scholarly journals Establishing the Correlations for Eco-Efficiency Index of Various Types of Structural Concrete Used in the Malaysian Housing Using Response Surface Method

2020 ◽  
Vol 10 (12) ◽  
pp. 4372
Author(s):  
Mohd Samsudin Abdul Hamid ◽  
Nasir Shafiq ◽  
Osamah Kiwan
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Linear Trend ◽  
Efficiency Index ◽  
Statistical Technique ◽  
Consumption Pattern ◽  
Residential Housing ◽  
Structural Concrete ◽  
Sustainable Environment ◽  
Surface Method

The concept of a sustainable environment generally refers to the development that creates a balance between the resources consumption pattern and the rate of depletion of natural resources. For determining the level of sustainability of any project, three types of impacts are assessed: economic, environmental, and social. This paper presents an analytical study that focused on establishing a correlation of eco-efficiency index for low-rise reinforced concrete residential housing in Malaysia. A statistical technique using the response surface method was performed, with the help of design expert software. The data was verified using regression analysis and represented by R2 value, standard deviation, and coefficient of variation. By using economic factors, environmental factors, and the eco-efficiency index, 3D model graphs were developed for structural concrete containing fly ash, and blast furnace slag (BFS), which was assigned to the structural members in a single and double story housing. The study has concluded that the correlations established between the cost and carbon emission, economic & environmental scores, and the eco-efficiency index have shown a linear trend for single story housing and a cubic for the double story housing.

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.

scholarly journals The optimization of Sumbawa manganese ore beneficiation using response surface method (RSM)

2021 ◽  
Author(s):  
Alfikri Khair ◽  
Haryudini A. Putri ◽  
Suprapto Suprapto ◽  
Yatim L. Ni’mah
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Manganese Ore ◽  
Surface Method
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