Hydrates of Binary Guest Mixtures: Fugacity Model Development and Experimental Validation

2020 ◽  
Vol 45 (1) ◽  
pp. 39-58 ◽  
Author(s):  
Anupama Kumari ◽  
Shadman Hasan Khan ◽  
A. K. Misra ◽  
C. B. Majumder ◽  
Amit Arora
Keyword(s):  
Experimental Data ◽  
Model Development ◽  
Second Virial Coefficient ◽  
Hydrate Formation ◽  
Good Prediction ◽  
Gas Phases ◽  
Kihara Potential ◽  
Coefficient Corrélation ◽  
Equilibrium Data ◽  
Potential Parameters

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.

Parameters of the Bender Equation of State for Chloro Derivatives of Methane and Chlorobenzene

2001 ◽  
Vol 66 (6) ◽  
pp. 833-854 ◽  
Author(s):  
Ivan Cibulka ◽  
Lubomír Hnědkovský ◽  
Květoslav Růžička
Keyword(s):  
Experimental Data ◽  
Equation Of State ◽  
Virial Coefficient ◽  
Second Virial Coefficient ◽  
Virial Coefficients ◽  
Liquid Equilibrium ◽  
Second Virial Coefficients ◽  
Equilibrium Data ◽  
State Behaviour ◽  
Derivatives Of

Values of adjustable parameters of the Bender equation of state evaluated for chloromethane, dichloromethane, trichloromethane, tetrachloromethane, and chlorobenzene from published experimental data are presented. Experimental data employed in the evaluation included the data on state behaviour (p-ρ-T) of fluid phases, vapour-liquid equilibrium data (saturated vapour pressures and orthobaric densities), second virial coefficients, and the coordinates of the gas-liquid critical point. The description of second virial coefficient by the equation of state is examined.

Isothermal and isobaric vapour-liquid equilibrium data in the tetrachloromethane-sec-butyl alcohol system

1983 ◽  
Vol 48 (9) ◽  
pp. 2446-2453 ◽  
Author(s):  
Jan Linek
Keyword(s):  
Experimental Data ◽  
Boiling Point ◽  
Butyl Alcohol ◽  
Correlation Equations ◽  
Wilson Equation ◽  
Liquid Equilibrium ◽  
Raoult’S Law ◽  
System A ◽  
Equilibrium Data ◽  
Alcohol System

Isothermal vapour-liquid equilibrium data at 65, 73 and 80 °C and isobaric ones at 101.3 kPa were measured in the tetrachloromethane-sec-butyl alcohol system. A modified circulation still of the Gillespie type was used for the measurements. Under the conditions of measurement, the system exhibits positive deviations from Raoult's law and minimum boiling-point azeotropes. The experimental data were fitted to a number of correlation equations, the most suitable being the Wilson equation.

scholarly journals Application of Artificial Intelligence (AI) for Sustainable Highway and Road System

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 60
Author(s):  
Md Arifuzzaman ◽  
Muhammad Aniq Gul ◽  
Kaffayatullah Khan ◽  
S. M. Zakir Hossain
Keyword(s):  
Experimental Data ◽  
High Performance ◽  
Adhesion Force ◽  
Model Development ◽  
Real Life ◽  
Bayesian Optimization ◽  
Support Vector ◽  
Adhesive Properties ◽  
Bayesian Optimization Algorithm ◽  
The Mean

There are several environmental factors such as temperature differential, moisture, oxidation, etc. that affect the extended life of the modified asphalt influencing its desired adhesive properties. Knowledge of the properties of asphalt adhesives can help to provide a more resilient and durable asphalt surface. In this study, a hybrid of Bayesian optimization algorithm and support vector regression approach is recommended to predict the adhesion force of asphalt. The effects of three important variables viz., conditions (fresh, wet and aged), binder types (base, 4% SB, 5% SB, 4% SBS and 5% SBS), and Carbon Nano Tube doses (0.5%, 1.0% and 1.5%) on adhesive force are taken into consideration. Real-life experimental data (405 specimens) are considered for model development. Using atomic force microscopy, the adhesive strength of nanoscales of test specimens is determined according to functional groups on the asphalt. It is found that the model predictions overlap with the experimental data with a high R2 of 90.5% and relative deviation are scattered around zero line. Besides, the mean, median and standard deviations of experimental and the predicted values are very close. In addition, the mean absolute Error, root mean square error and fractional bias values were found to be low, indicating the high performance of the developed model.

