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Готові списки джерел за темами / RSM modelling / Статті в журналах

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Статті в журналах з теми "RSM modelling"

Автор: Grafiati

Опубліковано: 25 січня 2025

Оновлено: 31 липня 2025

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1

Nwosu-Obieogu, Kenechi, Maureen A. Allen, Chukwunonso Nwogu, Bertrand Nwankwojike, Simeon Bright, and Christian Goodnews. "Modelling and optimization of luffa oil transesterification via acid activated waste marble catalyst." Journal of the Ghana Institution of Engineering (JGhIE) 24, no. 1 (2024): 58–71. http://dx.doi.org/10.56049/jghie.v24i1.140.

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This study assessed the performance of response surface methodology (RSM) and artificial neural network (ANN) in modelling the transesterification of luffa oil using acid activated waste marble catalyst. The waste marble was activated with 0.5 molar sulphuric acid at 600 oC for 4 hours and was characterized by SEM, FT-IR, XRD, XRF, and BET; the characterization proved that the catalyst was successfully activated. The experiments were conducted at a catalyst dosage (1-5 wt. %), temperature (40-80 oC), methanol-oil ratio (4:1-12:1), time (1-3 hours), and agitation speed of (100- 500 rpm) with ou

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2

Nair, Abhilash T., Abhipsa R. Makwana, and M. Mansoor Ahammed. "The use of response surface methodology for modelling and analysis of water and wastewater treatment processes: a review." Water Science and Technology 69, no. 3 (2013): 464–78. http://dx.doi.org/10.2166/wst.2013.733.

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In recent years, response surface methodology (RSM) has been used for modelling and optimising a variety of water and wastewater treatment processes. RSM is a collection of mathematical and statistical techniques for building models, evaluating the effects of several variables, and obtaining the values of process variables that produce desirable values of the response. This paper reviews the recent information on the use of RSM in different water and wastewater treatment processes. The theoretical principles and steps for its application are first described. The recent investigations on its ap

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3

Irfan, Muhammad, Sharjeel Waqas, Ushtar Arshad, et al. "Response Surface Methodology and Artificial Neural Network Modelling of Membrane Rotating Biological Contactors for Wastewater Treatment." Materials 15, no. 5 (2022): 1932. http://dx.doi.org/10.3390/ma15051932.

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Membrane fouling is a major hindrance to widespread wastewater treatment applications. This study optimizes operating parameters in membrane rotating biological contactors (MRBC) for maximized membrane fouling through Response Surface Methodology (RSM) and an Artificial Neural Network (ANN). MRBC is an integrated system, embracing membrane filtration and conventional rotating biological contactor in one individual bioreactor. The filtration performance was optimized by exploiting the three parameters of disk rotational speed, membrane-to-disk gap, and organic loading rate. The results showed t

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4

Daramola, M. O., K. J. Keesman, and F. Spenkelink. "Process Modelling of Ultrafiltration Units: An RSM Approach." Journal of Applied Sciences 7, no. 23 (2007): 3687–95. http://dx.doi.org/10.3923/jas.2007.3687.3695.

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5

Narasimman, Pasupathi, K. Ravi, and Sandra Pinelas. "Modelling the Additive Functional Equations through RSM Matrices." JOURNAL OF ADVANCES IN MATHEMATICS 12, no. 10 (2016): 6714–19. http://dx.doi.org/10.24297/jam.v12i10.117.

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This paper suggests one possible method to model additive type of functional equations using eigenvalues and eigenvectors of matrices with suitable numerical examples. The authors have defined a new type of Row Sum Matrix(RSM) and have discussed its eigenvalues and eigenvectors in order to model functional equations. The famous additive cauchy functional equation and Logical functional equation have also been modelled using identity matrix and Logical matrix in this study.

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6

Eser, Aykut, Elmas Aşkar Ayyıldız, Mustafa Ayyıldız, and Fuat Kara. "Artificial Intelligence-Based Surface Roughness Estimation Modelling for Milling of AA6061 Alloy." Advances in Materials Science and Engineering 2021 (February 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/5576600.

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This study introduces the improvement of mathematical and predictive models of surface roughness parameter (Ra) in milling AA6061 alloy using carbide cutting tools coated with CVD-TiCN in dry condition. An experimental model has been improved for estimating the surface roughness using artificial neural networks (ANN) and response surface methodology (RSM). For these models, cutting speed, depth of cut, and feed rate were evaluated as input parameters for experimental design. For the ANN modelling, the standard backpropagation algorithm was established to be the optimum selection for training t

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7

Owolabi, Rasheed, Mohammed Usman, Adefunmilayo Anuoluwapo, and Onyekachi Oguamanam. "Modelling, Optimization and Green Metrics Evaluation of Bio-Catalytic Synthesis of Biodiesel." Tikrit Journal of Engineering Sciences 27, no. 3 (2020): 17–30. http://dx.doi.org/10.25130/tjes.27.3.03.

