Development of an implicit least squares optimisation scheme for the determination of Kihara potential parameters using gas hydrate equilibrium data

2003 ◽  
Vol 211 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Matthew A Clarke ◽  
P.R Bishnoi
2020 ◽  
Vol 45 (1) ◽  
pp. 39-58 ◽  
Author(s):  
Anupama Kumari ◽  
Shadman Hasan Khan ◽  
A. K. Misra ◽  
C. B. Majumder ◽  
Amit Arora

AbstractA fugacity-based thermodynamic model for hydrate has been used to determine the equilibrium pressures of hydrate formation. This fugacity-based model uses the PRSV equation of state, which is used to represent the gas phases in the hydrate. The parameters of the model are fitted to the experimental data of binary guest hydrates. The present study is aimed at investigating binary mixtures of {\text{CH}_{4}}–{\text{H}_{2}}S, {\text{C}_{3}}{\text{H}_{8}}–{\text{N}_{2}}, {\text{N}_{2}}–{\text{CO}_{2}}, {\text{CH}_{4}}–i-butane, {\text{C}_{3}}{\text{H}_{8}}–i-butane, {\text{CH}_{4}}–n-butane, {\text{C}_{3}}{\text{H}_{8}}–n-butane, i-butane–{\text{CO}_{2}}, and n-butane–{\text{CO}_{2}} hydrates, which have not been modeled before. Unlike previous studies, the Kihara potential parameters were obtained using the second virial coefficient correlation and the data of viscosity for gases. The fugacity-based model provides reasonably good predictions for most of the binary guest hydrates ({\text{CH}_{4}}–{\text{C}_{3}}{\text{H}_{8}}). However it does not yield good prediction for hydrates of ({\text{CO}_{2}}–{\text{C}_{3}}{\text{H}_{8}}). The transitions of hydrate structure from sI to sII and from sII to sI have been also predicted by this model for binary guest hydrates. The AAD % calculated using the experimental data of natural gas hydrates is only 10 %, which is much lower than the AAD % calculated for the equilibrium data predicted by the VdP-w model.


2020 ◽  
Vol 17 (1) ◽  
pp. 87-94
Author(s):  
Ibrahim A. Naguib ◽  
Fatma F. Abdallah ◽  
Aml A. Emam ◽  
Eglal A. Abdelaleem

: Quantitative determination of pyridostigmine bromide in the presence of its two related substances; impurity A and impurity B was considered as a case study to construct the comparison. Introduction: Novel manipulations of the well-known classical least squares multivariate calibration model were explained in detail as a comparative analytical study in this research work. In addition to the application of plain classical least squares model, two preprocessing steps were tried, where prior to modeling with classical least squares, first derivatization and orthogonal projection to latent structures were applied to produce two novel manipulations of the classical least square-based model. Moreover, spectral residual augmented classical least squares model is included in the present comparative study. Methods: 3 factor 4 level design was implemented constructing a training set of 16 mixtures with different concentrations of the studied components. To investigate the predictive ability of the studied models; a test set consisting of 9 mixtures was constructed. Results: The key performance indicator of this comparative study was the root mean square error of prediction for the independent test set mixtures, where it was found 1.367 when classical least squares applied with no preprocessing method, 1.352 when first derivative data was implemented, 0.2100 when orthogonal projection to latent structures preprocessing method was applied and 0.2747 when spectral residual augmented classical least squares was performed. Conclusion: Coupling of classical least squares model with orthogonal projection to latent structures preprocessing method produced significant improvement of the predictive ability of it.


2007 ◽  
Vol 90 (2) ◽  
pp. 391-404 ◽  
Author(s):  
Fadia H Metwally ◽  
Yasser S El-Saharty ◽  
Mohamed Refaat ◽  
Sonia Z El-Khateeb

Abstract New selective, precise, and accurate methods are described for the determination of a ternary mixture containing drotaverine hydrochloride (I), caffeine (II), and paracetamol (III). The first method uses the first (D1) and third (D3) derivative spectrophotometry at 331 and 315 nm for the determination of (I) and (III), respectively, without interference from (II). The second method depends on the simultaneous use of the first derivative of the ratio spectra (DD1) with measurement at 312.4 nm for determination of (I) using the spectrum of 40 μg/mL (III) as a divisor or measurement at 286.4 and 304 nm after using the spectrum of 4 μg/mL (I) as a divisor for the determination of (II) and (III), respectively. In the third method, the predictive abilities of the classical least-squares, principal component regression, and partial least-squares were examined for the simultaneous determination of the ternary mixture. The last method depends on thin-layer chromatography-densitometry after separation of the mixture on silica gel plates using ethyl acetatechloroformmethanol (16 + 3 + 1, v/v/v) as the mobile phase. The spots were scanned at 281, 272, and 248 nm for the determination of (I), (II), and (III), respectively. Regression analysis showed good correlation in the selected ranges with excellent percentage recoveries. The chemical variables affecting the analytical performance of the methodology were studied and optimized. The methods showed no significant interferences from excipients. Intraday and interday assay precision and accuracy values were within regulatory limits. The suggested procedures were checked using laboratory-prepared mixtures and were successfully applied for the analysis of their pharmaceutical preparations. The validity of the proposed methods was further assessed by applying a standard addition technique. The results obtained by applying the proposed methods were statistically analyzed and compared with those obtained by the manufacturer's method.


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