Journal articles: 'Quadratic Response Surface'

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A.V, Dattatreya Rao, and Seshubabu P. "Quadratic response surface designs." International Journal of Advances in Computing and Information Technology 1, no. 2 (April 20, 2012): 174–81. http://dx.doi.org/10.6088/ijacit.12.10022.

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Shehzad, Muhammad Ahmed, Adnan Bashir, Muhammad Noor Ul Amin, Saima Khan Khosa, Muhammad Aslam, and Zubair Ahmad. "Reservoir Inflow Prediction by Employing Response Surface-Based Models Conjunction with Wavelet and Bootstrap Techniques." Mathematical Problems in Engineering 2021 (November 10, 2021): 1–9. http://dx.doi.org/10.1155/2021/4086918.

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Reservoir inflow prediction is a vital subject in the field of hydrology because it determines the flood event. The negative impact of the floods could be minimized greatly if the flood frequency is predicted accurately in advance. In the present study, a novel hybrid model, bootstrap quadratic response surface is developed to test daily streamflow prediction. The developed bootstrap quadratic response surface model is compared with multiple linear regression model, first-order response surface model, quadratic response surface model, wavelet first-order response surface model, wavelet quadratic response surface model, and bootstrap first-order response surface model. Time series data of monsoon season (1 July to 30 September) for the year 2010 of the Chenab river basin are analyzed. The studied models are tested by using performance indices: Nash–Sutcliffe coefficient of efficiency, mean absolute error, persistence index, and root mean square error. Results reveal that the proposed model, i.e., bootstrap quadratic response surface shows good performance and produces optimum results for daily reservoir inflow prediction than other models used in the study.

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Song, Wheyming Tina, and Chien-Chou Su. "CORRELATED SIMULATION EXPERIMENT IN QUADRATIC RESPONSE SURFACE DESIGNS." Journal of the Chinese Institute of Industrial Engineers 19, no. 3 (January 2002): 13–18. http://dx.doi.org/10.1080/10170660209509199.

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Hussey, James R., Raymond H. Myers, and Ernest C. Houck. "Pseudorandom Number Assignment in Quadratic Response Surface Designs." IIE Transactions 19, no. 4 (December 1987): 395–403. http://dx.doi.org/10.1080/07408178708975412.

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Hong, Kyung-Jin, Min-Soo Kim, and Dong-Hoon Choi. "Efficient approximation method for constructing quadratic response surface model." KSME International Journal 15, no. 7 (July 2001): 876–88. http://dx.doi.org/10.1007/bf03185266.

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Ainy Hafeez, Ainy Hafeez, Syed Mohsin Ali Kazmi Syed Mohsin Ali Kazmi, Muhammad Sulaiman Muhammad Sulaiman, and Chaudhry Haider Ali and Nadeem Feroze Chaudhry Haider Ali and Nadeem Feroze. "Optimization of Zinc Ions Removal by Modified Phoenix Dactylifera L. Seeds Using Response Surface Methodology." Journal of the chemical society of pakistan 41, no. 1 (2019): 78. http://dx.doi.org/10.52568/000719/jcsp/41.01.2019.

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The current study investigates the role of Phoenix Dactylifera L. (date palm) seeds as an effective biosorbent for removing Zn+2, a toxic heavy metal pollutant usually found in the waste streams of industries like fertilizer, mining and galvanizing etc. Date palm seeds were washed, dried, crushed in 170-300 um and modified by acidic treatment (0.1 MHNO3). The effect of most important parameters i.e., pH (3.5-6.1), initial zinc ion concentration (5-100mg/l), biosorbent dosage (0.1-1g) and contact time (0.5-60sec) have been studied via design expert software (version 8.0.6) of response surface methodology. The Box-Bhenken Design (BBD) was used in Response Surface Methodology (RSM) for designing the experiments and a number of 29 experiments were run. The model suggested by the design expert software was quadratic as it had maximum R2- value (0.9235) which indicated that the predicted values of quadratic model were best fitted to the experimental values. The significance of the factors was indicated by Analysis of Variance (ANOVA). The results showed that the metal uptake increased by increasing initial zinc concentration and decreasing in biosorbent dosage and pH while the contact time had negligible effect on the response surface. The parameters were numerically optimized and the optimum input parameters obtained were pH = 3.52, initial zinc ion concentration = 59.11ppm, biosorbent dosage = 0.1g and contact time = 60min with a metal uptake of 26.84mg/g. Therefore, (Phoenix Dactylifera L.) seeds substantially removed zinc ions under optimum conditions.

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Han, Feng, Zheng Liang Li, and Wen Liang Fan. "A New Adaptive Higher Order Response Surface Method." Advanced Materials Research 243-249 (May 2011): 5946–54. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5946.

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Response surface method has won numerous concerns in the reliability analysis of structure due to its simplicity and practicability, especially quadratic response surface taking no account of cross terms is most widely used. However, for the complex ultimate state curved surface corresponding to strongly nonlinear, the approximate accuracy of quadratic response surface is apparently not enough, causing a biggish error in estimation of reliability. Although, theoretically, higher order response surface method can resolve this problem, the sharp increase of undetermined coefficient reduces calculation efficiency, and even, cannot achieve. Therefore, on the basis of univariate analysis of multivariable function, an algorithm which can reasonably determine higher order response surface form is presented in this article, able to effectively reduce the number of undetermined coefficients in response surface, so as to reduce computational difficulties and put forward improving measures for possible problems; In addition, based on the tactics of number-theoretic setpoint, a type of scheme of number-theoretic selecting point applicable to response surface method has been developed. Finally, through the analysis of examples, the suggested algorithm was validated, with the result showing that the algorithm has good accuracy and efficiency.

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Law, Poh Gaik, Noor Haida Sebran, Ashraf Zin Zawawi, and Azlan Shah Hussain. "Optimization Study of Biomass Hydrogenation to Ethylene Glycol Using Response Surface Methodology." Processes 8, no. 5 (May 15, 2020): 588. http://dx.doi.org/10.3390/pr8050588.