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The response surface methodology (RSM) was adopted in ths study to evaluate the influence, interplay and interaction of various process variables on the biodiesel yield using methanol and castor oil as feedstocks in the presence of bovine bones as bio-catalyst.Twenty experimental runs were designed using central composite design (CCD). RSM statistical model of second order was developed. Analysis of variance (ANOVA) tests were performed on the model to find the relative influence of the process variables. An optimum yield of 95.12% was obtained at 60 0C reaction temperature, 120 minutes reacti

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8

Hudák, Peter, and Valéria Hrabovcová. "Mathematical Modelling and Parameter Determination of Reluctance Synchronous Motor with Squirrel Cage." Journal of Electrical Engineering 61, no. 6 (2010): 357–64. http://dx.doi.org/10.2478/v10187-010-0055-y.

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Mathematical Modelling and Parameter Determination of Reluctance Synchronous Motor with Squirrel Cage The paper provides an analysis of reluctance synchronous motor (RSM) with asymmetrical rotor cage. Its performances during its starting up is investigated. A mathematical model is created on the basis of detailed investigation of model parameters. The RSM starting up by switching it directly across the line was simulated and verified by measurements.

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9

Gadallah, Mohamed H. "Process re-modelling using RSM and the splitting approach." International Journal of Mechatronics and Manufacturing Systems 3, no. 1/2 (2010): 58. http://dx.doi.org/10.1504/ijmms.2010.029875.

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10

Dullah, Salinah, Hidayati Asrah, Movierawanna Bernard, and Jane Ann Jumi. "Preliminary Modelling of Hydrological Performance for Green Roof Drainage Layer using Response Surface Methodology." Journal of Advanced Research in Applied Sciences and Engineering Technology 55, no. 1 (2024): 105–24. https://doi.org/10.37934/araset.55.1.105124.

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Response Surface Methodology modelling is used in this study to investigate experimental result for waterproofing and drainage layers with slope ranging from 0% to 6% test beds with three types layers of drainage, rubber crumbs, oil palm shells and polyform. The aim of this study is to determine the accuracy and effectiveness of RSM through investigating the hydrological performance of green roofs. Nine sets of experimental data were used to analyse, and the input parameters include type of material drainage layer, slopes, and water absorption of the materials. The output variables were hydrog

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11

Yaro, Aprael S., and Khalid H. Rashid. "Modelling and Optimization of Carbon Steel Corrosion in CO2 Containing Oilfield Produced Water in Presence of HAc." Iraqi Journal of Chemical and Petroleum Engineering 16, no. 2 (2015): 1–8. http://dx.doi.org/10.31699/ijcpe.2015.2.1.

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Previously, many empirical models have been used to predict corrosion rates under different CO2 corrosion parameters conditions. Most of these models did not predict the corrosion rate exactly, besides it determined effects of variables by holding some variables constant and changing the values of other variables to obtain the regression model. As a result the experiments will be large and cost too much. In this paper response surface methodology (RSM) was proposed to optimize the experiments and reduce the experimental running. The experiments studied effects of temperature (40 – 60 °C), pH (

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12

Leone, Claudio, Silvio Genna, and Vincenzo Tagliaferri. "An integrated approach for the modelling of silicon carbide components laser milling process." International Journal of Advanced Manufacturing Technology 116, no. 7-8 (2021): 2335–57. http://dx.doi.org/10.1007/s00170-021-07516-2.

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AbstractThe paper deals with characterisation and modelling of laser milling process on silicon carbide hard ceramic. To this end, a Yb:YAG pulsed fiber laser was adopted to mill silicon carbide bars. Square pockets, 5×5 mm2 in plane dimension, were machined at the maximum nominal average power (30W), under different laser process parameters: pulse frequency, scan speed, hatching distance, repetitions and scanning strategy. After machining, the achieved depth and the roughness parameters were measured by way of digital microscopy and 3D surface profiling, respectively. In addition, the materia

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13

Okewale, Akindele, Olusola Adesina, and Mustapha Oloko-Oba. "Comparative Study of Artificial Neural Network (ANN) and Response Surface Methodology (RSM) on Optimization of Ethanol Production from Sawdust." International Journal of Engineering Research in Africa 30 (May 2017): 125–33. http://dx.doi.org/10.4028/www.scientific.net/jera.30.125.

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This work focused on optimization of production of ethanol from saw dust using two empirical methods, the ANN and the RSM. It further investigated the modeling and optimization efficiencies of RSM and ANN in separate hydrolysis and fermentation of sawdust for ethanol production. Box - Behnken Design (BBD) was used to generate 17 individual experiments which were carried out, RSM and Genetic Algorithm (GA) of ANN which were used to optimize the production which was then compared. The optimum concentrations of ethanol yield predicted were 56.968 wt. % and 57. 387263 wt. % for RSM and ANN models

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14

Kahsin, Maciej. "Numerical Modelling of Structures with Uncertainties." Polish Maritime Research 24, s1 (2017): 125–32. http://dx.doi.org/10.1515/pomr-2017-0030.

