HDD Slider Air Bearing Design Optimization Using a Surrogate Model

World Tribology Congress III, Volume 1 ◽

10.1115/wtc2005-64163 ◽

2005 ◽

Author(s):

Naozumi Tsuda ◽

David B. Bogy

Keyword(s):

Convergence Rate ◽

Cost Function ◽

Surrogate Model ◽

Search Space ◽

Kriging Model ◽

Flying Height ◽

Direct Algorithm ◽

Air Bearing ◽

High Convergence Rate ◽

Sampling Points

This report addresses a new optimization method in which the DIRECT algorithm is used in conjunction with a surrogate model. The DIRECT algorithm itself can find the global optimum with a high convergence rate. However the convergence rate can be much improved by coupling DIRECT with a surrogate model. The surrogate model known as the Kriging model is used in this research. It is determined by using sampling points generated by the DIRECT algorithm. This model expresses the shape of a hyper surface approximation of the cost function over the entire search space. Finding the optimum point on this hyper surface is very fast because it is not necessary to solve the time consuming air bearing equations. By using this optimum candidate as one of the DIRECT sampling points, we can eliminate many cost function evaluations. To illustrate the power of this approach we first present some simple optimization examples using known difficult functions. Then we determine the optimum design of a slider with 5nm flying height (FH) starting with a design that has a 7nm FH.

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A Kriging-Assisted Multi-Objective Constrained Global Optimization Method for Expensive Black-Box Functions

Mathematics ◽

10.3390/math9020149 ◽

2021 ◽

Vol 9 (2) ◽

pp. 149

Author(s):

Yaohui Li ◽

Jingfang Shen ◽

Ziliang Cai ◽

Yizhong Wu ◽

Shuting Wang

Keyword(s):

Global Optimization ◽

Pareto Frontier ◽

Kriging Model ◽

Optimization Method ◽

Function Evaluation ◽

Sampling Point ◽

Constrained Global Optimization ◽

Multi Objective ◽

Sample Data ◽

Sampling Points

The kriging optimization method that can only obtain one sampling point per cycle has encountered a bottleneck in practical engineering applications. How to find a suitable optimization method to generate multiple sampling points at a time while improving the accuracy of convergence and reducing the number of expensive evaluations has been a wide concern. For this reason, a kriging-assisted multi-objective constrained global optimization (KMCGO) method has been proposed. The sample data obtained from the expensive function evaluation is first used to construct or update the kriging model in each cycle. Then, kriging-based estimated target, RMSE (root mean square error), and feasibility probability are used to form three objectives, which are optimized to generate the Pareto frontier set through multi-objective optimization. Finally, the sample data from the Pareto frontier set is further screened to obtain more promising and valuable sampling points. The test results of five benchmark functions, four design problems, and a fuel economy simulation optimization prove the effectiveness of the proposed algorithm.

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Research on the Optimized Tool-Path Planning of Computer Controlled Optical Surfacing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.399-401.1763 ◽

2011 ◽

Vol 399-401 ◽

pp. 1763-1767

Author(s):

Ri Pan ◽

Wei Yang ◽

Yin Biao Guo ◽

Feng Yang ◽

Dong Xu Zhang

Keyword(s):

Convergence Rate ◽

Processing Time ◽

Tool Path ◽

Tool Path Planning ◽

Tool Paths ◽

High Convergence Rate ◽

Computer Controlled Optical Surfacing ◽

Computer Controlled ◽

Removal Processes ◽

Working Efficiency

Computer controlled optical surfacing (CCOS) is widely used in aspheric optical lenses fabrication because of their high convergence rate on surface based on deterministic removal processes since 1963. As an important part of CCOS techniques, reasonable tool-path would increase the polishing speed, decrease the processing time and then improve the efficiency of polishing. Optimized policy combined with improved Prim algorithm is presented in this paper based on the study of the characteristic of aspheric polishing and the tool-paths in common use. The simulated results show that the length of tool-path is reduced so as to decrease the processing time and increase the working efficiency.

