uncertainties associated with the loads, the material properties, and environmental data etc., is presented. In order to fulfill the defined task, reliability based design optimization (RBDO) concept combining the reliability analysis and optimization is performed with reliability constraints including stress, buckling, and the lowest natural frequency. The probabilistic constraints are evaluated by using Reliability Index Approach (RIA) and Performance Measure approach (PMA). The mass of the tower is considered as being the objective function; the thickness and diameter of the cross-section of the jacket members are taken as being design variables of the optimization.

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