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Abstract The nature of environmental interactions, as well as large dimensions and complex structure of marine offshore objects, make designing, building and operation of these objects a great challenge. This is the reason why a vast majority of investment cases of this type include structural analysis, performed using scaled laboratory models and complemented by extended computer simulations. The present paper focuses on FEM modelling of the offshore wind turbine supporting structure. Then problem is studied using the modal analysis, sensitivity analysis, as well as the design of experiment (

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15

Kupolusi, Kupolusi, Joseph A, Adedeji Adedeji, and Shalom Odunayo. "Modelling of Aerial Biomass and Its Physicochemical Properties Using Artificial Intelligence and Response Surface Methodology." Scholars Journal of Physics, Mathematics and Statistics 12, no. 03 (2025): 33–42. https://doi.org/10.36347/sjpms.2025.v12i03.001.

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Aerial biomass and its associated physicochemical properties are pivotal components in understanding ecosystem dynamics, with far-reaching implications for environmental and agricultural management. This study delves into the dynamics of aerial biomass and its correlation with physicochemical properties, utilizing a dataset derived from research on Spartina alterniflora in the Cape Fear Estuary of North Carolina. Machine learning (ML) models, including Response Surface Methodology (RSM), the Quadratic Model, Artificial Neural Networks (ANN), and the Adaptive Neuro-Fuzzy Inference System (ANFIS

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16

Rezk, Hegazy, A. G. Olabi, Mohammad Ali Abdelkareem, Hussein M. Maghrabie, and Enas Taha Sayed. "Fuzzy Modelling and Optimization of Yeast-MFC for Simultaneous Wastewater Treatment and Electrical Energy Production." Sustainability 15, no. 3 (2023): 1878. http://dx.doi.org/10.3390/su15031878.

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Microbial fuel cells convert the chemical energy conserved in organic matter in wastewater directly to electrical energy through living microorganisms. These devices are environmentally friendly thanks to their ability to simultaneously produce electrical energy and wastewater treatment. The output power of the yeast microbial fuel cell (YMFC) depends mainly on glucose concentration and glucose/yeast ratio. Thus, the paper aims to boost the power of YMFC by identifying the best values of glucose concentration and glucose/yeast ratio. The suggested approach comprises fuzzy modelling and optimiz

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17

Hassan Nejad, H., S. Shafiei Zadeh, and S. Alam. "Modelling of platinum extraction by Aliquat 336 utilising RSM technique." Canadian Metallurgical Quarterly 52, no. 4 (2013): 342–47. http://dx.doi.org/10.1179/1879139513y.0000000067.

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18

Grbatinić, Ivan, Nemanja Rajković, and Nebojša Milošević. "Computational RSM modelling of dentate nucleus neuron 2D image surface." Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 6, no. 1 (2016): 43–50. http://dx.doi.org/10.1080/21681163.2016.1160798.

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19

Nalbur, Berrak Erol, Arzu Teksoy, Seval Kutlu Akal Solmaz, and Hilal Safiye Azak. "Modelling Dimethoate Removal by Fenton-Like Process Using Response Surface Methodology." Proceedings 2, no. 11 (2018): 649. http://dx.doi.org/10.3390/proceedings2110649.

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The (RSM) is a useful method for optimizing analytical methods and it has been applied to evaluate independent variables in FPs. In this study, the removal of dimethoate (DMT) which is a commonly used pesticide and has a toxic effect on the environment, was evaluated in terms of oxidation and mineralization efficiency using response surface methodology (RSM) in the Fenton-like process (FLP). The obtained optimum conditions for DMT oxidation and mineralization using the FLP included DMT/Fe+3/H2O2 ratio of 0.018 mM/0.03 mM/0.15 mM and reaction time of 65 min. DMT oxidation efficiency was 78% and

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20

Fathy, Ahmed, Hegazy Rezk, Dalia Yousri, Abdullah G. Alharbi, Sulaiman Alshammari, and Yahia B. Hassan. "Maximizing Bio-Hydrogen Production from an Innovative Microbial Electrolysis Cell Using Artificial Intelligence." Sustainability 15, no. 4 (2023): 3730. http://dx.doi.org/10.3390/su15043730.

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In this research work, the best operating conditions of microbial electrolysis cells (MECs) were identified using artificial intelligence and modern optimization. MECs are innovative materials that can be used for simultaneous wastewater treatment and bio-hydrogen production. The main objective is the maximization of bio-hydrogen production during the wastewater treatment process by MECs. The suggested strategy contains two main stages: modelling and optimal parameter identification. Firstly, using adaptive neuro-Fuzzy inference system (ANFIS) modelling, an accurate model of the MES was create

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21

Yıkmış, Seydi, Filiz Aksu, Sema Sandıkçı Altunatmaz, and Başak Gökçe Çöl. "Ultrasound Processing of Vinegar: Modelling the Impact on Bioactives and Other Quality Factors." Foods 10, no. 8 (2021): 1703. http://dx.doi.org/10.3390/foods10081703.

