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Journal articles on the topic 'Response surface'

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Published: 4 June 2021

Last updated: 25 May 2024

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1

Jin, J., X. Wang, Y. Han, Y. Cai, Y. Cai, H. Wang, L. Zhu, L. Xu, L. Zhao, and Z. Li. "Combined beef thawing using response surface methodology." Czech Journal of Food Sciences 34, No. 6 (December 21, 2016): 547–53. http://dx.doi.org/10.17221/138/2016-cjfs.

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Based on four thawing methods (still air, still water, ultrasonic wave, and microwave) and single-factor tests, we established a four-factor three-level response surface methodology for a regression model (four factors: pH, drip loss rate, cooking loss rate, protein content). The optimal combined thawing method for beef rib-eye is: microwave thawing (35 s work/10 s stop, totally 170 s) until beef surfaces soften, then air thawing at 15°C until the beef centre temperature reaches –8°C, and finally ultrasonic thawing at 220 W until the beef centre temperature rises to 0°C. With this method, the drip loss rate is 1.9003%, cooking loss rate is 33.3997%, and protein content is 229.603 μg, which are not significantly different from the model-predicted theoretical results (P ≥ 0.05).

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2

Dube, Vinitkumar Dilipkumar. "Optimization of Biodiesel (MOME) Using Response Surface Methodology (RSM)." International journal of Emerging Trends in Science and Technology 04, no. 11 (November 13, 2016): 4736–41. http://dx.doi.org/10.18535/ijetst/v3i11.02.

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3

Manuel, Jeremia, Raffi Paramawati, and Maria D. P. Masli. "UTILIZATION OF RESPONSE SURFACE METHODOLOGY IN THE OPTIMIZATION OF ROSELLE ICE CREAM MAKING [Penggunaan Response Surface Methodology dalam Optimisasi Pembuatan Es Krim Rosella]." Jurnal Teknologi dan Industri Pangan 25, no. 2 (December 2014): 125–33. http://dx.doi.org/10.6066/jtip.2014.25.2.125.

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4

Shibata, Mario. "Response Surface Methodology." Nippon Shokuhin Kagaku Kogaku Kaishi 60, no. 12 (2013): 728–29. http://dx.doi.org/10.3136/nskkk.60.728.

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5

Myers, Raymond H., and Douglas C. Montgomery. "Response Surface Methodology." IIE Transactions 28, no. 12 (December 1996): 1031–32. http://dx.doi.org/10.1080/15458830.1996.11770760.

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6

Copeland, Karen A. F. "Response Surface Methodology." Journal of Quality Technology 28, no. 2 (April 1996): 262. http://dx.doi.org/10.1080/00224065.1996.11979672.

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7

Ginebra, Josep, and Murray K. Clayton. "Response Surface Bandits." Journal of the Royal Statistical Society: Series B (Methodological) 57, no. 4 (November 1995): 771–84. http://dx.doi.org/10.1111/j.2517-6161.1995.tb02062.x.

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8

Khuri, André I., and Siuli Mukhopadhyay. "Response surface methodology." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 2 (March 2010): 128–49. http://dx.doi.org/10.1002/wics.73.

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9

PRAJINA N V, PRAJINA N. V., and T. D. JOHN T D JOHN. "Multi Response Optimization of Cutting Forces in End Milling Using Response Surface Methodology and Desirability Function." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 126–30. http://dx.doi.org/10.15373/22778179/may2013/45.

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10

Doti, Baqe, Daudi Nyaanga, Samwel Nyakach, Jane Nyaanga, and Oscar Ingasia. "Biochar production and quality optimization using response surface methodology technique." Applied Research Journal of Environmental Engineering 4, no. 1 (March 31, 2022): 1–16. http://dx.doi.org/10.47721/arjee20220401011.

