scholarly journals Response surface modelling and performance evaluation of solar dryer for drying of grapes

2021 ◽  
Vol 5 (2) ◽  
pp. 157-168
Author(s):  
Aditya Arvind Yadav ◽  
Pravin A. Prabhu ◽  
Jaydeep S. Bagi
Keyword(s):  
Response Surface ◽  
Sugar Content ◽  
Size Variation ◽  
Surface Modelling ◽  
Solar Dryer ◽  
Surface Plot ◽  
Solar Greenhouse ◽  
Response Surface Modelling ◽  
And Performance ◽  
Drying Conditions

The current study focuses on the performance of Solar Greenhouse Dryer for drying of grapes for raisin making in Solar Dryer and Open sun condition in Western Maharashtra.  The Maharashtra state ranks first in the production of grapes, probably Western Maharashtra produces nearly 800 thousand tons of grapes every year. The major wastage of grapes is due to low sugar content, glossy appearance, shrinkage, excess water in berry, scorching and size variation. Therefore, there is a need to preserve the grapes by drying and making raisins for a non-seasonal requirement. The experiment was conducted for drying of grapes in Solar Greenhouse Dryer and Open Sun condition from 1st of April to 4th of April for 48 hours. The initial weight of the grapes to be dried was 500 grams for both Solar Greenhouse Dryer and open sun drying conditions. The experiment was conducted at Bahe, Borgaon, Tal-Walwa, Dist- Sangli, Maharashtra, India located at 17.115o N and 74.33o E.  The main aim of using DOE i.e., Response Surface Modelling is to get an optimum region for drying of grapes in Solar Greenhouse Dryer, from the Surface plot; the region of maxima and minima was obtained.

scholarly journals Experimental Investigation of Thermal Fatigue Die Casting Dies by Using Response Surface Modelling

Metals ◽  
2017 ◽  
Vol 7 (6) ◽  
pp. 191 ◽  
Author(s):  
Hassan Abdulhadi ◽  
Syarifah Ahmad ◽  
Izwan Ismail ◽  
Mahadzir Ishak ◽  
Ghusoon Mohammed
Keyword(s):  
Experimental Investigation ◽  
Response Surface ◽  
Thermal Fatigue ◽  
Die Casting ◽  
Surface Modelling ◽  
Response Surface Modelling

scholarly journals A green membrane distillation system for seawater desalination: Response surface modelling and optimization

2018 ◽  
Vol 361 ◽  
pp. 012011 ◽  
Author(s):  
Siti Khadijah Hubadillah ◽  
Mohd Hafiz Dzarfan Othman ◽  
Paran Gani ◽  
Ahmad Fauzi Ismail ◽  
Mukhlis A. Rahman ◽  
...  
Keyword(s):  
Response Surface ◽  
Membrane Distillation ◽  
Seawater Desalination ◽  
Surface Modelling ◽  
Distillation System ◽  
Response Surface Modelling ◽  
Modelling And Optimization

scholarly journals Predictive modelling to support sensitivity analysis for robust design in aerospace engineering

2020 ◽  
Vol 61 (5) ◽  
pp. 2177-2192 ◽  
Author(s):  
Siva Krishna Dasari ◽  
Abbas Cheddad ◽  
Petter Andersson
Keyword(s):  
Sensitivity Analysis ◽  
Response Surface ◽  
Robust Design ◽  
Aerospace Engineering ◽  
Multivariate Adaptive Regression Splines ◽  
Linear Functions ◽  
Computational Time ◽  
Surface Modelling ◽  
Non Linear ◽  
Response Surface Modelling

AbstractThe design of aircraft engines involves computationally expensive engineering simulations. One way to solve this problem is the use of response surface models to approximate the high-fidelity time-consuming simulations while reducing computational time. For a robust design, sensitivity analysis based on these models allows for the efficient study of uncertain variables’ effect on system performance. The aim of this study is to support sensitivity analysis for a robust design in aerospace engineering. For this, an approach is presented in which random forests (RF) and multivariate adaptive regression splines (MARS) are explored to handle linear and non-linear response types for response surface modelling. Quantitative experiments are conducted to evaluate the predictive performance of these methods with Turbine Rear Structure (a component of aircraft) case study datasets for response surface modelling. Furthermore, to test these models’ applicability to perform sensitivity analysis, experiments are conducted using mathematical test problems (linear and non-linear functions) and their results are presented. From the experimental investigations, it appears that RF fits better on non-linear functions compared with MARS, whereas MARS fits well on linear functions.

Response surface modelling for cleaning and disinfecting materials used in milking systems with electrolysed oxidizing water

2005 ◽  
Vol 58 (2) ◽  
pp. 65-73 ◽  
Author(s):  
STEPHEN P WALKER ◽  
ALI DEMIRCI ◽  
ROBERT E GRAVES ◽  
STEPHEN B SPENCER ◽  
ROBERT F ROBERTS
Keyword(s):  
Response Surface ◽  
Surface Modelling ◽  
Response Surface Modelling ◽  
Materials Used
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