Physicochemical, Interaction & Topological Descriptors vs. hMAO-A Inhibition of Aplysinopsin Analogs: A Boulevard to the Discovery of Semi-Synthetic Anti-Depression Agents

2021 ◽  
Vol 22 ◽  
Author(s):  
Rajeev K. Singla ◽  
Ghulam Md Ashraf ◽  
Magdah Ganash ◽  
Varadaraj Bhat G ◽  
Bairong Shen
Keyword(s):  
Model Development ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Topological Descriptors ◽  
Good Prediction ◽  
Physicochemical Interaction ◽  
Human Beings ◽  
2D Qsar

Background: Neurological disorder, depression is the globally 4th leading cause of chronic disabilities in human beings. Objective: This study aimed to model a 2D-QSAR equation that can facilitate the researchers to design better aplysinopsin analogs with potent hMAO-A inhibition. Methods: Aplysinopsin analogs dataset were subjected to ADME assessment for drug-likeness suitability using StarDrop software before modeled equation. 2D-QSAR equations were generated using VLife MDS 4.6. Dataset was segregated into training and test set using different methodologies, followed by variable selection. Model development was done using principal component regression, partial least square regression, and multiple regression. Results: The dataset has successfully qualified the drug-likeness criteria in ADME simulation, with more than 90% of molecules cleared the ideal conditions including intrinsic solubility, hydrophobicity, CYP3A4 2C9pKi, hERG pIC50, etc. 112 models were developed using multiparametric consideration of methodologies. The best six models were discussed with their extent of significance and prediction capabilities. ALP97 was emerged out as the most significant model out of all, with ~83% of the variance in the training set, the internal predictive ability of ~74% while having the external predictive capability of ~79%. Conclusion: ADME assessment suggested that aplysinopsin analogs are worth investigating. Interaction among the descriptors in a way of summation or multiplication products, are quite influential and yielding significant 2D-QSAR models with good prediction efficiency. This model can be used for the design of a more potent hMAO-A inhibitor having an aplysinopsin scaffold, which can then contribute to the treatment of depression and other neurological disorders.

Self-Diffusion Coefficient and Viscosity in Fluids

2011 ◽  
Vol 9 (1) ◽  
Author(s):  
Lawrence Novak
Keyword(s):  
Experimental Data ◽  
Diffusion Coefficient ◽  
Transport Coefficient ◽  
Transport Coefficients ◽  
Dynamics Simulation ◽  
Residual Entropy ◽  
Transport Reaction ◽  
Self Diffusion ◽  
Coefficient Corrélation ◽  
Self Diffusion Coefficient

Rate-based models suitable for equipment or transport-reaction modeling require a capability for predicting transport coefficients over a sufficient range of temperature and pressure. This paper demonstrates a relatively simple novel approach to correlate and estimate transport coefficients for pure components over the entire fluid region.The use of Chapman-Enskog transport coefficients for reducing self-diffusion coefficient and viscosity to dimensionless form results in relatively simple mathematical relationships between component dimensionless transport coefficients and residual entropy over the entire fluid region. Dimensionless self-diffusion coefficients and viscosities were calculated from extensive molecular dynamics simulation data and experimental data on argon, methane, ethylene, ethane, propane, and n-decane. These dimensionless transport coefficients were plotted against dimensionless residual entropy calculated from highly accurate reference equations of state.Based on experimental data, the new scaling model introduced here shows promise as: (1) an equation of state-based transport coefficient correlation over the entire fluid region (liquid, gas, and critical fluid), (2) a component transport coefficient correlation for testing transport data consistency, and (3) a component transport coefficient correlation for interpolation and extrapolation of self-diffusion coefficient and viscosity.