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In recent years, non-thermal technology has been used for the enrichment of ultrasound bioactive components. For this purpose, it was applied to tomato vinegar and modeled with response surface methodology (RSM) and artificial neural network (ANN). At the end of the RSM, cupric reducing antioxidant capacity (68.64%), 1,1-diphenyl-2-picrylhydrazyl (62.47%), total flavonoid content (2.44 mg CE/mL), total phenolic content (12.22 mg GAE/mL), total ascorbic acid content (2.53 mg/100 mL) and total lycopene (5.44 μg/mL) were determined. The ANN model has higher prediction accuracy than RSM. The micro

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22

Mangesh Dadarao Shende. "RSM and ANN Modeling Techniques to Forecast How Various Parameters will Affect the Improvement of Electronics Cooling using Radial Heat Sink." Advances in Nonlinear Variational Inequalities 27, no. 2 (2024): 650–62. http://dx.doi.org/10.52783/anvi.v27.1352.

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This research provides the mathematical modeling for temperature difference for natural convection using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) based modelling. Length of fin (L), height of fin (H), number of fins (N) and the heat input (Q) for the Radial heat sink are the parameters selected under natural convection heat transfer. Looking at the pattern of the data, feed forward back propagation type neural network is chosen. The RSM mathematical model of temperature difference is used to compare the performance of the created ANN models. ANN Simulations proved

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23

Doraisamy, Amrishraj, Thiyagarajan Senthilvelan, and S. Sampath Kumar. "Empirical Modelling and Optimization of Sliding Wear Behaviour of Copper-Graphite Composites Using RSM." Applied Mechanics and Materials 592-594 (July 2014): 260–68. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.260.

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Copper-Graphite composites have been prepared through powder metallurgy (P/M) method. 0 3 and 6 wt % of graphite particles have been added as the reinforcement to the Copper powder which forms the matrix and composites have been prepared. Microstructure of the newly prepared composites was analyzed using Scanning Electron Microscopy (SEM). Wear test was done using Pin-on-disc tribometer according to G99 standards. A linear regression Mathematical model has been developed using RSM to predict the sliding wear behavior of the composites. Optimization has been done using RSM and also based on ANO

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24

Yamin, Jehad A. A. "Response Surface Modelling of Diesel Engine Emissions under Variable Stroke Length and Constant Compression Ratio." Modern Applied Science 12, no. 10 (2018): 36. http://dx.doi.org/10.5539/mas.v12n10p36.

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A theoretical investigation using RSM statistical technique on the relative change of emissions of a four-stroke, direct injection, water-cooled, 4-stroke, diesel engine with variable stroke length was carried out.&nbsp; The performance parameters were studied over wide range of speeds (1000 - 3000 RPM at an increment of 500 RPM) and stroke lengths (130 mm to 210mm at an increment of 20mm). The compression ratio was kept constant by adjusting the piston bowl volume. It was found within the range of stroke length studied, that larger stroke lengths are favorable for lower NOx and specific C

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25

Deng, Zhao Hui, Lin Lin Wan, Xiao Hong Zhang, and Sheng Chao Li. "Modelling the Processing Parameters of Rotary Curved Surface Grinding Using RSM." Advanced Materials Research 338 (September 2011): 130–35. http://dx.doi.org/10.4028/www.scientific.net/amr.338.130.

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The NC grinding of Si3N4 ceramics rotary curved surface workpieces was carried on the CNC jig grinders, combining the nomal tracing grinding and the arc envelope forming grinding. According to the grinding track, a grinding surface scallop height model was built. The model analysis indicated that workpiece curvature, wheel radius and feed rate affected the surface roughness. A prediction model based on the response surface methodology (RSM) was built to study the influences of these processing parameters on the surface roughness, using the Box-Behnken design to design the grinding experiments.

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26

Kundu, R. R., and B. N. Lahiri. "Study and statistical modelling of Green Sand Mould properties using RSM." International Journal of Materials and Product Technology 31, no. 2/3/4 (2008): 143. http://dx.doi.org/10.1504/ijmpt.2008.018016.

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27

Vates, Umesh Kumar, Nand Jee Kanu, Eva Gupta, Gyanendra Kumar Singh, Naveen Anand Daniel, and Bhupendra Prakash Sharma. "Optimization of FDM 3D Printing Process Parameters on ABS based Bone Hammer using RSM Technique." IOP Conference Series: Materials Science and Engineering 1206, no. 1 (2021): 012001. http://dx.doi.org/10.1088/1757-899x/1206/1/012001.

