On the Importance of Choosing the Best Minimization Algorithm for the Determination of Ternary Diffusion Coefficients by the Taylor Dispersion Method
| Autor: | Martino Di Serio, Riccardo Tesser, Ornella Ortona, Vincenzo Russo, Luigi Paduano |
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| Přispěvatelé: | Russo, Vincenzo, Ortona, Ornella, Tesser, Riccardo, Paduano, Luigi, Di Serio, Martino |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
010405 organic chemistry Estimation theory General Chemical Engineering Taylor dispersion Experimental data 02 engineering and technology General Chemistry 01 natural sciences Article 0104 chemical sciences lcsh:Chemistry lcsh:QD1-999 020401 chemical engineering Multicomponent systems Minimization algorithm Applied mathematics 0204 chemical engineering Diffusion (business) Ternary operation MATLAB computer Mathematics computer.programming_language |
| Zdroj: | ACS Omega ACS Omega, Vol 2, Iss 6, Pp 2945-2952 (2017) |
| ISSN: | 2470-1343 |
| Popis: | Taylor dispersion method is a common technique for the determination of diffusion coefficients in the case of multicomponent systems. One of the main problems related to the parameter estimation analysis of the collected results is the choice of the best minimization algorithm that allows finding the real minimum of the objective function. Usually, researchers use the Levenberg–Marquardt algorithm, averaging the parameters obtained by different estimation analyses. In this paper, some nonlinear minimization algorithms included in MATLAB R2016a have been tested, and the results are compared in terms of best fit on the experimental data collected for sodium dodecyl sulfate (SDS) + sodium octanoate (SOC) + water system. |
| Databáze: | OpenAIRE |
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