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The dependency on fossil fuels can be reduced by the use of renewable energy sources like biomass and it can make a remarkable contribution to the reduction of CO2 emissions and as a result reducing the carbon footprint hence eliminating the greenhouse gas effect. Biomass materials that go to waste can be recovered through the pyrolysis process in order to produce biochar which can be used as a source of energy for cooking. The aim of this study was to carry out optimization of biochar production and quality using the Response Surface Methodology technique. The parameters varied were feedstock moisture content (FMC) (10%, 15% and 20%), pyrolysis residence time (PRT) (in minutes) 90, 135 and 180 and chimney inclination angle (CIA) (30o, 45o and 60o). An experimental insulated metallic carbonization kiln (1 m high and 0.5 m diameter) was developed and used. Response Surface Methodology technique by using Box-Behnken Design was used to develop a mathematical equation to predict the production and quality of the biochar with respect to varied parameters which was later optimized to determine the optimal conditions for biochar production and quality. The biochar quality was based on its moisture content (MC), volatile matter (VM), ash content (AC), fixed carbon (FC) and pH. The combined optimal conditions were 10% feedstock moisture content, 126.93 min pyrolysis residence time and 30o chimney inclination angle resulting to production of 44.35%, MC = 3.82%, VM = 23.52%, AC = 2.94%, FC = 67.89% and pH = 9.28. The mathematical equation developed had composite desirability (CD) of 0.9490 at a p-value≤0.05 which made it viable. These research findings are of importance since optimization reduces the wastage of resources resulting into increase in the efficiency of the pyrolysis system. Keywords: Renewable Energy, Pyrolysis, Biochar, Optimization, Response Surface Methodology

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11

Zhang, Q., Y. Lin, S. Shen, Z. Xing, and X. Ruan. "Simulation and Optimization on Cellulase Immobilization Using Response Surface Methodology." International Journal of Environmental Science and Development 6, no. 9 (2015): 664–67. http://dx.doi.org/10.7763/ijesd.2015.v6.677.

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12

Aruna, M. "Optimization of Parameters for Student Assessment Using Response Surface Methodology." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 31, 2019): 1492–97. http://dx.doi.org/10.5373/jardcs/v11sp10/20192994.

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13

M, Aruna, and Rashmi Rani. "Optimization of Parameters for Student Assessment Using Response Surface Methodology." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11-SPECIAL ISSUE (February 20, 2019): 540–45. http://dx.doi.org/10.5373/jardcs/v11sp11/20193064.

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14

Yumnam, S. "OPTIMIZATION OF TANNASE POSITIVE PROBIOTIC PRODUCTION BY SURFACE RESPONSE METHODOLOGY." Biotechnologia acta 7, no. 5 (2014): 62–70. http://dx.doi.org/10.15407/biotech7.05.062.

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15

Park, Kwon Hyun, Min Soo Heu, and Jin-Soo Kim. "Development of Salted Semi-dried Common Gray Mullet Mugil cephalus using Response Surface Methodology." Korean Journal of Fisheries and Aquatic Sciences 48, no. 6 (December 31, 2015): 839–48. http://dx.doi.org/10.5657/kfas.2015.0839.

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16

Rawal, Manjunath R., Vaibhav Varane, and Rakesh R. Kolhapure. "Process Parameter Optimization for Resistance Spot Welding using Response Surface Methdology." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1078–82. http://dx.doi.org/10.31142/ijtsrd23151.

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17

Huang, Xin, and Michael A. Paradiso. "V1 Response Timing and Surface Filling-In." Journal of Neurophysiology 100, no. 1 (July 2008): 539–47. http://dx.doi.org/10.1152/jn.00997.2007.

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There is ample evidence from demonstrations such as color induction and stabilized images that information from surface boundaries plays a special role in determining the perception of surface interiors. Surface interiors appear to “fill-in.” Psychophysical experiments also show that surface perception involves a slow scale-dependent process distinct from mechanisms involved in contour perception. The present experiments aimed to test the hypothesis that surface perception is associated with relatively slow scale-dependent neural filling-in. We found that responses in macaque primary visual cortex (V1) are slower to surface interiors than responses to optimal bar stimuli. Moreover, we found that the response to a surface interior is delayed relative to the response to the surface's border and the extent of the delay is proportional to the distance between a receptive field and the border. These findings are consistent with some forms of neural filling-in and suggest that V1 may provide the neural substrate for perceptual filling-in.