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Abstract Rapid prototyping (RP) uses a cycle where a real model is made by explicitly adding material as thin cross-sectional layers. Fused deposition modelling (FDM) 3D printer is being use for synthesis of ABS based bone hammer. Response surface methodology (RSM) based L27 design of experiment were adopted to perform the experiment using four influencing parameters such as layer thickness, infill percentage, orientation and nozzle temperature for the three responses deflection, hardness and weight. Response surface methodology was used for modelling and optimization of considered process par

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28

Reddy Paturi, Uma Maheshwera, Konidhala Nandan, Nudurupati Achintya Vamshi, Omkar Sunil Sahasra Bhojane, Goturi Sheshank Reddy, and N. S. Reddy. "Multi-objective parametric modelling during minimum quantity lubrication machining of Incoloy 800H." Journal of Physics: Conference Series 2837, no. 1 (2024): 012064. http://dx.doi.org/10.1088/1742-6596/2837/1/012064.

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Abstract This study utilizes multi-objective optimization to minimize surface roughness and maximize material removal rate (MRR) during minimum quantity lubrication (MQL) turning of Incoloy 800H under different cutting conditions. The correlations among process conditions are examined using response surface methodology (RSM) and the desirability function. The obtained optimal values for the cutting parameters are as follows: 125 m/min cutting speed, 0.1 mm/rev feed rate, and 0.05 mm depth of cut. The predicted surface roughness and MRR were 0.585 µm and 4377.932 mm3/min, respectively. A correl

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29

Reddy Paturi, Uma Maheshwera, Omkar Sunil Sahasra Bhojane, Goturi Sheshank Reddy, Nudurupati Achintya Vamshi, Konidhala Nandan, and N. S. Reddy. "Multi-objective parametric modelling during wire-cut electric discharge machining of Incoloy 800H." Journal of Physics: Conference Series 2837, no. 1 (2024): 012077. http://dx.doi.org/10.1088/1742-6596/2837/1/012077.

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Abstract Incoloy 800H exhibits exceptional resistance to corrosion in aqueous environments and demonstrates a strong resistance to chloride stress-corrosion cracking. In this study, a multi-objective parametric optimization technique is used to model and optimize the process inputs and the response parameters during wire electrical discharge machining (WEDM) of Incoloy 800H. Statistical techniques, response surface methodology (RSM) and analysis of variance (ANOVA) were employed for this purpose. The correlation coefficient is used to determine the accuracy of statistical model predictions bas

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30

Jamil Hosni, Nor Ain Binti, Mohd Amri Bin Lajis, and Muhammad Ridzuan Bin Idris. "Modelling and optimization of Chromium Powder Mixed EDM Parameter Effect Over the Surface Characteristics by Response Surface Methodology Approach." International Journal of Engineering Materials and Manufacture 3, no. 2 (2018): 78–86. http://dx.doi.org/10.26776/ijemm.03.02.2018.02.

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In this paper, an optimization of chromium powder mixed parameters effect, i.e. discharge current, pulse on time and Cr powder concentration of AISI D2 steels in Powder Mixed EDM (PMEDM) has been made. RSM has been employed to plan and analyzed the experiment. Central composite design (CCD) was chosen as the RSM design that is useful for investigating the quadratic effects. The version 8.0 of the Design Expert software was used to develop the experimental plan for RSM. A mathematical model in the form of the multiple regression equation for second order response surface with the best fittings

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31

Ghorbani, Mehdi, Aghil Ghorbani, Mansoor Omidi, and Seyed Mohammad Hashemi. "Response Surface Modelling of Noradrenaline Production in Hairy Root Culture of Purslane (Portulaca oleracea L.)." Turkish Journal of Agriculture - Food Science and Technology 3, no. 6 (2015): 349. http://dx.doi.org/10.24925/turjaf.v3i6.349-443.320.

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Common purslane (Portulaca oleracea L.) is an annual plant as one of the natural sources for noradrenaline hormone. In this research, hairy root culture of purslane was established by using Agrobacterium rhizogenes strain ATCC 15834. In the following, Box-Behnken model of response surface methodology (RSM) was employed to optimize B5 medium for the growth of P. oleracea L. hairy root line. According to the results, modelling and optimization conditions, including sucrose, CaCl2.H2O, H2PO4 and NO3-/NH4+ concentrations on maximum dry weight (0.155 g) and noradrenaline content (0.36 mg.g-1 DW) wa

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32

Nwose, Sebastian Azowenu, Francis Odikpo Edoziuno, and Sylvester O. Osuji. "Statistical analysis and Response Surface Modelling of the compressive strength inhibition of crude oil in concrete test cubes." Algerian Journal of Engineering and Technology 4 (April 16, 2021): 99–107. https://doi.org/10.5281/zenodo.4696030.