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Performance of Sliders Flying Over Discrete-Track Media

Journal of Tribology ◽

10.1115/1.2768069 ◽

2007 ◽

Vol 129 (4) ◽

pp. 712-719 ◽

Cited By ~ 23

Author(s):

Jianhua Li ◽

Junguo Xu ◽

Yuki Shimizu

Keyword(s):

Estimation Method ◽

Simulation Method ◽

Measured Data ◽

Flying Height ◽

Height Loss ◽

Air Bearing ◽

Slider Air Bearing ◽

Discrete Track ◽

Flying Attitude ◽

Manufacturing Variation

A simulation method in which grooves are virtually distributed on the slider air bearing instead of on the grooved medium surface has been developed and used to investigate the performance of sliders flying over the surface of a discrete-track medium. The simulated flying height loss due to a discrete-track medium coincides well with the measured data, whereas the average-estimation method overestimates flying height loss. Among the characteristics of a slider flying over the surface of a discrete-track medium that were studied are the flying attitude, the effect of groove parameters on flying profile, and the flying height losses due to manufacturing variation and altitude. The results indicate that when a slider is flying over the surface of a discrete-track medium, it will have a higher 3σ of flying height, be more sensitive to altitude, and will have a greater flying height loss.

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A High Convergence Rate Solution Method, the Residual Cutting Algorithm, in Iterative Solution of Poisson’s Equation

Turbomachinery Fluid Dynamics and Heat Transfer ◽

10.1201/9780203734919-13 ◽

2017 ◽

pp. 277-290

Author(s):

Atsuhiro Tamura ◽

Kazuo Kikuchi ◽

Tadayasu Takahashi

Keyword(s):

Convergence Rate ◽

Solution Method ◽

Iterative Solution ◽

Poisson’S Equation ◽

Poisson's Equation ◽

High Convergence Rate ◽

Cutting Algorithm

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Effect of Intermolecular Forces on the Static and Dynamic Performance of Air Bearing Sliders: Part II—Dependence of the Stability on Hamaker Constant, Suspension Preload and Pitch Angle

Journal of Tribology ◽

10.1115/1.2000270 ◽

2005 ◽

Vol 128 (1) ◽

pp. 203-208 ◽

Cited By ~ 10

Author(s):

Vineet Gupta ◽

David B. Bogy

Keyword(s):

Pitch Angle ◽

Dynamic Performance ◽

Hard Disk Drives ◽

Intermolecular Forces ◽

Flying Height ◽

Total Force ◽

Air Bearing ◽

Force Increase ◽

The Stability ◽

Fly Height

Intermolecular and surface forces contribute significantly to the total forces acting on air bearing sliders for flying heights below 5 nm. Their contributions to the total force increase sharply with the reduction in flying height, and hence their existence can no longer be ignored in air bearing simulation for hard disk drives. Various experimentally observed dynamic instabilities can be explained by the inclusion of these forces in the model for low flying sliders. In this paper parametric studies are presented using a 3-DOF model to better understand the effect of the Hamaker constants, suspension pre load and pitch angle on the dynamic stability/instability of the sliders. A stiffness matrix is used to characterize the stability in the vertical, pitch, and roll directions. The fly height diagrams are used to examine the multiple equilibriums that exist for low flying heights. It has been found that the system instability increases as the magnitude of the van der Waals force increases. It has also been found that higher suspension pre load and higher pitch angles tend to stabilize the system.

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Computational Models of Bio Heuristics Based on Physical and Cognitive Processes (Review)

INFORMACIONNYE TEHNOLOGII ◽

10.17587/it.27.563-574 ◽

2021 ◽

Vol 27 (11) ◽

pp. 563-574

Author(s):

V. V. Kureychik ◽

◽

S. I. Rodzin ◽

Keyword(s):

Computational Complexity ◽

Convergence Rate ◽

Rate Of Convergence ◽

Cognitive Processes ◽

Computational Models ◽

Optimization Problems ◽

Search Space ◽

Experimental Results ◽

Software Implementation ◽

Minimum Total Length

Computational models of bio heuristics based on physical and cognitive processes are presented. Data on such characteristics of bio heuristics (including evolutionary and swarm bio heuristics) are compared.) such as the rate of convergence, computational complexity, the required amount of memory, the configuration of the algorithm parameters, the difficulties of software implementation. The balance between the convergence rate of bio heuristics and the diversification of the search space for solutions to optimization problems is estimated. Experimental results are presented for the problem of placing Peco graphs in a lattice with the minimum total length of the graph edges.

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