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18

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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19

Donnelly, T. A. "Response-surface experimental design." IEEE Potentials 11, no. 1 (February 1992): 19–21. http://dx.doi.org/10.1109/45.127696.

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20

Trinca, Luzia A., and Steven G. Gilmour. "Multistratum Response Surface Designs." Technometrics 43, no. 1 (February 2001): 25–33. http://dx.doi.org/10.1198/00401700152404291.

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21

Draper, Norman R., and Dennis K. J. Lin. "Small Response-Surface Designs." Technometrics 32, no. 2 (May 1990): 187–94. http://dx.doi.org/10.1080/00401706.1990.10484634.

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22

Lin, Dennis K. J., and Wanzhu Tu. "Dual Response Surface Optimization." Journal of Quality Technology 27, no. 1 (January 1995): 34–39. http://dx.doi.org/10.1080/00224065.1995.11979556.

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23

Goos, P., and A. N. Donev. "Blocking response surface designs." Computational Statistics & Data Analysis 51, no. 2 (November 2006): 1075–88. http://dx.doi.org/10.1016/j.csda.2005.11.003.

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24

P.B.Wagh, P. B. Wagh, Dr R. R. Deshmukh Dr. R.R.Deshmukh, and R. D. Gurav R.D.Gurav. "Mathematical Modeling and Process Parameters Optimization for Surface Roughness in Edm for En31 Material by Response Surface Methodology." Indian Journal of Applied Research 3, no. 10 (October 1, 2011): 1–3. http://dx.doi.org/10.15373/2249555x/oct2013/50.

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25

O’Neill, Larry W., Dudley B. Chelton, and Steven K. Esbensen. "Covariability of Surface Wind and Stress Responses to Sea Surface Temperature Fronts." Journal of Climate 25, no. 17 (April 18, 2012): 5916–42. http://dx.doi.org/10.1175/jcli-d-11-00230.1.

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Abstract The responses of surface wind and wind stress to spatial variations of sea surface temperature (SST) are investigated using satellite observations of the surface wind from the Quick Scatterometer (QuikSCAT) and SST from the Advanced Microwave Scanning Radiometer on the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) Aqua satellite. This analysis considers the 7-yr period June 2002–May 2009 during which both instruments were operating. Attention is focused in the Kuroshio, North and South Atlantic, and Agulhas Return Current regions. Since scatterometer wind stresses are computed solely as a nonlinear function of the scatterometer-derived 10-m equivalent neutral wind speed (ENW), qualitatively similar responses of the stress and ENW to SST are expected. However, the responses are found to be more complicated on the oceanic mesoscale. First, the stress and ENW are both approximately linearly related to SST, despite a nonlinear relationship between them. Second, the stress response to SST is 2 to 5 times stronger during winter compared to summer, while the ENW response to SST exhibits relatively little seasonal variability. Finally, the stress response to SST can be strong in regions where the ENW response is weak and vice versa. A straightforward algebraic manipulation shows that the stress perturbations are directly proportional to the ENW perturbations multiplied by a nonlinear function of the ambient large-scale ENW. This proportionality explains why both the stress and ENW depend linearly on the mesoscale SST perturbations, while the dependence of the stress perturbations on the ambient large-scale ENW explains both the seasonal pulsing and the geographic variability of the stress response to SST compared with the less variable ENW response.

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26

Anjneya, Kumar, and Koushik Roy. "Response surface-based structural damage identification using dynamic responses." Structures 29 (February 2021): 1047–58. http://dx.doi.org/10.1016/j.istruc.2020.11.033.

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27

He, Zhen, Jing Wang, Jinho Oh, and Sung H. Park. "Robust optimization for multiple responses using response surface methodology." Applied Stochastic Models in Business and Industry 26, no. 2 (March 2010): 157–71. http://dx.doi.org/10.1002/asmb.788.

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28

Robles, Daniel, Aritza Brizuela, Manuel Fernández-Domínguez, and Javier Gil. "Osteoblastic and Bacterial Response of Hybrid Dental Implants." Journal of Functional Biomaterials 14, no. 6 (June 13, 2023): 321. http://dx.doi.org/10.3390/jfb14060321.