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The use of crude oil contaminated fine aggregates in the production of concrete significantly affect the properties of such concrete, especially the compressive strength. In the present investigation, response surface methodology (RSM) of the Design-Expert software version 11.1.0.1 was used for the statistical analysis and predictive modelling of the compressive strength of concrete cubes made from crude oil contaminated fine aggregates at 7, 14, 28, and 56 days curing periods. The fine aggregates were mixed with varying concentrations of crude oil contamination (ranging from 0% to 5% by weigh

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Shu, Dun Tao, Yan Ling He, Qing Yi Wang, and Wang Li. "Optimization and Modelling of Denitrification and Methanogenic Activity in Start up of Mixotrophic Anammox Reactor." Advanced Materials Research 1073-1076 (December 2014): 127–35. http://dx.doi.org/10.4028/www.scientific.net/amr.1073-1076.127.

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In the present study, the SDA (specific denitrification activity) and SMA (specific methanogenic activity) in Start up of mixotrophic anammox reactor was optimized by applying the response surface method (RSM). The purpose of this work was to find the optimal combination of C/N ratio, influent ammonium (NH4+-N) and volatile suspended solid (VSS) with respect to minmum the SDA and SMA. Based on the RSM results, the quadratic model developed for the responses indicated that optimal conditions were C/N ratio of 0.5, influent NH4+-N content of 200mg L-1, and VSS content of 59.31g L-1. Under this c

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Kristianto, Y., W. Wignyanto, B. D. Argo, and I. Santoso. "Antioxidant increase by response surface optimization and Bayesian neural network modelling of pumpkin (Cucurbita moschata Duch) freezing." Food Research 5, no. 3 (2021): 73–82. http://dx.doi.org/10.26656/fr.2017.5(3).598.

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Pumpkin antioxidants have been found to benefit diabetics. This current study was attempted to optimize slow freezing treatment for a pumpkin to obtain maximum antioxidant gain using response surface methodology (RSM) and Bayesian regularized neural network (BRANN) approaches. A central composite design was used to generate the freezing experiment and to examine response change as a function of temperature and freezing time. Feedforward neural networks with a 2-15-1 structure were developed and trained using the Bayesian regularization algorithm. The results showed that the freezing data were

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Sentyabov, A. V., D. V. Platonov, A. V. Minakov, and A. S. Lobasov. "Numerical study of the vortex breakdown and vortex reconnection in the flow path of high-pressure water turbine." Journal of Physics: Conference Series 2088, no. 1 (2021): 012040. http://dx.doi.org/10.1088/1742-6596/2088/1/012040.

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Abstract The paper presents a study of the instability of the precessing vortex core in the model of the draft tube of a hydraulic turbine. The study was carried out using numerical modeling using various approaches: URANS, RSM, LES. The best agreement with the experimental data was shown by the RSM and LES methods with the modelling of the runner rotation by the sliding mesh method. In the regime under consideration, the precessing vortex rope is subject to instability, which leads to reconnection of its turns and the formation of an isolated vortex ring. Reconnection of the vortex core leads

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Vitas, Jasmina. "ANN and RSM modelling of antioxidant characteristics of kombucha fermented milk beverages with peppermint." Mljekarstvo 68, no. 2 (2018): 116–25. http://dx.doi.org/10.15567/mljekarstvo.2018.0205.

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Antioxidant activity to stable DPPH radical (AADPPH) and unstable hydroxyl radicals (AA.OH) and nutraceuticals (monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs) and ascorbic acid) content of kombucha fermented milks with peppermint (KFM-P) were modelled and optimised. Beverages were produced by the addition of 10 % of kombucha peppermint inoculum to the milk containing 0.8, 1.6 and 2.8 % milk fat at 37, 40 and 43 °C. Response surface methodology (RSM) indicated opposite response surfaces for AADPPH and AA.OH PUFAs and ascorbic acid, as most significant and influential f

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Anantha Padmanabha, E., P. Shashivardhan Reddy, B. Narender, S. Muralikrishnan, and V. K. Dadhwal. "Photogrammetric processing of hexagon stereo data for change detection studies." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8 (November 27, 2014): 151–57. http://dx.doi.org/10.5194/isprsannals-ii-8-151-2014.

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Hexagon satellite data acquired as a part of USA Corona program has been declassified and is accessible to general public. This image data was acquired in high resolution much before the launch of civilian satellites. However the non availability of interior and exterior orientation parameters is the main bottle neck in photogrammetric processing of this data. In the present study, an attempt was made to orient and adjust Hexagon stereo pair through Rigorous Sensor Model (RSM) and Rational Function Models (RFM). The study area is part of Western Ghats in India. For rigorous sensor modelling an

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Jenarthanan, M. P., A. Ajay Subramanian, and R. Jeyapaul. "Comparative analysis of surface roughness prediction using DOE and ANN techniques during endmilling of glass fibre reinforced polymer (GFRP) composites." Pigment & Resin Technology 45, no. 2 (2016): 126–39. http://dx.doi.org/10.1108/prt-03-2015-0026.

