Wyniki wyszukiwania - BazTech

1

Analysis Of Factors Affecting Gravity-Induced Deflection For Large And Thin Wafers In Flatness Measurement Using Three-Point-Support Method

Liu H., Dong Z., Kang R., Zhou P., Gao S.

Metrology and Measurement Systems

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2015

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Vol. 22, nr 4

531--546

EN

Accurate flatness measurement of silicon wafers is affected greatly by the gravity-induced deflection (GID) of the wafers, especially for large and thin wafers. The three-point-support method is a preferred method for the measurement, in which the GID uniquely determined by the positions of the supports could be calculated and subtracted. The accurate calculation of GID is affected by the initial stress of the wafer and the positioning errors of the supports. In this paper, a finite element model (FEM) including the effect of initial stress was developed to calculate GID. The influence of the initial stress of the wafer on GID calculation was investigated and verified by experiment. A systematic study of the effects of positioning errors of the support ball and the wafer on GID calculation was conducted. The results showed that the effect of the initial stress could not be neglected for ground wafers. The wafer positioning error and the circumferential error of the support were the most influential factors while the effect of the vertical positioning error was negligible in GID calculation.

2

A Hybrid Invasive Weed Optimization with Feasibility-Based Rule for Constrained Optimization Problem

Chen H., Zhou P., Guo P., Ouyang X., He S., Zheng H.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

160-167

EN

During the past decade, hybrid algorithms combining evolutionary computation and constraint-handling techniques is one of the most popular method to solve constrained optimization problems. Usually, penalty functions are often used in constrained optimization. But it is difficult to strike the right balance between objective and penalty functions. As a novel population-based algorithm, invasive weed optimization (IWO) algorithm has gained wide applications in a variety of fields, especially for unconstrained optimization problems. In this paper, a hybrid IWO (HIWO) with a feasibility-based rule is proposed to solve constrained optimization problems. The feasibility-based rule does not need additional parameters, which is different from penalty functions. In addition, the complex method is used to provide direction for weed evolution, which can accelerate the convergence speed. Simulation and comparisons based on several well-studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed HIWO.

PL

W artykule przedstawiono opracowaną metodę optymalizacji z funkcją kosztu, bazującą na hybrydowej metodzie IWO (ang. Hybrid Invasive Weed Optimizastion) oraz regułach związanych z wykonalnością. Zasady wykonalności, w przeciwieństwie do funkcji kar, nie wymagają dodatkowych parametrów. Dodatkowo zastosowano kompleksową metodę określania kierunki ewolucji trawy w algorytmie IWO, co pozwala na przyspieszenie konwergencji. Przeprowadzone badania symulacyjne i porównawcze dowodzą skuteczności i sprawności proponowanej metody HIWO.

3

Development of a 3D Dynamic Programming Method for Weather Routing

Wei S., Zhou P.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2012

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Vol. 6, no. 1

79--85

EN

This paper presents a novel forward dynamic programming method for weather routing to min-imize ship fuel consumption during a voyage. Compared with the traditional two dimensional dynamic pro-gramming (2DDP) methods which only optimize the ship’s heading, while the engine power or propeller rota-tion speed are set as a constant throughout the voyage, this new method considers both the ship power setting and heading control. A float state technique is used to reduce the iteration on the process of optimization for computing time saving. This new method could lead to a real global-optimal routing in a comparison with a tradition weather routing method which results in a sub-optimal routing.