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Statistical-based study using response surface methodology (RSM) was conducted to study the effects of process parameters towards biomass hydrogenation. Using Malaysian oil palm empty fruit bunches (EFB) fibres as feedstock, the central composite design (CCD) technique was employed and 18 runs were generated by CCD when four parameters (mass ratio of binary catalyst, hydrogen pressure, temperature and mass ratio of catalyst to feedstock) were varied with two center points to determine the effects of process parameters and eventually to get optimum ethylene glycol (EG) yield. RSM with quadratic function was generated for biomass hydrogenation, indicating all factors except temperature, were important in determining EG yield. Analysis of variance (ANOVA) showed a high coefficient of determination (R2) value of >0.98, ensuring a satisfactory prediction of the quadratic model with experimental data. The quadratic model suggested the optimum EG yield should be >25 wt.% and the EG yield results were successfully reproduced in the laboratory.

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Qin, Li, Wei Lin Peng, and Wei Han. "High-Order RSM for Dynamic Reliability of UHV Transmission Tower." Applied Mechanics and Materials 799-800 (October 2015): 1295–98. http://dx.doi.org/10.4028/www.scientific.net/amm.799-800.1295.

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As transmission tower system has the characteristics of large-span and spatial truss structure, the study of the reliability is also developed on the basis of space truss research and large-span structure system. As simple and suitable, RSM (response surface method), in particular, quadratic response surface without considering the cross term is often used in reliability calculation. However, strong nonlinear limit that corresponding to a complex surface, the accuracy of quadratic response surface is inadequate, causing greater reliability estimation error. High-order response surface solves it well. To this end, based on univariate analysis of multivariate function, a reasonable algorithm as to assure that the form of higher-order response surface is proposed; on the algorithm is verified by given examples, the result shows better accuracy and efficiency .

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Gengec, E., M. Kobya, E. Demirbas, A. Akyol, and K. Oktor. "Electrochemical treatment of Baker's yeast wastewater containing melanoidin: optimization through response surface methodology." Water Science and Technology 65, no. 12 (June 1, 2012): 2183–90. http://dx.doi.org/10.2166/wst.2012.130.

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Effluents from Baker's yeast production plant contain a high percentage of color and a large amount of organic load. In the present study, Baker's yeast wastewater (BYW) is treated with the electrocoagulation (EC) process using Al electrodes. Operating parameters (pH, current density, color intensity and operating time) are optimized by response surface methodology (RSM). Quadratic models are developed for the responses which are removal efficiencies of color, chemical oxygen demand (COD) and total organic carbon (TOC) and operating cost (OC). Optimum operating parameters and responses are determined as initial pH 5.2, current density of 61.3 A/m2 and operation time of 33 min, and 71% of color, 24% of COD, 24% of TOC removal efficiencies and OC of 0.869 €/m3, respectively. The quadratic model fits for all responses very well with R2 (>0.95). This paper clearly shows that RSM is able to optimize the operating parameters to maximize the color, COD and TOC removal efficiencies and minimize the OC.

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C, Satheesh, Sevvel P, and Senthil Kumar R. "Experimental Identification of Optimized Process Parameters for FSW of AZ91C Mg Alloy Using Quadratic Regression Models." Strojniški vestnik – Journal of Mechanical Engineering 66, no. 12 (December 15, 2020): 736–51. http://dx.doi.org/10.5545/sv-jme.2020.6929.

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This experimental work aims to devise and establish quadratic regression equations, including various input criteria of a friction stir welding (FSW) technique to predict and determine the responses during the fabrication of AZ91C Mg alloy joints. The input process parameters taken into consideration include the traversing speed of the tool, the speed of rotation of the tool, its pin profile (geometry) and the axial force. A five-level, 4 four-factor composite design (of central nature) was applied, and response surface methodology (RSM) was used to formulate quadratic regression models, to develop 3D response surface charts, and to anticipate the responses for various mechanical properties. The generated quadratic mathematical model was tested and validated using the technique of analysis of variance. Validation experimental trial results outlined in the form of scatter diagrams revealed precedented coincidence with that of the generated models. The AZ91C Mg alloy joints obtained using the tool having taper cylindrical pin geometry employed at 1045 rpm, 1.5 mm/s traversing speed, under the exertion of an axial load of 4.87 kN was found to exhibit improved mechanical properties.

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Bashir, Adnan, Muhammad Ahmed Shehzad, Aamna Khan, Muhammad Nabeel Asghar, Muhammad Aslam, Ramy Aldallal, Mutua Kilai, and Mohamed S. Mohamed. "Response Surface Models Using the Wavelet Technique for Reservoir Inflow Prediction." Mathematical Problems in Engineering 2022 (April 5, 2022): 1–10. http://dx.doi.org/10.1155/2022/5171969.

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Reliable streamflow prediction is vital to improving river operations, flood avoidance, water supply, and water resources management. Recently, response surface models have been launched in reservoir inflow prediction due to their potential to model composite nonlinear behaviour. Authors develop a hybrid model, wavelet quadratic response surface for reservoir inflow prediction in Chenab river basin, Pakistan. Wavelet transform has extensive applications in the field biomedical, engineering, and hydrology. Discrete wavelet transform technique discloses the structure of nonstationary signals. A proper and careful selection of mother wavelet ensure the best performance of wavelet transform. The choice of a suitable wavelet function participates in implementing the wavelet function used in response surface based models for reliable prediction. The performance of the proposed model is checked on different performance indices for model evaluation. The new developed model, wavelet quadratic response surface, depicts excellent results than other studied models.

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Yin, Xiangrong, and Lynne Seymour. "Standard Errors for the Multiple Roots in Quadratic Response Surface Models." Technometrics 47, no. 3 (August 2005): 260–63. http://dx.doi.org/10.1198/004017005000000049.

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Seymour, Lynne, and Xiangrong Yin. "Estimating the Dimensionality of a Ridge in Quadratic Response Surface Models." Quality Technology & Quantitative Management 6, no. 3 (January 2009): 281–94. http://dx.doi.org/10.1080/16843703.2009.11673200.

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Pham, Tung-Dinh, Nam-Ky Nguyen, Cuong-Manh Tran, and Mai Phuong Vuong. "Constructing response surface designs with orthogonal quadratic effects using cyclic generators." Chemometrics and Intelligent Laboratory Systems 198 (March 2020): 103918. http://dx.doi.org/10.1016/j.chemolab.2019.103918.

