In this paper, a new optimisation method incorporating lamination parameters and a guide-based blending model is proposed. Lamination parameters for a guide laminate and ply number of each panel are employed as design variables for optimisation with a parallel real-coded genetic algorithm incorporating structure behaviour and manufacturing constraints. During the optimisation process, with a form of least squares fitting adopted, another genetic algorithm is used to obtain the guide stacking sequence of the guide laminate from the guide lamination parameters, and then the laminate configurations of each panel are obtained from the guide stacking sequence and number of plies for each panel. The proposed framework is demonstrated via design of an 18-panel horseshoe configuration, where each panel is optimised individually with a buckling constraint. Numerical results indicate that the present algorithm is capable of obtaining fully blended designs.
The effect of the top electrode interface on the hysteretic behavior of epitaxial ferroelectric Pb(Zr,Ti)O3 thin films with bottom SrRuO3 electrode J. Appl. Phys. 112, 064116 (2012); 10.1063/1.4754318 Role of dual-laser ablation in controlling the Pb depletion in epitaxial growth of Pb(Zr0.52Ti0.48)O3 thin films with enhanced surface quality and ferroelectric properties J. Appl. Phys. 111, 064102 (2012); 10.1063/1.3694035 Misfit strain dependence of ferroelectric and piezoelectric properties of clamped (001) epitaxial Pb(Zr0.52,Ti0.48)O3 thin filmsThe interface effects on the ferroelectric polarization and stability of PbTiO 3 (PTO) films with metallic (Pt) or oxide (LaNiO 3 , SrRuO 3 ) electrodes were studied using density functional theory calculation. It was found that the PTO film with oxide electrodes has stronger electrode/ ferroelectric interface adhesion, lower polarization magnitude, and worse polarization stability, than that with Pt electrode. The PbO-terminated PTO films show weaker adhesion with the electrodes, but have higher polarization magnitude and better polarization stability than the TiO 2 -terminated ones. The strain effects induced by misfit interface were also studied. Results show that the ferroelectric polarization and its stability can be enhanced by applying compressive strain, while depressed by applying tensile strain. V C 2013 AIP Publishing LLC.
Purpose
This paper aims to provide the proper preset temperatures of the convection reflow oven when reflowing a printed circuit board (PCB) assembly with varied sizes of components simultaneously.
Design/methodology/approach
In this study, computational fluid dynamics modeling is used to simulate the reflow soldering process. The training data provided to the machine learning (ML) model is generated from a programmed system based on the physics model. Support vector regression and an artificial neural network are used to validate the accuracy of ML models.
Findings
Integrated physical and ML models synergistically can accurately predict reflow profiles of solder joints and alleviate the expense of repeated trials. Using this system, the reflow oven temperature settings to achieve the desired reflow profile can be obtained at substantially reduced computation cost.
Practical implications
The prediction of the reflow profile subjected to varied temperature settings of the reflow oven is beneficial to process engineers when reflowing bulky components. The study of reflowing a new PCB assembly can be started at the early stage of board design with no need for a physical profiling board prototype.
Originality/value
This study provides a smart solution to determine the optimal preset temperatures of the reflow oven, which is usually relied on experience. The hybrid physics–ML model providing accurate prediction with the significantly reduced expense is used in this application for the first time.
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