There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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Fundamental Concepts In The Design Of Experiments

On centrifugal pumps

A major issue in surrogate model-based design optimization is the modeling fidelity. An effective approach is to employ multiple surrogates based on the same training data to offer approximations from alternative modeling viewpoints. This approach is employed in a compressor blade shape optimization using the NASA rotor 37 as the case study. The surrogate models considered include polynomial response surface approximation, Kriging, and radial basis neural network. In addition, a weighted average model based on global error measures is constructed. Sequential quadratic programming is used to search the optimal point based on these alternative surrogates. Three design variables characterizing the blade regarding sweep, lean, and skew are selected along with the three-level full factorial approach for design of experiment. The optimization is guided by three objectives aimed at maximizing the adiabatic efficiency, as well as the total pressure and total temperature ratios. The optimized compressor blades yield lower losses by moving the separation line toward the downstream direction. The optima for total pressure and total temperature ratios are similar, but the optimum for adiabatic efficiency is located far from them. It is found that the most accurate surrogate did not always lead to the best design. This demonstrated that using multiple surrogates can improve the robustness of the optimization at a minimal computational cost.

Multiple surrogate modeling for axial compressor blade shape optimization

The paper reviews recent research and development activities in the field of hydropower technology. It covers emerging and advanced technologies to mitigate flow instabilities (active and passive a ...

Analysis of emerging technologies in the hydropower sector

This work was supported by the Industrial Infrastructure Program through the Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government Ministry of Trade, Industry and Energy (Grant No. N0000502).

Improvement of Hydrodynamic Performance of a Multiphase Pump Using Design of Experiment Techniques

High performance ocean energy harvesting turbine design–A new casing treatment scheme

Development of numerical Eulerian-Eulerian models for simulating multiphase pumps

This paper presents the design optimization of a centrifugal compressor impeller with a hybrid multi-objective evolutionary algorithm. Reynolds-averaged Navier—Stokes (RANS) equations are solved with the shear stress transport turbulence model as a turbulence closure model. Flow analysis is performed on a hexahedral grid through a finite-volume solver. Two objectives, viz., the isentropic efficiency and the total pressure ratio (PR), are selected with four design variables that define the impeller hub and shroud contours in meridian terms for optimizing the system. The validation of numerical results was performed through experimental data for the total PR and the isentropic efficiency. Objective-function values are numerically evaluated through the RANS analysis at design points that are selected through the Latin hypercube sampling method. A fast and elitist non-dominated sorting genetic algorithm (NSGA-II) with an e-constraint strategy for local search coupled with a surrogate model is used for...

Multi-objective optimization of a centrifugal compressor impeller through evolutionary algorithms:

Hydrodynamic analysis and an optimization of a vaned diffuser in a mixed-flow pump are performed in this work. Numerical analysis is carried out by solving three-dimensional Reynolds-averaged Navier-Stokes equations using the shear stress transport turbulence model. A validation of numerical results is conducted by comparison with experimental data for the head, power, and efficiency. An optimization process based on a radial basis neural network model is performed with four design variables that define the straight vane length ratio, the diffusion area ratio, the angle at the diffuser vane tip, and the distance ratio between the impeller blade trailing edge and the diffuser vane leading edge. Efficiency as a hydrodynamic performance parameter is selected as the objective function for optimization. The objective function is numerically assessed at design points selected by Latin hypercube sampling in the design space. The optimization yielded a maximum increase in efficiency of 9.75% at the design flow coefficient compared to a reference design. The performance curve for efficiency was also enhanced in the high flow rate region. Detailed internal flow fields between the reference and optimum designs are analyzed and discussed.

Jin-Hyuk Kim

Papers

Improvement of Hydrodynamic Performance of a Multiphase Pump Using Design of Experiment Techniques

High performance ocean energy harvesting turbine design–A new casing treatment scheme

Development of numerical Eulerian-Eulerian models for simulating multiphase pumps

Multi-objective optimization of a centrifugal compressor impeller through evolutionary algorithms:

Analysis and Optimization of a Vaned Diffuser in a Mixed Flow Pump to Improve Hydrodynamic Performance