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Kuldosheva, Firuza S. "Supercritical CO2 extraction of glycyrrhizic acid from licorice root: optimization of extraction conditions using RSM (response surface metodology)." Butlerov Communications 58, no. 6 (June 30, 2019): 114–22. http://dx.doi.org/10.37952/roi-jbc-01/19-58-6-114.

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Extraction of HA from licorice roots was carried out by SC-CO2 with ethanol, as a solvent. Experiments and modeling were denoted by RSM. Licorice root extract was analyzed by chromatography and AAS. The RSM design was used to optimize the variables of the CCE and the GC output. The maximum yield of HA is observed under conditions of 10 MPa, 90.8 and 48.2 °C, 92 minutes and a flow of 1.70 and 1.50 ml/min of CO2 using RSM, respectively. According to RSM, R2 and the modified R2 model are 96.1% and 93.2%, respectively. The accuracy of the GC output model is confirmed by triplet experiments, giving an average extraction yield of 52.2±1.2%, respectively, for RSM. The difference of this study from the data known in the literature lies in the design of experiments on modeling and optimization of the extraction yield. An innovation is the optimization of process parameters via RSM, where the maximum yield is achieved by optimizing the extraction conditions. Estimated optimal yield under specific conditions is confirmed by triple experiments (CHIP) in this study. Notation: P (MPa) – extraction pressure, φ (ml/мин) – CO2 flow rate, R (%) – yield, t (мин) – extraction duration, E (oС) – extraction temperature. RSM is a polynomial model of the 2nd order, to explain the variation in the rate of extraction of GC depending on the variables. The linear terms of temperature, pressure and dynamic time, the quadratic terms of dynamic time and pressure with P ≤ 0.001 are highly reliable. The linear term of the CO2 stream, the quadratic term of temperature, and the terms of interaction t – p and r – the dynamic time with 0.001 0.01 are insignificant. By applying multiple regression analysis to experimental data, one can obtain second-order polynomial equations.

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Yu, Yang, Hai Jiao Yu, and Yin Ping Zhao. "Study on Optimization of Degradation of Landfill Leachate by Electrochemical Oxidation Process with Response Surface Methodology." Advanced Materials Research 989-994 (July 2014): 591–94. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.591.

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This experiment used the response surface methodology to optimize the treatment effect of electrochemical oxidation degradation of landfill leachate. The relationship between current intensity, aeration and pH value was studied by the response surface methodology. The analysis of quadratic polynomial regression and response surface was studied by Design expert7.0 software, and the model was optimized.

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Weglowski, Marek Stanisław. "Experimental Study and Response Surface Methodology for Investigation of FSP Process." Archive of Mechanical Engineering 61, no. 4 (December 1, 2014): 539–52. http://dx.doi.org/10.2478/meceng-2014-0031.

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Abstract The article presents the effect of rotational and travelling speed and down force on the spindle torque acting on the tool in Friction Stir Processing (FSP) process. The response surface methodology (RSM) was applied to find a dependence combining the spindle torque acting on the tool with the rotational speed, travelling speed and the down force. The linear and quadratic models with interaction between parameters were used. A better fitting was achieved for a quadratic model. The studies have shown that the increase in rotational speed causes a decrease in the torque while the increase in travelling speed and down force causes an increase in the torque. The tests were conducted on casting aluminium alloy AlSi9Mg. Metallography examination has revealed that the application of FSP process results in a decrease in the porosity in the modified material and microstructure refining in the stir zone. The segregation of Si and Fe elements was evident in the parent material, while in the friction stir processed area this distribution was significantly uniform.

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Zhao, Yan, Xiao Min Hu, Bin Hui Jiang, Shu Fan Ye, Liang Li, Zhong Tian, and Yu Jia Wang. "Optimization of Capacitive Deionization for Salt Removal from Water with Response Surface Methodology." Applied Mechanics and Materials 368-370 (August 2013): 257–60. http://dx.doi.org/10.4028/www.scientific.net/amm.368-370.257.

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A efficient treatment method capacitive deionization (also called electrosorption) against high salinity and ionic concentration in wastewater or groundwater was discussed. Response surface methodology was used to investigate the effect of electrodes potentials, distance between electrodes plates and flow rates on the desalination rate from water. A quadratic response surface model and optimum level values were obtained based on experimental data under box-behnken design (BBD) of software Design-Expert 8.0. The results showed that the maximum desalination rate was 59.05% on the optimal conditions of potentials, distance between electrodes plates and flow rates were 1.6 V, 2 mm, and 21.32 ml/min, respectively. The analysis of variance on quadratic response surface model indicated that regression model reached significant level, fit well and its reliability and accuracy were in the practicable extent, coinciding with the experimental results perfectly.

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Lin, Yi-Chung, Jack Farr, Kevin Carter, and Benjamin J. Fregly. "Response Surface Optimization for Joint Contact Model Evaluation." Journal of Applied Biomechanics 22, no. 2 (May 2006): 120–30. http://dx.doi.org/10.1123/jab.22.2.120.

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When optimization is used to evaluate a joint contact model's ability to reproduce experimental measurements, the high computational cost of repeated contact analysis can be a limiting factor. This paper presents a computationally-efficient response surface optimization methodology to address this limitation. Quadratic response surfaces were fit to contact quantities (contact force, maximum pressure, average pressure, and contact area) predicted by a discrete element contact model of the tibiofemoral joint for various combinations of material modulus and relative bone pose (i.e., position and orientation). The response surfaces were then used as surrogates for costly contact analyses in optimizations that minimized differences between measured and predicted contact quantities. The methodology was evaluated theoretically using six sets of synthetic (i.e., computer-generated) contact data, and practically using one set of experimental contact data. For the synthetic cases, the response surface optimizations recovered all contact quantities to within 3.4% error. For the experimental case, they matched all contact quantities to within 6.3% error except for maximum contact pressure, which was in error by up to 50%. Response surface optimization provides rapid evaluation of joint contact models within a limited range of relative bone poses and can help identify potential weaknesses in contact model formulation and/or experimental data quality.