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Bacterial infections in dental implants generate peri-implantitis disease that causes bone loss and the mobility of the dental implant. It is well known that specific ranges of roughness favor the proliferation of bacteria, and it is for this reason that new dental implants called hybrids have appeared. These implants have a smooth area in the coronal part and a rough surface in the apical part. The objective of this research is the physico-chemical characterization of the surface and the osteoblastic and microbiological behavior. One-hundred and eighty discs of titanium grade 3 with three different surfaces (smooth, smooth–rough, and completely rough) were studied. The roughness was determined by white light interferometry, and the wettability and surface energy by the sessile drop technique and the application of Owens and Wendt equations. Human osteoblast SaOS-2 was cultured to determine cell adhesion, proliferation, and differentiation. Microbiological studies were performed with two common bacterial strains in oral infection, E. faecalis and S. gordonii, at different times of culture. The roughness obtained for the smooth surface was Sa = 0.23 and for the rough surface it was 1.98 μm. The contact angles were more hydrophilic for the smooth surface (61.2°) than for the rough surface (76.1°). However, the surface energy was lower for the rough surface (22.70 mJ/m2) in both its dispersive and polar components than the smooth surface (41.77 mJ/m2). Cellular activity in adhesion, proliferation, and differentiation was much higher on rough surfaces than on smooth surfaces. After 6 h of incubation, the osteoblast number in rough surfaces was more than 32% higher in relation to the smooth surface. The cell area in smooth surfaces was higher than rough surfaces. The proliferation increased and the alkaline phosphatase presented a maximum after 14 days, with the mineral content of the cells being higher in rough surfaces. In addition, the rough surfaces showed greater bacterial proliferation at the times studied and in the two strains used. Hybrid implants sacrifice the good osteoblast behavior of the coronal part of the implant in order to obstruct bacterial adhesion. The following fact should be considered by clinicians: there is a possible loss of bone fixation when preventing peri-implantitis.

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29

Jiang, Shui-Hua, Dian-Qing Li, Chuang-Bing Zhou, and Li-Min Zhang. "Capabilities of stochastic response surface method and response surface method in reliability analysis." Structural Engineering and Mechanics 49, no. 1 (January 10, 2014): 111–28. http://dx.doi.org/10.12989/sem.2014.49.1.111.

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30

Qudeiri, Jaber E. Abu, Fayez Y. Abu Khadra, Usama Umer, and Hussein M. A. Hussein. "Response Surface Metamodel to Predict Springback in Sheet Metal Air Bending Process." International Journal of Materials, Mechanics and Manufacturing 3, no. 4 (2015): 266–69. http://dx.doi.org/10.7763/ijmmm.2015.v3.208.

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31

Hussain, Sarfraz, Salim-ur Rehman, Qaisar Raza, Itrat Fatima, Syeda Mahvish Zahra, Farhat Rashid, and Ayesha Rafique. "Optimization of sensory properties of chemically preserved Mushrooms through response surface methodology." International Journal of Scientific Innovations 01, no. 01 (December 31, 2017): 006–14. http://dx.doi.org/10.32594/ijsi.2017.0102.

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32

Demirkɪran, Nizamettin, G. Deniz Turhan Özdemir, and Merve Dardağan. "Application of Response Surface Method to Copper Cementation by Metallic Aluminum Particles." Chemistry & Chemical Technology 14, no. 4 (December 15, 2020): 590–96. http://dx.doi.org/10.23939/chcht14.04.590.

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In the present study, the interactive effects of the process variables containing copper concentration, temperature, and time on the efficiency of copper cementation by metallic aluminum particles were examined by using response surface methodology (RSM). It was observed that the efficiency of cementation increased with an increase in the initial concentration of copper, temperature and time. The multiple regression analysis to the experimental data was applied to see the interactive effects of process variables. The second-order polynomial equation was obtained. The optimal values were found to be 0.075 mol/l, 303 K, and 90 min to maximize the amount of the deposited copper.