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Purpose – This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface roughness during endmilling of glass-fibre-reinforced polymer composites. Design/methodology/approach – Aiming to achieve this goal, several milling experiments were performed with polycrystalline diamond inserts at different machining parameters, namely, feed rate, cutting speed, depth of cut and fibre orientation angle. Mathematical model is created using central composite face-centred second-order in RSM and the adequac

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Hossain, Md Shahriar Jahan, and Nafis Ahmad. "Surface roughness prediction modelling for commercial dies using ANFIS, ANN and RSM." International Journal of Industrial and Systems Engineering 16, no. 2 (2014): 156. http://dx.doi.org/10.1504/ijise.2014.058834.

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Reddy, P. Venkateshwar, B. Veerabhadra Reddy, and P. Janaki Ramulu. "Mathematical modelling for prediction of tube hydroforming process using RSM and ANN." International Journal of Industrial and Systems Engineering 35, no. 1 (2020): 13. http://dx.doi.org/10.1504/ijise.2020.106848.

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Danso-Boateng, Eric, Melissa Fitzsimmons, Andrew B. Ross, and Ted Mariner. "Response Surface Modelling of Methylene Blue Adsorption onto Seaweed, Coconut Shell and Oak Wood Hydrochars." Water 15, no. 5 (2023): 977. http://dx.doi.org/10.3390/w15050977.

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Adsorption of methylene blue (MB) dye from an aqueous solution onto hydrochars produced from brown seaweed (Fucus Serratus) (FS-HC), coconut shell (CS-HC), and oak wood (Oak-HC) at different temperatures (200–250 °C) was investigated in a batch system. Response surface modelling (RSM) was used to investigate the effect of initial MB concentration (50–300 mg/L), contact time (0–240 min), and solution pH (2–12) on the adsorption process. RSM was also used to model and optimise these parameters for efficient adsorption. Kinetic and isotherms studies were carried out to study the adsorption mechan

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Pachiyappan, Jayakaran, Gnanasundaram Nirmala, Selvaraju Sivamani, et al. "Biogenic Synthesis, Characterization, and Photocatalytic Evaluation of Pristine and Graphene-Loaded Zn50Mg50O Nanocomposites for Organic Dyes Removal." Nanomaterials 12, no. 16 (2022): 2809. http://dx.doi.org/10.3390/nano12162809.

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Algal biomass synthesised nanocomposites have a higher surface area and reusability advantages. This study aimed to synthesise and characterise ZnMgO and silica-supported graphene with ZnMgO (G-ZnMgO) nanocomposites from Kappaphycusalvarezii and evaluate their potential in the application of photocatalysis to remove Rhodamine-B (RhB) and methylene blue (MB) dyes from their aqueous medium by maximising the percentage removal using response surface methodology (RSM) modelling. Nanocomposites were synthesised and characterised by biogenic and instrumental (Powder X-ray diffraction (P-XRD), electr

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Barışçı, Sibel, and Ozge Turkay. "Optimization and modelling using the response surface methodology (RSM) for ciprofloxacin removal by electrocoagulation." Water Science and Technology 73, no. 7 (2015): 1673–79. http://dx.doi.org/10.2166/wst.2015.649.

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In this study, response surface methodology (RSM) was used to investigate the effects of different operating conditions on the removal of ciprofloxacin (CIP) by the electrocoagulation (EC) with pure iron electrodes. Box-Behnken design was used for the optimization of the EC process and to evaluate the effects and interactions of process variables such as applied current density, process time, initial CIP concentration and pH on the removal of CIP by the EC process. The optimum conditions for maximum CIP removal (86.6%) were found as pH = 4; Co = 5 mg.L1−; Id = 4.325 mA.cm2−; tprocess = 10 min.

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Panneerselvam, K., and Kasirajan Lenin. "Parameters optimization in FSW of polypropylene based on RSM." Multidiscipline Modeling in Materials and Structures 11, no. 1 (2015): 32–42. http://dx.doi.org/10.1108/mmms-07-2013-0048.

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Purpose – The purpose of this paper is to weld polypropylene (PP) material by friction stir welding (FSW) process. The input process parameters considered were: tool pin profile, feed rate and tool rotational speed and the process output characteristics were tensile strength, Shore-D hardness, Rockwell hardness, Izod strength, Charpy strength and nugget area. Design/methodology/approach – Optimization of process parameters were carried out based on response surface methodology (RSM) and significant parameters were obtained by performing analysis of variance (ANOVA). Findings – The optimized re

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Maalihan, Reymark D. "Modelling the Toughness of Nanostructured Polyhedral Oligomeric Silsesquioxane Composites Fabricated by Stereolithography 3D Printing: A Response Surface Methodology and Artificial Neural Network Approach." Materials Science Forum 1053 (February 17, 2022): 41–46. http://dx.doi.org/10.4028/p-6s4jp4.