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Ruiz, B. López, G. Frutos, P. Sanz Pedrero, and J. P. Martín. "Use of a quadratic response surface in the polarographic determination of lead." Analyst 118, no. 1 (1993): 59–63. http://dx.doi.org/10.1039/an9931800059.

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Mandal, Nripes Kumar, and Berthold Heiligers. "Minimax designs for estimating the optimum point in a quadratic response surface." Journal of Statistical Planning and Inference 31, no. 2 (May 1992): 235–44. http://dx.doi.org/10.1016/0378-3758(92)90032-n.

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Xuan, Hoa N., Jean‐Louis Coulomb, Laurent Gerbaud, Jean‐Christophe Crebier, and Nicolas Rouger. "Application of progressive quadratic response surface method for an oscillation problem optimization." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 31, no. 3 (May 4, 2012): 842–57. http://dx.doi.org/10.1108/03321641211209744.

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Park, Kyoungwoo, and Seungjae Moon. "Optimal design of heat exchangers using the progressive quadratic response surface model." International Journal of Heat and Mass Transfer 48, no. 11 (May 2005): 2126–39. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2004.12.023.

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Huang, Liang-Tsung, and M. Michael Gromiha. "Analysis and prediction of protein folding rates using quadratic response surface models." Journal of Computational Chemistry 29, no. 10 (March 19, 2008): 1675–83. http://dx.doi.org/10.1002/jcc.20925.

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Liong, M. T., and N. P. Shah. "Optimization of Cholesterol Removal by Probiotics in the Presence of Prebiotics by Using a Response Surface Method." Applied and Environmental Microbiology 71, no. 4 (April 2005): 1745–53. http://dx.doi.org/10.1128/aem.71.4.1745-1753.2005.

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ABSTRACT Lactobacillus casei ASCC 292 was grown in the presence of six prebiotics, namely, sorbitol, mannitol, maltodextrin, high-amylose maize, fructooligosaccharide (FOS), and inulin, in order to determine the combination of probiotic and prebiotics that would remove the highest level of cholesterol. A first-order model showed that the combination of L. casei ASCC 292, FOS, and maltodextrin was the most efficient for the removal of cholesterol, and the optimum experimental region was developed by using the steepest ascent. This led to the middle points of probiotic (1.70% [wt/vol]), FOS (4.80% [wt/vol]), and maltodextrin (6.80% [wt/vol]) for the development of a central composite design for optimization. Perturbation plot, response surface, and coefficient estimates showed that all three factors had significant quadratic effects on cholesterol removal, with FOS showing the most conspicuous quadratic change. A second-order polynomial regression model estimated that the optimum condition of the factors for cholesterol removal by L. casei ASCC 292 is 1.71% (wt/vol) probiotic, 4.95% (wt/vol) FOS, and 6.62% (wt/vol) maltodextrin. Validation experiments showed that the predicted optimum conditions were more efficient than the high and low levels of the factors and the center points. A response surface method proved reliable for developing the model, optimizing factors, and analyzing interaction effects. Analyses of growth, substrate utilization, growth yield, mean doubling time, and short-chain fatty acid (SCFA) production by the use of quadratic models indicated that cholesterol removal was growth associated. The concentration of L. casei ASCC 292 had the most significant quadratic effect on all responses studied, except for substrate utilization and SCFA production, which were significantly (P < 0.05) influenced by the interactions between the probiotic and both prebiotics, indicating that they were closely associated with the uptake of prebiotics.

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Morland, L. W. "The general viscous relation for the response of ice and its implications in the reduced model for ice-sheet flow." Journal of Glaciology 53, no. 182 (2007): 435–41. http://dx.doi.org/10.3189/002214307783258413.

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AbstractAnalyses of confined and unconfined compression combined with shear, and of biaxial stress laterally confined or unconfined, are presented for a general deviatoric viscous relation describing the response of an incompressible material. At present, numerical models for ice-sheet flow commonly adopt a very simple viscous law throughout the ice sheet, in which the deviatoric stress is coaxial with the strain rate, and the single response function depends on only one invariant, and is determined by single stress component tests which cannot verify the validity of the simplification. The analysis presented here is concerned with two-stress-component experimental configurations which could determine the general quadratic form of a viscous relation, with two response functions depending on two invariants. It is shown that the two combined compression and shear tests can also check the consistency of a viscous fluid assumption, but not so the biaxial stress tests. Each test allows a direct assessment of the significance of the quadratic term. It is then shown that a significant quadratic term changes the relative stress magnitudes in the commonly adopted reduced model for ice-sheet flow, and that the crucial simplifications are not achieved.

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Chinchilli, Vernon M., Walter H. Carter, Timothy J. Breen, and Eleanor D. Campbell. "An asymptotic confidence interval for the response at the stationary point of a quadratic response surface." Journal of Biopharmaceutical Statistics 1, no. 2 (January 1, 1991): 287–301. http://dx.doi.org/10.1080/10543409108835024.

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Han, Mu Xin, Dong Mei Li, Yu Jie Feng, and Yu Fei Tan. "Process Optimization of Microwave Drying Sludge with Response Surface Methodology." Advanced Materials Research 396-398 (November 2011): 1269–72. http://dx.doi.org/10.4028/www.scientific.net/amr.396-398.1269.

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To enhance further treatment efficiency of the sludge, a process microwave drying of sludge was optimized using response surface methodology (RSM). A quadratic polynomial mathematical model was developed through Box-Behnken experimental design to describe the relationship between tested variables and moisture content of sludge. The experimental values were found to be in accordance with the predicted values, the correlation coefficient is 0.9203(P < 0.001). Estimated optimum parameters were as follows: The sludge: tree bark is 58:1, microwave power is 630w and processing time is 5.32 minutes. Under these conditions, a lowest moisture content of sludge (49.12%) after microwave drying was reached.

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Nguyen, Tuan Hung, Huynh Xuan Le, and Ha Phuong Do. "Fuzzy Finite Element Analysis for Static Responses of Plane Structures." Civil and Environmental Engineering 17, no. 2 (December 1, 2021): 420–37. http://dx.doi.org/10.2478/cee-2021-0045.

