Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity
Abstract Herein, multivariate Lagrange's interpolation polynomial (MLIP) and multivariate least square (MLS) methods are used to derive linear and higher‐order polynomials for two varied applications. (1) For an effective fabrication of Pectin degrading Fe3O4‐SiO2 Nanobiocatalyst activity (IU/m...
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Wiley
2021-04-01
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| Series: | IET Nanobiotechnology |
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| Online Access: | https://doi.org/10.1049/nbt2.12034 |
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| author | Boopathi Muthusamy Sujatha Ramalingam Senthil Kumar Chandran Sathish Kumar Kannaiyan |
| author_facet | Boopathi Muthusamy Sujatha Ramalingam Senthil Kumar Chandran Sathish Kumar Kannaiyan |
| author_sort | Boopathi Muthusamy |
| collection | DOAJ |
| description | Abstract Herein, multivariate Lagrange's interpolation polynomial (MLIP) and multivariate least square (MLS) methods are used to derive linear and higher‐order polynomials for two varied applications. (1) For an effective fabrication of Pectin degrading Fe3O4‐SiO2 Nanobiocatalyst activity (IU/mg). Here, the three parameters namely: pH value, pectinase loading and temperature as independent variables are optimized for the maximal of anobiocatalyst activity as a dependent variable. (2) For a passive system reliability estimation of decay heat removal (DHR) of a nuclear power plant. The success criteria of the system depend on three types temperature that do not exceed their respective design safety limits and are considered as dependent variables and 14 significant parameters were used as independent variables. Statistically, the validation of these multivariate polynomials are done by testing of hypothesis. Comparative study of the proposed approach gives significance results in the first application have the optimum conditions for maximum activity using linear MLIP method is: 58.64 with pH = 4, pL = 250 and Temp = 4°C. The maximum activity using second order MLIP method is 59.825 and method of MLS is 59.8249 with the optimized values of an independent variables pH = 4, pL = 300 and Temp = 8°C depicted in Table 1. In DHR system, the significance results are obtained and depicted in Table 2. |
| format | Article |
| id | doaj-art-d98ab399cf954b00bdf00177ea865d06 |
| institution | Kabale University |
| issn | 1751-8741 1751-875X |
| language | English |
| publishDate | 2021-04-01 |
| publisher | Wiley |
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| series | IET Nanobiotechnology |
| spelling | doaj-art-d98ab399cf954b00bdf00177ea865d062025-02-03T06:47:18ZengWileyIET Nanobiotechnology1751-87411751-875X2021-04-0115217319610.1049/nbt2.12034Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activityBoopathi Muthusamy0Sujatha Ramalingam1Senthil Kumar Chandran2Sathish Kumar Kannaiyan3Department of Mathematics Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Kancheepuram IndiaDepartment of Mathematics Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Kancheepuram IndiaSouthern Regional Regulatory Centre Atomic Energy Regulatory Board Chennai IndiaDepartment of Chemical Engineering Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Kancheepuram IndiaAbstract Herein, multivariate Lagrange's interpolation polynomial (MLIP) and multivariate least square (MLS) methods are used to derive linear and higher‐order polynomials for two varied applications. (1) For an effective fabrication of Pectin degrading Fe3O4‐SiO2 Nanobiocatalyst activity (IU/mg). Here, the three parameters namely: pH value, pectinase loading and temperature as independent variables are optimized for the maximal of anobiocatalyst activity as a dependent variable. (2) For a passive system reliability estimation of decay heat removal (DHR) of a nuclear power plant. The success criteria of the system depend on three types temperature that do not exceed their respective design safety limits and are considered as dependent variables and 14 significant parameters were used as independent variables. Statistically, the validation of these multivariate polynomials are done by testing of hypothesis. Comparative study of the proposed approach gives significance results in the first application have the optimum conditions for maximum activity using linear MLIP method is: 58.64 with pH = 4, pL = 250 and Temp = 4°C. The maximum activity using second order MLIP method is 59.825 and method of MLS is 59.8249 with the optimized values of an independent variables pH = 4, pL = 300 and Temp = 8°C depicted in Table 1. In DHR system, the significance results are obtained and depicted in Table 2.https://doi.org/10.1049/nbt2.12034interpolationleast squares approximationsnanobiotechnologypolynomials |
| spellingShingle | Boopathi Muthusamy Sujatha Ramalingam Senthil Kumar Chandran Sathish Kumar Kannaiyan Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity IET Nanobiotechnology interpolation least squares approximations nanobiotechnology polynomials |
| title | Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity |
| title_full | Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity |
| title_fullStr | Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity |
| title_full_unstemmed | Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity |
| title_short | Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity |
| title_sort | multivariate polynomial fit decay heat removal system and pectin degrading fe3o4 sio2 nanobiocatalyst activity |
| topic | interpolation least squares approximations nanobiotechnology polynomials |
| url | https://doi.org/10.1049/nbt2.12034 |
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