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In this study, stereolithography (SLA) 3D printing was used to prepare toughened composites by facile blending of chemically compatible nanoscale polyhedral oligomeric silsesquioxanes (POSS) to commercial photoreactive resin. Due to the complex nature of 3D printing, the mechanical performance of the final parts cannot be simply determined or even estimated until they are manufactured and tested. Thus, response surface methodology (RSM) and artificial neural network (ANN) were used to build regression models for determining the toughness of fabricated composites as function of toughener (POSS)

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Fourati, Mariam, Slim Smaoui, Karim Ennouri, et al. "Multiresponse Optimization of Pomegranate Peel Extraction by Statistical versus Artificial Intelligence: Predictive Approach for Foodborne Bacterial Pathogen Inactivation." Evidence-Based Complementary and Alternative Medicine 2019 (October 13, 2019): 1–18. http://dx.doi.org/10.1155/2019/1542615.

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Pomegranate (Punica granatum L.) peel is a potential source of polyphenols known for their activity against foodborne pathogen bacteria. In this study, the effects of pomegranate peel extraction time (10–60 min), agitation speed (120–180 rpm), and solvent/solid ratio (10–30) on phytochemical content and antibacterial activity were determined. Response surface methodology (RSM) and artificial neural network (ANN) methods were used, respectively, for multiresponse optimization and predictive modelling. Compared with the original conditions, the total phenolic content (TPC), the total flavonoid c

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47

Soomro, Shakeel Ahmed, Kunjie Chen, and Sohail Ahmed Soomro. "Mathematical Modelling and Optimisation of Low-Temperature Drying on Quality Aspects of Rough Rice." Journal of Food Quality 2020 (January 25, 2020): 1–10. http://dx.doi.org/10.1155/2020/6501257.

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Rice when harvested normally has a high moisture content of 20–25% which requires immediate drying, reducing its mass loss and preventing it to spoil. This situation is more crucial with the areas under humid tropical conditions, where moisture and temperature mainly play an important role in deteriorating the quality of rough rice. Keeping the importance of quality attributes of rough rice, the study was carried out to assess the effects of low-temperature drying and suggest an optimum condition. Response surface methodology (RSM) with a central composite design was employed to study the effe

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Lin, Weiyun, Liang Jing, and Baiyu Zhang. "Micellar-Enhanced Ultrafiltration to Remove Nickel Ions: A Response Surface Method and Artificial Neural Network Optimization." Water 12, no. 5 (2020): 1269. http://dx.doi.org/10.3390/w12051269.

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Nickel ions from aqueous solutions were removed by micellar-enhanced ultrafiltration (MEUF), using the surfactant sodium dodecyl sulfate (SDS) as a chelating agent. Process variables and indicators were modeled and optimized by a response surface methodology (RSM), using the Box–Behnken design (BBD). The generated quadratic models described the relationship between a performance indicator (nickel rejection rate or permeate flux) and process variables (pressure, nickel concentration, SDS concentration, and molecular weight cut-off (MWCO)). The analysis of variance (ANOVA) showed that both model

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Yeo, J. S., S. Koting, C. C. Onn, and K. H. Mo. "Optimisation of mix design of concrete paving block using response surface methodology." Journal of Physics: Conference Series 2521, no. 1 (2023): 012012. http://dx.doi.org/10.1088/1742-6596/2521/1/012012.

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Abstract This study investigated the optimal water/binder (w/b) and aggregate/binder (a/b) ratios in producing a concrete paving block. The w/b and a/b ratios in the concrete paving block were optimised using the response surface methodology (RSM), considering the performances of the ultrasonic pulse velocity (UPV), flexural, and compressive strengths. Regression modelling was conducted to represent the relationships between the UPV and compressive strength and the compressive and flexural strengths. Generally, the UPV, flexural, and compressive strengths increased with the increment of w/b ra

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O.U.Osazuwa;, E.I. Ehiawaguan G.J. Obiuwevbi and A.N. Amenaghawon. "Bio-Inspired Hydroxyapatite-Chitosan Composite for Enhanced Indigo Blue Dye Removal: Kinetic and Adsorption Optimization Study." Journal of Energy Technology and Environment 6, no. 4 (2024): 15–28. https://doi.org/10.5281/zenodo.14523041.

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<em>The presence of dye molecules in water has a number of negative effects on aquatic and terrestrial animals. This study aimed to synthesize and characterize a composite of hydroxyapatite and chitosan to adsorb Indigo Blue (IB) dye from water, and to optimize its use for the adsorption process using the Response Surface Methodology (RSM) modelling tool. The combination of hydroxyapatite obtained from goat bone and chitosan obtained from periwinkle shell was carried out to enhance the mechanical strength and removal efficiency of the adsorbent. The formulated adsorbent was characterized using

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