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Abstract In this paper, a fuzzy finite element algorithm is investigated to determine static responses of plane structures. This algorithm concerns finite element method, fuzzy sets theory, and response surface method. Firstly, the notion of a standardized triangular fuzzy number is developed and utilized to replace original fuzzy numbers in the surrogate models. Then, the error estimations between the training and the test sets are performed to select the suitable response surface model amongst the regression models. Lastly, a good performance combination of complete and non-complete quadratic polynomial regression models is proposed to define the responses of structures. The merits of the proposed algorithm are illustrated via numerical examples.

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Kamaraj, Raj, Jinu Gowthami Thankachi Raghuvaran, Arul Panimayam, and Haiter Allasi. "Performance and Exhaust Emission Optimization of a Dual Fuel Engine by Response Surface Methodology." Energies 11, no. 12 (December 16, 2018): 3508. http://dx.doi.org/10.3390/en11123508.

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A central composite face-centered design (CCFD) was employed to examine the optimal conditions for the compression ratio of the Sardine Fish Oil Methyl Ester (SFOME) blend to the Thermal cracked Cashew Shell Nut Liquid T-CSNL blend by simultaneously considering the brake thermal efficiency (BTE), the brake specific fuel consumption (BSFC), carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NOx) emissions as response variables. The experimental results obtained were analyzed with the help of Design Expert software, and output response predictions were fitted with a polynomial quadratic model of the second degree. The maximum overall desirability obtained for the entire model was 0.7506 with a compression ratio of 19.31 and blend ratios of 20% for SFOME and 15.72% for T-CSNL by volume proportion. Under optimum conditions, it was found that the predicted and experimental results were very similar, and it can be concluded that the quadratic model of second-order can precisely predict the performance and emission characteristics of engines.

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Xu, Jingshui, Haiying Yang, Chaoyi Zhang, and Chuyi Liu. "Optimised preparation and characterisation of lotus root starch oxidised with sodium hypochlorite (NaOCl) using response surface methodology." Czech Journal of Food Sciences 40, No. 1 (February 24, 2022): 61–68. http://dx.doi.org/10.17221/22/2021-cjfs.

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In this paper, response surface methodology (RSM) was used to study the optimised process conditions of lotus root starches modified by treatment with sodium hypochlorite (NaOCl). Based on the Box-Behnken design, quadratic models were developed to correlate the reaction variables. Analysis of variance (ANOVA) revealed that the active chlorine content was the most significant variable for the response. Under the experimental conditions in this paper, the calculated carboxyl content (CNCOOH) of obtained samples was approximately 0.98% ± 0.02% (n = 5). The spectra of Fourier transform infrared (FTIR) spectroscopy displayed that the formation of carboxyl groups successfully occurred on the oxidised lotus root starches. Scanning electron microscope (SEM) analysis showed that the oxidised lotus root starch (CNCOOH, 0.98%) granules were mostly spherical in shape and their surfaces were slightly rougher than those of native lotus root starch. This work may contribute to providing technical support and theoretical guidance for the production of oxidised lotus root starches using NaOCl as an oxidising agent.

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KHAN, AKHTAR, and KALIPADA MAITY. "3D FINITE ELEMENT MODELING FOR ESTIMATING KEY MACHINABILITY ASPECTS IN TURNING OF COMMERCIALLY PURE TITANIUM." Surface Review and Letters 26, no. 01 (January 2019): 1850136. http://dx.doi.org/10.1142/s0218625x18501366.

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The present work aims at numerical approximation in combination with experimental validation of some of the important performance measures in turning of commercially pure titanium (CP-Ti) with uncoated carbide inserts. A three-dimensional (3D) finite element model was developed based on Lagrangian criterion. Simulation of the turning operation was performed using DEFORM 3D software in order to approximate the responses viz. feed force ([Formula: see text], radial force ([Formula: see text], tangential force ([Formula: see text], flank wear (Vb) and machining temperature ([Formula: see text]. Usui’s tool wear model was used to predict the flank wear. Morphology of the free and back surfaces of the chips was examined under a field emission electron microscope (FESEM). Turning experiments were carried out on a heavy duty lathe equipped with a 3D dynamometer. Secondly, a quadratic model was acquired for all the aforementioned quality characteristics using response surface methodology (RSM). Analysis of variance (ANOVA) test was performed to confirm the adequacy of the developed quadratic model. The results obtained from simulation and quadratic model were compared with the experimental data sets. Finally, an error analysis was done to determine the percentage inaccuracy of both the models. The percentage error for all the turning responses, was observed within 6% which showed the satisfactoriness of the proposed approximation tools. However, the simulation model exhibited lower prediction error when compared with the quadratic counterpart.

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Azhari, Ayu Wazira, Kamaruzzaman Sopian, Dewi Suriyani Che Halin, Abdul Haqi Ibrahim, and Saleem H. Zaidi. "Response Surface Methodology (RSM) in Fabrication of Nanostructured Silicon." Materials Science Forum 857 (May 2016): 151–55. http://dx.doi.org/10.4028/www.scientific.net/msf.857.151.

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In this paper, a respond surface methodology (RSM) model has been developed using three levels Box-Benkhen experimental design (BBD) technique to study the influence of several metal-assisted chemical etching (MACE) process variables on the properties of nanostructured silicon (Si) wafer. Five process variables are examined i.e. concentrations of silver (Ag), hydrofluoric acid (HF), deposition time, H2O2 concentration and etching time as a function of etching rate. Design-Expert® software (version 7.1) is used in formulating the RSM model of five factors with 46 experiments. A regression quadratic model is developed to correlate the process variables where the most significant factors are identified and validated using analysis of variance (ANOVA). The model for etching rate is found to be significant with R2 of 0.8, where both Ag concentrations and etching time are the major influence.

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Jayathilakan, K., Rajkumar Ahirwar, Khudsia Sultana, and M. C. Pandey. "Development of compressed meat based bar using response surface methodology." Defence Life Science Journal 2, no. 2 (May 31, 2017): 226. http://dx.doi.org/10.14429/dlsj.2.11367.