Effect of Common Impurities on the Phase Behavior of Carbon-Dioxide-Rich Systems: Minimizing the Risk of Hydrate Formation and Two-Phase Flow

SPE Journal ◽  
2011 ◽  
Vol 16 (04) ◽  
pp. 921-930 ◽  
Author(s):  
Antonin Chapoy ◽  
Rod Burgass ◽  
Bahman Tohidi ◽  
J. Michael Austell ◽  
Charles Eickhoff
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Phase Behavior ◽  
Water Content ◽  
Thermodynamic Model ◽  
Two Phase Flow ◽  
Hydrate Formation ◽  
Experimental Methodology ◽  
Phase Flow ◽  
Two Phase

Summary Carbon dioxide (CO2) produced by carbon-capture processes is generally not pure and can contain impurities such as N2, H2, CO, H2 S, and water. The presence of these impurities could lead to challenging flow-assurance issues. The presence of water may result in ice or gas-hydrate formation and cause blockage. Reducing the water content is commonly required to reduce the potential for corrosion, but, for an offshore pipeline system, it is also used as a means of preventing gas-hydrate problems; however, there is little information on the dehydration requirements. Furthermore, the gaseous CO2-rich stream is generally compressed to be transported as liquid or dense-phase in order to avoid two-phase flow and increase in the density of the system. The presence of impurities will also change the system's bubblepoint pressure, hence affecting the compression requirement. The aim of this study is to evaluate the risk of hydrate formation in a CO2-rich stream and to study the phase behavior of CO2 in the presence of common impurities. An experimental methodology was developed for measuring water content in a CO2-rich phase in equilibrium with hydrates. The water content in equilibrium with hydrates at simulated pipeline conditions (e.g., 4°C and up to 190 bar) as well as after simulated choke conditions (e.g., at -2°C and approximately 50 bar) was measured for pure CO2 and a mixture of 2 mol% H2 and 98 mol% CO2. Bubblepoint measurements were also taken for this binary mixture for temperatures ranging from -20 to 25°C. A thermodynamic approach was employed to model the phase equilibria. The experimental data available in the literature on gas solubility in water in binary systems were used in tuning the binary interaction parameters (BIPs). The thermodynamic model was used to predict the phase behavior and the hydrate-dissociation conditions of various CO2-rich streams in the presence of free water and various levels of dehydration (250 and 500 ppm). The results are in good agreement with the available experimental data. The developed experimental methodology and thermodynamic model could provide the necessary data in determining the required dehydration level for CO2-rich systems, as well as minimum pipeline pressure required to avoid two-phase flow, hydrates, and water condensation.

scholarly journals Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies

2018 ◽  
Author(s):  
Jukka Intosalmi ◽  
Adrian C. Scott ◽  
Michelle Hays ◽  
Nicholas Flann ◽  
Olli Yli-Harja ◽  
...  
Keyword(s):  
Experimental Data ◽  
Time Course ◽  
Model Development ◽  
Growth Dynamics ◽  
Colony Growth ◽  
Data Driven ◽  
Coarse Grained ◽  
Intercellular Signaling ◽  
Growth Data ◽  
Metabolic Coupling

AbstractMotivationMulticellular entities, such as mammalian tissues or microbial biofilms, typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding on how cell–cell and metabolic coupling produce functionally optimized structures is still limited.ResultsHere, we present a data-driven spatial framework to computationally investigate the development of one multicellular structure, yeast colonies. Using experimental growth data from homogeneous liquid media conditions, we develop and parameterize a dynamic cell state and growth model. We then use the resulting model in a coarse-grained spatial model, which we calibrate using experimental time-course data of colony growth. Throughout the model development process, we use state-of-the-art statistical techniques to handle the uncertainty of model structure and parameterization. Further, we validate the model predictions against independent experimental data and illustrate how metabolic coupling plays a central role in colony formation.AvailabilityExperimental data and a computational implementation to reproduce the results are available athttp://research.cs.aalto.fi/csb/software/multiscale/[email protected],[email protected]

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