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33

Utomo, Budi, and Muhammad Iqbal. "Vertical Motion Optimization of Series 60 Hull Forms Using Response Surface Methods." Kapal: Jurnal Ilmu Pengetahuan dan Teknologi Kelautan 17, no. 3 (October 29, 2020): 130–37. http://dx.doi.org/10.14710/kapal.v17i3.33212.

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There are many aspects to analyze seakeeping performance, one of which is the ship's vertical motion. As well-known, vertical motion and its derivatives, vertical velocity and acceleration, will be related to other aspects of seakeeping performance, such as slamming, deck wetness, and MSI. This study discusses optimizing the hull shape with small vertical motion using the Response Surface Methods (RSM). This research aims to minimize the ship's vertical motion so that the ship's performance is better than the initial one. Besides, this research was conducted to apply the RSM in the naval architecture field. The hull's shape used in this study is Series 60 hull form with a length of 31 m. The variables used for the optimization process are the ratio of L/B (X1) and B/T (X2) in the range of ± 10% with fixed displacement. Seakeeping analysis was carried out at a speed of 6.78 knots (Fr 0.2), a heading angle of 180°, and a significant wave height of 0.77 meters. The results show that the optimum model is found in Model 9 where the value of X1 = -2.94 or L/B = 6.71 and X2 = 5 or B/T = 2.75. Model 9 can reduce the vertical motion of the ship by 16.38%.

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34

Cynthia. S. J, Cynthia S. J., and John Don Bosco. S. "Process Optimization for Tamarindus Indica. L Pulp Extraction Using Response Surface Methodology." International Journal of Scientific Research 2, no. 4 (June 1, 2012): 183–85. http://dx.doi.org/10.15373/22778179/apr2013/64.

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35

Nie, Bin, Dan Liao, Jing Ding, and Yao Dong He. "Multiple-Response Surface Approach: Modeling and Optimization." Advanced Materials Research 339 (September 2011): 321–25. http://dx.doi.org/10.4028/www.scientific.net/amr.339.321.

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Many products and processes have multidimensional characteristics and criteria. As these responses involve common parameters and processes, the response data are correlated. The quality and reliability improvement of such products and processes will typically involve multiple-response optimizations to find optimal operating conditions. Many of the current multiple-response optimization approaches assume a single-response uncertainty in the response models, and the uncertainty in the parameter estimates of the models. In this paper, we consider a Bayesian Model Average (BMA) approach to the modeling and optimization of variability of the predictions and the uncertainty of the model parameters. We further propose a Mahalanobis distance (MD) approach to account for the correlations among the response and the variation in the estimation of the response model.

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36

Salimana, MAR, A. Zaidonb, ES Bakarb, SH Leeb, PM Tahira, NF Leemona, MF Kaipina, and AH Julianaa. "RESPONSE SURFACE METHODOLOGY MODEL OF." JOURNAL OF TROPICAL FOREST SECIENCE 29, no. 3 (July 31, 2017): 318–24. http://dx.doi.org/10.26525/jtfs2017.29.3.318324.

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37

Myers, Raymond H., André I. Khuri, Walter H. Carter, and Andre I. Khuri. "Response Surface Methodology: 1966-1988." Technometrics 31, no. 2 (May 1989): 137. http://dx.doi.org/10.2307/1268813.

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38

Gilmour, Steven G., and Luzia A. Trinca. "Fractional polynomial response surface models." Journal of Agricultural, Biological, and Environmental Statistics 10, no. 1 (March 2005): 50–60. http://dx.doi.org/10.1198/108571105x29029.

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39

Engel, Ronald E., John M. Sorensen, Randall S. May, Kenneth J. DOran, N. G. Trikouros, and Eugene S. Mozias. "Response Surface Development Using RETRAN." Nuclear Technology 93, no. 1 (January 1991): 65–81. http://dx.doi.org/10.13182/nt91-a34519.

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40

YAMAZAKI, Koetsu. "Development of Response Surface Approach." Journal of the Society of Mechanical Engineers 109, no. 1050 (2006): 377–79. http://dx.doi.org/10.1299/jsmemag.109.1050_377.