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Studies were carried out to optimize the percentage of ingredients for the development of ready to eat mutton bar. Central composite rotatable design of response surface methodology (RSM) was used for designing the experimental combinations. Matrix for compression was designed by selecting factors like mutton powder, binders and applied pressure. Protein percentage, hardness and over all acceptability (OAA) were taken as responses. OAA and hardness showed highly significant and fitted with quadratic model whereas other response i.e. protein levels found to be significant and fitted with linear model. From the design of experiments 45g/100g of mutton powder with 5g/100g binders having an applied pressure of 142 kg/cm2 yielded a bar having a protein percentage of 35g/100g with a hardness of 20.9 N with an overall acceptability score of 8.6 ±0.2 on a 9 point hedonic scale. The product gives energy of 393 kcal per 100 g.

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Chen, Zhi Gang. "Dynamic Response of Shallow Buried Tunnel Subjected to SH Wave." Advanced Materials Research 163-167 (December 2010): 4265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.163-167.4265.

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The dynamic stress concentration on quadratic and U-shaped cavities in half space, which are similar to the cross-section of the tunnels, is solved in this paper impacted by SH-wave. The analytical solution for the cavity in elastic half space is gained by the complex function method. In the complex plane, the scattering wave which satisfies the zero-stress condition at the horizontal surface can be constructed, the problem can be inverted into a set of algebraic equations to solve coefficients of the constructed scattering wave by least square method. For the earthquake-resistance researches, the numerical examples of the dynamic stress concentration around the quadratic and U-shaped cavities impacted by SH-wave are given. The influences of the dynamic stress concentration by the incident wave number and angle, the depth and shape of the cavity are discussed. It is showed that the interaction among the wave, the surface and the shallow buried tunnels should be cared in half space. In this situation, the dynamic stress concentration around the tunnel is greater obvious than the whole space.

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Datta, S., A. Bandyapadhyay, and P. K. Pal. "Quadratic Response Surface Modeling for Prediction of Bead Geometry in Submerged Arc Welding." Indian Welding Journal 39, no. 1 (January 1, 2006): 33. http://dx.doi.org/10.22486/iwj.v39i1.178945.

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Pérez, Victor M., John E. Renaud, and Layne T. Watson. "Reduced sampling for construction of quadratic response surface approximations using adaptive experimental design." Engineering Computations 25, no. 8 (November 14, 2008): 764–82. http://dx.doi.org/10.1108/02644400810909607.

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PurposeTo reduce the computational complexity per step from O(n2) to O(n) for optimization based on quadratic surrogates, where n is the number of design variables.Design/methodology/approachApplying nonlinear optimization strategies directly to complex multidisciplinary systems can be prohibitively expensive when the complexity of the simulation codes is large. Increasingly, response surface approximations (RSAs), and specifically quadratic approximations, are being integrated with nonlinear optimizers in order to reduce the CPU time required for the optimization of complex multidisciplinary systems. For evaluation by the optimizer, RSAs provide a computationally inexpensive lower fidelity representation of the system performance. The curse of dimensionality is a major drawback in the implementation of these approximations as the amount of required data grows quadratically with the number n of design variables in the problem. In this paper a novel technique to reduce the magnitude of the sampling from O(n2) to O(n) is presented.FindingsThe technique uses prior information to approximate the eigenvectors of the Hessian matrix of the RSA and only requires the eigenvalues to be computed by response surface techniques. The technique is implemented in a sequential approximate optimization algorithm and applied to engineering problems of variable size and characteristics. Results demonstrate that a reduction in the data required per step from O(n2) to O(n) points can be accomplished without significantly compromising the performance of the optimization algorithm.Originality/valueA reduction in the time (number of system analyses) required per step from O(n2) to O(n) is significant, even more so as n increases. The novelty lies in how only O(n) system analyses can be used to approximate a Hessian matrix whose estimation normally requires O(n2) system analyses.

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Donohue, Joan M., Ernest C. Houck, and Raymond H. Myers. "Simulation Designs for Quadratic Response Surface Models in the Presence of Model Misspecification." Management Science 38, no. 12 (December 1992): 1765–91. http://dx.doi.org/10.1287/mnsc.38.12.1765.

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Jaya, Abdul Syukor Mohamad, Siti Zaiton Mohd Hashim, Habibollah Haron, Muhd Razali Muhamad, Md Nizam Abd Rahman, and A. Samad Hasan Basari. "Predictive Modeling of TiN Coating Roughness." Advanced Materials Research 626 (December 2012): 219–23. http://dx.doi.org/10.4028/www.scientific.net/amr.626.219.

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In this paper, an approach in modeling surface roughness of Titanium Nitrite (TiN) coating using Response Surface Method (RSM) is implemented. The TiN coatings were formed using Physical Vapor Deposition (PVD) sputtering process. N2pressure, Argon pressure and turntable speed were selected as process variables. Coating surface roughness as an important coating characteristic was characterized using Atomic Force Microscopy (AFM) equipment. Analysis of variance (ANOVA) is used to determine the significant factors influencing resultant TiN coating roughness. Based on that, a quadratic polynomial model equation represented the process variables and coating roughness was developed. The result indicated that the actual coating roughness of validation runs data fell within the 90% prediction interval (PI) and the residual errors were very low. The findings from this study suggested that Argon pressure, quadratic term of N2pressure, quadratic term of turntable speed, interaction between N2pressure and turntable speed, and interaction between Argon pressure and turntable speed influenced the TiN coating surface roughness.

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Aris, Khadijah Mohamad, Suzana Ramli, Zulhafizal Othman, and Jurina Jaafar. "Evaluation of Ammonia-Nitrogen Removal by Ultrasonic Irradiation in Synthetic Solution Using Response Surface Methodology." Key Engineering Materials 797 (March 2019): 108–17. http://dx.doi.org/10.4028/www.scientific.net/kem.797.108.

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The objective of this study was to evaluate the ability of ultrasonic irradiation to remove ammonia-nitrogen in synthetic solution by considering the factors including initial concentration, pH and irradiation time. Ultrasonic bath was used to provide a constant effective power, frequency and temperature of 150 W, 37 kHz and 60°C, respectively during sonication. It was revealed that the removal efficiency of ammonia-nitrogen improved at lower concentration with basic water environment and extended irradiation time. Based on this judgement, optimization is carried out by using response surface methodology (RSM) of Box Behnken design to develop a quadratic regression model in order to analyze the interactions between the three factors and their effects on the removal efficiency. Optimum removal achieved from the model was found to be 82.26% at 10 mg/L of initial concentration with pH of 11 and sonication for 30 minutes. Verification of the quadratic regression model is done by comparing with the experimental work conducted within the experimental domain.

