Simulation and Estimation of Vapor-Liquid Equilibrium for Asymmetric Binary Systems (CO2-Alcohols) Using Artificial Neural Network

Since it is not always possible to carry out experiments at all desired temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of vapor-liquid equilibrium. In this work, a method using artificial neural network (ANN) was designed and applied to simulate and estimate the VLE for the binary asymmetric systems containing CO₂ and Alcohols. The vapor-liquid equilibrium data of six systems include (CO₂-methanol), (CO₂-ethanol), (CO₂-1-butanol), (CO₂-2-butanol), (CO₂-1-pentanol) and (CO₂-2-pentanol) were used to developed the ANN for simulation of VLE. The results when using a developed ANN model or other methods such as SRK equations of state with LCVM, PSRK, WS, were compared with experimental data at various temperatures and pressures. Finally, it was observed that there is more qualitative and quantitative conformity between ANN model results and experimental data. Furthermore, the developed ANN model showed more accurate estimation over wide range of experimental conditions.     

Methodology for in-line rheology by ultrasound Doppler velocity profiling and pressure difference techniques

This paper describes a methodology for measuring rheological flow properties in-line, in real-time, based on simultaneous measurements of velocity profiles using an ultrasound velocity profiling (UVP) technique with pressure difference (PD) technology. The methodology allows measurements that are rapid, non-destructive and non-invasive and has several advantages over methods presented previously. The set-up used here allows direct access to demodulated echo amplitude data, thus providing an option to switch between time domain algorithms and algorithms based on FFT for estimating velocities, depending on the signal-to-noise ratio (SNR) and time resolution required. Software based on the MATLAB^® graphical user interface (GUI) has been developed and provides a powerful and rapid tool for visualizing and processing the data acquired, giving rheological information in real-time and in excellent agreement with conventional methods. This paper further focuses on crucial aspects of the methodology: implementation of low-pass filter and singular value decomposition (SVD) methods, non-invasive measurements and determination of the wall positions using channel correlation and methods based on SVD. Measurements of sound velocity and attenuation of ultrasound in-line were introduced to increase measurement accuracy and provide an interesting approach to determine particle concentration in-line. The UVP-PD methodology presented may serve as an in-line tool for non-invasive, real-time monitoring and process control.     

Stick-slip conditions in the general motion of a planar rigid body

In this paper we study combined translational and rotational (general) motion of planar rigid bodies in the presence of dry coulomb friction contact. Despite the cases where the body has pure translational/ rotational motion or can be assumed as a point mass, during the general motion, distinct points of the rigid body move in different directions which cause the friction force vector at each point to be different. Therefore, the direction and the magnitude of the overall friction force cannot be intuitively defined. Here the concept of instantaneous center of rotation is used as an effective method to determine the resultant friction force and moment. The main contribution of this paper is to propose novel stick-slip switching conditions for the general in-plane motion of rigid bodies. Simulation results for some combination of external forces are provided and some experimental tests are designed and conducted for practical verification of the proposed stick-slip conditions.     

In vitro evaluation of spray‐dried chitosan microspheres crosslinked with pyromellitic dianhydride for oral colon‐specific delivery of protein drugs

Chitosan microspheres have been prepared using a spray‐drying method, and crosslinked with pyromellitic dianhydride. The chemical structure of the modified chitosan was characterized by FTIR spectroscopy and solid state 13C NMR analysis. The particle size and morphology of the crosslinked chitosan were investigated. These microspheres were evaluated for colon‐specific delivery of bovine serum albumin (BSA) as a model protein drug. The results indicate that the drug was released as follows: 37.1 ± 2.8% after 2 h in SGF, 73.1 ± 4.8% after 8 h (2 h in SGF+ 6 h in SIF), and 80.9 ± 4.1% after 12 h in SCF. The effect of β‐glucosidase on the drug release was also examined. The encapsulation efficiency was decreased from 88.4 ± 3.1% to 62.8 ± 2.9%, with increasing BSA concentration. Loading capacity was significantly increased from 6.3 ± 0.3% to 41.8 ± 4.1% by increasing the initial BSA concentration. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40514.     

From Side Chains Rattling on Picoseconds to Ensemble Simulations of Protein Folding

Simulations of biological macromolecules have evolved tremendously since the discoveries of the 1970s. The field has moved from simple simulations in vacuo on picosecond scales to milliseconds of accurate sampling of large proteins, and it has become a standard tool in biochemistry and biophysics, rather than a dedicated theoretical one. This is partly due to increasing computational power, but it would not have been possible without huge research efforts invested in new algorithms and software. Here, we illustrate some of this development, both past and future challenges, and in particular, discuss how the recent introduction of modern ensemble methods is breaking the trend of ever-longer simulations to instead focus on throughput and sampling. This has not only helped simulations become much more accurate, but it provides statistical error estimates, which are critical, as simulations are increasingly used to predict properties that have not yet been measured experimentally.     

A new hybrid approach to discrete multiple facility location problem

Locating certain facilities in predetermined sites is named the multiple facility location problems (MFLP). The objective of these kinds of problems is locating facilities to serve a given set of customers so that candidate sites and requirements are known. When the new facility sites have to be selected from a given set of candidate sites, the mentioned location problem becomes a discrete multiple facility location problem (DMFLP). In this paper, a special approach of DMFLP is considered where different multiple facilities have to be placed (location decision) and also customers have to be assigned to these facilities (allocation or assignment). The mathematical model of the proposed problem is developed, and with respect to the complexity of solving the mathematical model, especially in large scale, a new hybrid approach is proposed based on tabu search algorithm to solve the problem at each scale. Computational results on several randomly generated problems in comparison with a new proposed lower bound obtained from Lagrangian relaxation indicate that the proposed hybrid approach is both accurate and efficient.     

A hidden Markov model to detect regime changes in cryptoasset markets

The objective of this work is to understand the dynamics of cryptocurrency prices. Specifically, how prices switch between different regimes, going from “bull” to “stable” and “bear” times. For this purpose, we propose a hidden Markov model that aims at explaining the evolution of Bitcoin prices through different, unobserved states. The implementation of the proposed model includes a likelihood ratio test that allows to compare models with different states and with different covariance structures. Our empirical findings show that the time movements of Bitcoin prices across different exchange markets are well-described by the proposed model. In particular, a parsimonious model with a diagonal covariance matrix leads to better predictions, compared with a model with a full covariance matrix.     

Particle Detachment from Rough Surfaces in Turbulent Flows: An Analytical Expression for Resuspension Fraction

The critical shear velocity for resuspension of micrometer size particles from rough surfaces was studied. The random variation of surface roughness was accounted for. The recently developed Monte Carlo simulations accounted for the statistical variations of physical parameters that control the particle resuspension process. A sensitivity analysis showed that the surface roughness and its random variation was the key factor affecting the particle resuspension from rough surfaces. The theory of probabilistic transformation was used and an analytical expression for evaluating the resuspension fraction of particles of different sizes from rough surfaces versus the shear velocity was developed. The resuspension fractions as predicted by the analytical model were evaluated for several particles sizes for a range of turbulent flow shear velocities. The resulting resuspension fractions were compared with those obtained from the Monte Carlo simulations as well as the available experimental data. It was found that the predictions of the new analytical equation were in good agreement with the Monte Carlo simulation results and the experimental data, especially for smaller size particles. This new analytical expression could be used as a simple empirical equation for estimating flow-induced resuspension of particles from rough surfaces.