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41

Tantbirojn, Daranee, Antheunis Versluis, Maria R. Pintado, Ralph Delong, and Carol Dunn. "TOOTH SURFACE LOSS: Authors' response." Journal of the American Dental Association 143, no. 7 (July 2012): 730–32. http://dx.doi.org/10.14219/jada.archive.2012.0247.

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42

Kshirsagar, Anant M., and Min-Chu Lin. "Reinforcement of Response Surface Designs." Communications in Statistics - Simulation and Computation 18, no. 3 (January 1989): 971–84. http://dx.doi.org/10.1080/03610918908812802.

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43

Steinberg, David M., and Dizza Bursztyn. "Response Surface Methodology in Biotechnology." Quality Engineering 22, no. 2 (March 5, 2010): 78–87. http://dx.doi.org/10.1080/08982110903510388.

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44

Myers, Raymond H., André I. Khuri, and Walter H. Carter. "Response Surface Methodology: 1966–l988." Technometrics 31, no. 2 (May 1989): 137–57. http://dx.doi.org/10.1080/00401706.1989.10488509.

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45

Gilmour, Steven G., and Luzia A. Trinca. "Row-Column Response Surface Designs." Journal of Quality Technology 35, no. 2 (April 2003): 184–93. http://dx.doi.org/10.1080/00224065.2003.11980206.

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46

McDaniel, William R., and Bruce E. Ankenman. "A response surface test bed." Quality and Reliability Engineering International 16, no. 5 (2000): 363–72. http://dx.doi.org/10.1002/1099-1638(200009/10)16:5<363::aid-qre345>3.0.co;2-k.

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47

Chipman, Hugh, Edward I. George, Robert B. Gramacy, and Robert McCulloch. "Bayesian treed response surface models." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3, no. 4 (July 2013): 298–305. http://dx.doi.org/10.1002/widm.1094.

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48

Masin, Sergio Cesare. "Response bias in grouping." Paidéia (Ribeirão Preto) 14, no. 27 (April 2004): 45–48. http://dx.doi.org/10.1590/s0103-863x2004000100007.

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Surface color similarity may cause the perceptual grouping of uniform achromatic surfaces on an achromatic background both when the background is homogeneous and when the background contains achromatic context surfaces. Empirical results reported here show that the grouping response due to the similarity in color of test surfaces is also affected by context surfaces. It is proposed that this response bias results from interference of the grouping response caused by the similarity in color of test surfaces with an implicit grouping response caused by the similarity in color between context surfaces and test surfaces.

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49

Pradhan, Mohan Kumar, and Chandan Kumar Biswas. "Response Surface Analysis of EDMED Surfaces of AISI D2 Steel." Advanced Materials Research 264-265 (June 2011): 1960–65. http://dx.doi.org/10.4028/www.scientific.net/amr.264-265.1960.

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In this study, the effects of the machining parameters in electrical-discharge machining (EDM) on the machining characteristics of AISI D2 steel using copper electrodes were investigated. The response functions considered material removal rate (MRR) and Surface Roughness (Ra),while machining variables are pulse current, pulse on time, pause time and gap voltage. A Response surface methodology was used to reduce the total number of experiments. Empirical models correlating process variables and their interactions with the said response functions have been established. The significant parameters that critically influenced the machining characteristics were examined, and the optimal combination levels of machining parameters for material removal rate, and surface roughness were determined. The models developed reveal that pulse current is the most significant machining parameter on the response functions followed by voltage and pulse off time for MRR. However for, for Ra also pulse current is most significant followed by pulse on time and discharge voltage the respectively. The model sufficiency is very satisfactory as the coefficientR2of is determination (R2) is found to these be greater than 98 %. These models can be used for selecting the values of process variables to get the desired

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50

Yusa Ali, Dego, Purnama Darmadji, and Yudi Pranoto. "OPTIMASI NANOENKAPSULASI ASAP CAIR TEMPURUNG KELAPA DENGAN RESPONSE SURFACE METHODOLOGY DAN KARAKTERISASI NANOKAPSUL." Jurnal Teknologi dan Industri Pangan 25, no. 1 (June 2014): 23–30. http://dx.doi.org/10.6066/jtip.2014.25.1.23.

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