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Milad, Abdalrhman Abrahim, Sayf A. Majeed, and Nur Izzi Md Yusoff. "Comparative Study of Utilising Neural Network and Response Surface Methodology for Flexible Pavement Maintenance Treatments." Civil Engineering Journal 6, no. 10 (October 1, 2020): 1895–905. http://dx.doi.org/10.28991/cej-2020-03091590.

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The use of Artificial Intelligence (AI) for the prediction of flexible pavement maintenance that is caused by distressing on the surface layer is crucial in the effort to increase the service life span of pavements as well as reduce government expenses. This study aimed to predict flexible pavement maintenance in tropical regions by using an Artificial Neural Network (ANN) and the Response Surface Methodology (RSM) for predicting models for pavement maintenance in the tropical region. However, to predict the performance of the treatment techniques for flexible pavements, we used critical criteria to choose our date from different sources to represent the situation of the current pavement. The effect of the distress condition on the flexible pavement surface performance was one of the criteria considered in our study. The data were chosen in this study for 288 sets of treatment techniques for flexible pavements. The input parameters used for the prediction were severity, density, road function, and Average Daily Traffic (ADT). The finding of regression models in (R2) values for the ANN prediction model is 0.93, while the (R2) values are (RSM) prediction model dependent on the full quadratic is 0.85. The results of two methods were compared for their predictive capabilities in terms of the coefficient of determination (𝑅2), the Mean Squared Error (MSE), and the Root Mean Square Error (RMSE), based on the dataset. The results showed that the prediction made utilizing ANN was very relevant to the goal in contrast to that made using the statistical program RSM based on different types of mathematical methods such as full quadratic, pure quadratic, interactions, and linear regression.

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Ahmady-Asbchin, Salman. "Response surface methodology for cadmium biosorption on Pseudomonas aeruginosa." Water Science and Technology 73, no. 11 (February 19, 2016): 2608–15. http://dx.doi.org/10.2166/wst.2016.061.

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In this research the effects of various physicochemical factors on Cd2+ biosorption such as initial metal concentration, pH and contact exposure time were studied. This study has shown a Cd2+ biosorption, equilibrium time of about 5 min for Pseudomonas aeruginosa and the adsorption equilibrium data were well described by Langmuir equation. The maximum capacity for biosorption has been extrapolated to 0.56 mmol.g−1 for P. aeruginosa. The thermodynamic properties ΔG0, ΔH0, and ΔS0 of Cd2+ for biosorption were analyzed by the equilibrium constant value obtained from experimented data at different temperatures. The results show that biosorption of Cd2+ by P. aeruginosa are endothermic and spontaneous with ΔH value of 36.35 J.mol−1. By response surface methodology, the quadratic model has adequately described the experimental data based on the adjusted determination coefficient (R2 = 0.98). The optimum conditions for maximum uptake onto the biosorbent were established at 0.5 g.l−1 biosorbent concentration, pH 6 for the aqueous solution, and a temperature of 30 °C.

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Ferreira, Joelma M., Ramdayal Swarnakar, and Flávio L. H. da Silva. "Effect of nutrient sources on bench scale vinegar production using response surface methodology." Revista Brasileira de Engenharia Agrícola e Ambiental 9, no. 1 (March 2005): 73–77. http://dx.doi.org/10.1590/s1415-43662005000100011.

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The present work aims to evaluate on a bench scale, the effects of nitrogen and phosphorous nutrient source concentrations in vinegar production, a process that is used by small scale industries in the State of Paraiba. The response surface methodology has been utilized for modeling and optimization of the fermentation process. Initially a 2³ complete factorial design was used, where the effects of initial concentrations of ethyl alcohol, phosphorous and nitrogen sources were observed. After this analysis the concentration range of the nutrient variables were extended and a two level plus a star configuration factorial experimental design was performed. The experimental values are well represented by the linear and quadratic model equations obtained. The optimum concentration of ethanol was 4% in which the yield and the productivity of the acetic acid were maximized to the values of 70% and 0.87 g L-1 h-1 respectively, for a 24 hours fermentation period. The evaluation of the quadratic models showed that the yield of vinegar is maximized from 28.1 to 51.04% and the productivity from 0.69 to 1.29 g L-1 h-1 when the concentration of the nitrogen nutrient in the medium is increased from 0.2 to 2.3 g mL-1. Thus, at the optimized nitrogen nutrient concentration both the yield and the productivity of the vinegar are increased by 1.85 times.

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Zhao, Chang-Cheng, Gui-Hun Jiang, and Jong-Bang Eun. "Optimization of Drying Process for Squid-Laver Snack by a Combined Method of Fuzzy Synthetic and Response Surface Methodology." Journal of Food Quality 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/9761356.

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The aim of this study was to investigate the effects of drying temperature (50–70°C) and drying time (3–5 h) on the physical properties and quality of squid-laver snack (SLS) using response surface methodology combined with a synthetic evaluation method to optimize the drying process conditions. Moisture content, water activity, color (L⁎, a⁎, b⁎), shear force, and overall acceptability were evaluated as responses. Increased drying times and higher temperatures significantly reduced the moisture content and water activity of SLS from 9.07% to 4.76% and 0.136 to 0.056, respectively (p<0.05). There was no significant difference in the L⁎ and a⁎ values under different drying conditions. The quadratic effect of temperature and time was observed for the b⁎ value and overall acceptability of SLS. For shear force, a quadratic and interaction term for drying temperature and time on shear force was observed. In conclusion, the recommended optimal hot air-drying conditions for SLS are temperature and time of 70°C and 3 h, respectively.

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Sahu, Omprakash, Anurag Tiwari, and Dharm Pal. "Recovery of copper from synthetic solution by efficient technology: Membrane separation with response surface methodology." Resource-Efficient Technologies, no. 1 (June 4, 2017): 37–45. http://dx.doi.org/10.18799/24056529/2017/1/115.

