Process design for heat fusion of thermoplastic composites using molecular dynamics and a response surface method

2016 ◽  
Vol 25 (sup1) ◽  
pp. 33-49 ◽  
Author(s):  
Kento Takeuchi ◽  
Ryosuke Matsuzaki ◽  
Tomonaga Okabe ◽  
Yutaka Oya
Keyword(s):  
Molecular Dynamics ◽  
Response Surface ◽  
Response Surface Method ◽  
Process Design ◽  
Thermoplastic Composites ◽  
Surface Method

Blending quality of co-air-textured yarn: Optimization parameters of Kevlar/polypropylene applicable for thermoplastic composites

2018 ◽  
Vol 53 (13) ◽  
pp. 1791-1802
Author(s):  
Mehrdad Hosseinalizadeh ◽  
Mehdi K Dolatabadi ◽  
Saeed S Najar ◽  
Reza E Farsani
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Cross Sections ◽  
Feed Rate ◽  
Textile Composites ◽  
Air Pressure ◽  
Thermoplastic Composites ◽  
Blend Ratio ◽  
Surface Method

Nowadays, hybrid yarns, which consist of at least one-component thermoplastic fibers, are used in thermoplastic textile composites. The uniformity of the fibers in hybrid yarns is a key factor that directly influences the composite properties. Accordingly, one of the main aims of the present research was to optimize the air texturing parameters to achieve the uniform blending of Kevlar/polypropylene fibers. To evaluate the blending uniformity of yarns, the radial, lateral and angular distribution of fibers, based on the position of the pixels of the constituent fibers, was evaluated using the image processing data of yarn cross sections. According to this method, the production parameters, namely, blend ratio, delivery speed, feed rate and air pressure, were optimized simultaneously via the response surface method to obtain the blending uniformity of the fibers. The uniform blending distribution could be achieved by a higher blend ratio of Kevlar/PP (1:6), a lower production speed (300 m/min), a higher feed rate (500 m/min), and a higher air pressure (10 bar). Eventually, it was confirmed that there was a good correlation between the blending quality of the real samples and the predicted quality of the response surface method model.

A Proposal of PSO with Presumption Function of the Solution Landscape by Response Surface Method

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Surface Method

scholarly journals Creep-Based Reliability Evaluation of Turbine Blade-Tip Clearance with Novel Neural Network Regression

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3552 ◽  
Author(s):  
Chun-Yi Zhang ◽  
Jing-Shan Wei ◽  
Ze Wang ◽  
Zhe-Shan Yuan ◽  
Cheng-Wei Fei ◽  
...  
Keyword(s):  
Neural Network ◽  
High Pressure ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Tip Clearance ◽  
Strong Nonlinearity ◽  
Surface Method ◽  
Blade Tip ◽  
Blade Tip Clearance

To reveal the effect of high-temperature creep on the blade-tip radial running clearance of aeroengine high-pressure turbines, a distributed collaborative generalized regression extremum neural network is proposed by absorbing the heuristic thoughts of distributed collaborative response surface method and the generalized extremum neural network, in order to improve the reliability analysis of blade-tip clearance with creep behavior in terms of modeling precision and simulation efficiency. In this method, the generalized extremum neural network was used to handle the transients by simplifying the response process as one extremum and to address the strong nonlinearity by means of its nonlinear mapping ability. The distributed collaborative response surface method was applied to handle multi-object multi-discipline analysis, by decomposing one “big” model with hyperparameters and high nonlinearity into a series of “small” sub-models with few parameters and low nonlinearity. Based on the developed method, the blade-tip clearance reliability analysis of an aeroengine high-pressure turbine was performed subject to the creep behaviors of structural materials, by considering the randomness of influencing parameters such as gas temperature, rotational speed, material parameters, convective heat transfer coefficient, and so forth. It was found that the reliability degree of the clearance is 0.9909 when the allowable value is 2.2 mm, and the creep deformation of the clearance presents a normal distribution with a mean of 1.9829 mm and a standard deviation of 0.07539 mm. Based on a comparison of the methods, it is demonstrated that the proposed method requires a computing time of 1.201 s and has a computational accuracy of 99.929% over 104 simulations, which are improvements of 70.5% and 1.23%, respectively, relative to the distributed collaborative response surface method. Meanwhile, the high efficiency and high precision of the presented approach become more obvious with the increasing simulations. The efforts of this study provide a promising approach to improve the dynamic reliability analysis of complex structures.

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