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Heavy metals are toxic in nature as declared by theWorld Health Organisation. Excess concentration of heavy metals causes harmful affect andalters the physicochemical characteristics of surrounding environmental parameters. Copper is an important heavy metal present in the aquaticenvironment, including wide industrial applications, and is an essential factor in animal metabolism. To recover and reduce copper concentrationfrom aqueous medium an attempted has been made with membrane technology. In this research work ultra filtration, nano filtration and reserveosmosis have been used. At optimum conditions 4.49 g/L initial concentration, 0.72 m3/h inlet flow rate, 40 bar working pressure were obtainedfor maximum recovery (40.977 g/min) of copper at pH 6.8 with reverse osmosis. To achieve this, 27 experimental runs were developed accordingto central composite design and analysed. The value of R2 > 0.91 for the obtained quadratic model indicates the high correlation between observedor the experimental value of response and response value predicted by the mathematical model. This implies that the experimental data correlatedvery well with the quadratic model chosen for the analysis.

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Liu, Shu Xing, Shuang Zhang, and Wei Na Jiao. "Optimization of Sargassum Extracts Preparation with Complex Enzyme by Response Surface Methodology." Advanced Materials Research 550-553 (July 2012): 1653–58. http://dx.doi.org/10.4028/www.scientific.net/amr.550-553.1653.

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Use Design Expert software to establish a quadratic polynomial model between four factors and content of reducing sugar which is characterization for hydrolysis. The four factors are the amount of complex enzyme, the ratio of complex enzyme, hydrolysis temperature and hydrolysis time. Process of sargassum extracts preparation with complex enzyme is optimized by response surface methodology. The optimum preparation conditions were achieved as follows：amount of complex enzyme is 2.05%, ratio of complex enzyme is 1.98, hydrolysis temperature is 55°C, hydrolysis time is 64minutes, and the final reducing sugar content is 0.832% which is good repeatability.

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Mohamad, Mardawani, Rizki Wannahari, Rosmawani Mohammad, Noor Fazliani Shoparwe, Kwan Wei Lun, and Lim Jun Wei. "ADSORPTION OF MALACHITE GREEN DYE USING SPENT COFFEE GROUND BIOCHAR: OPTIMISATION USING RESPONSE SURFACE METHODOLOGY." Jurnal Teknologi 83, no. 1 (December 7, 2020): 27–36. http://dx.doi.org/10.11113/jurnalteknologi.v83.14904.

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Used coffee grounds usually end up as landfill. However, the unique structural properties of its porous surface make coffee grounds can be transformed into biochar and performed as an alternative low cost adsorbent. Malachite green (MG) is a readily water soluble dye which is used extensively in textile and aquaculture industries. The mordant complex structures of MG generate destructive effects to animals and environment. In this study, adsorption of malachite green using spent coffee ground biochar as adsorbent was investigated. The experiments were designed in two methods: classical and optimisation by response surface methodology. Three parameters were studied, which are adsorbent dosage, contact time and pH while the responses in this study are malachite green removal (%) and adsorption capacity (mg/g). Optimisation studies were performed using response surface methodology. Quadratic model was chosen for both response and studied using central composite design. The correlation coefficient, R2 for the quadratic model of malachite green removal (%) and adsorption capacity (mg/g) were 0.95 and 0.99, respectively. The optimum malachite green removal (%) predicted was found at 99.27%, by using 0.12 g of adsorbent dosage, 43.05 minutes of contact time and pH of 9.45 at desirability of 1.0. The optimum adsorption capacity (mg/g) predicted was found at 118.01 mg/g, by using 0.02 g of adsorbent dosage, 60 minutes of contact time and pH of 10.24 at desirability of 0.98. So, it was concluded that the spent coffee ground biochar can be used as an effective adsorbent for malachite green removal from aqueous solution.

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Rahmawati, Cut. "Optimization of Geopolymer Compressive Strength Using Response Surface Methodology." Jurnal Inotera 8, no. 2 (July 13, 2023): 203–12. http://dx.doi.org/10.31572/inotera.vol8.iss2.2023.id242.

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Geopolymers have issues related to cracking resistance and pore filling, decreasing their mechanical strength. However, the addition of nanosilica and Cellulose Nanocrystals (CNCs) has been found to enhance their mechanical properties. This study focused on optimizing the utilization of nanosilica and CNCs to enhance the compressive strength of geopolymers. This research employed Response Surface Methodology (RSM) with Central Composite Design (CCD). The concentrations of nanosilica and CNCs used in the experiments ranged from 2% to 4% and 1% to 3%, respectively. The experimental results consist of 13 runs, including 5 center point runs. The model suggested concentrations of nanosilica and CNCs of 3.98% and 1%, respectively, for an optimal compressive strength of 22.20 MPa. The proposed quadratic model exhibited high accuracy, as evidenced by an R2 of 0.9865, Adj- R2 of 0.9769, and predicted R2 of 0.9168. The closeness of R2 to 1 indicates a strong correlation between the actual and predicted values, thus highlighting the model's significant relevance. Ultimately, the model developed in this study holds the potential for predicting the compressive strength of geopolymers incorporating nanosilica and CNCs.

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Lessoued, Ridha, Fatiha Souahi, and Leonor Castrillon Pelaez. "Assessment of coagulation pretreatment of leachate by response surface methodology." Water Science and Technology 76, no. 9 (July 7, 2017): 2321–27. http://dx.doi.org/10.2166/wst.2017.397.

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Abstract Coagulation-flocculation is a relatively simple technique that can be used successfully for the treatment of old leachate by poly-aluminum chloride (PAC). The main objectives of this study are to design the experiments, build models and optimize the operating parameters, dosage m and pH, using the central composite design and response surface method. Developed for chemical organic matter (COD) and turbidity responses, the quadratic polynomial model is suitable for prediction within the range of simulated variables as it showed that the optimum conditions were m of 5.55 g/L at pH 7.05, with a determination coefficient R² at 99.33%, 99.92% and adjusted R² at 98.85% and 99.86% for both COD and turbidity. We confirm that the initial pH and PAC dosage have significant effects on COD and turbidity removal. The experimental data and model predictions agreed well and the removal efficiency of COD, turbidity, Fe, Pb and Cu reached respectively 61%, 96.4%, 97.1%, 99% and 100%.

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Journal articles on the topic 'Quadratic Response Surface'

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