Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods

The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position and time. Integrating knowledge derived from a discrete element model, this method can be used to predict residence time distribution, mean and relative standard deviation of the API concentration in a continuous mixer. Low‐order statistical models, including response surface methods, kriging, and high‐dimensional model representations are also presented. Their efficiency for design optimization and process design space identification with respect to operating and design variables is illustrated.

     

The mean squared error of Geweke and Porter-Hudak's estimator of the memory parameter of a long-memory time series

We establish some asymptotic properties of a log-periodogram regression estimator for the memory parameter of a long-memory time series. We consider the estimator originally proposed by Geweke and Porter-Hudak (The estimation and application of long memory time series models. Journal of Time Ser. Anal. 4 (1983), 221–37). In particular, we do not omit any of the low frequency periodogram ordinates from the regression. We derive expressions for the estimator's asymptotic bias, variance and mean squared error as functions of the number of periodogram ordinates, m , used in the regression. Consistency of the estimator is obtained as long as m ←∞ and n ←∞ with ( m log m )/ n ← 0, where n is the sample size. Under these and the additional conditions assumed in this paper, the optimal m , minimizing the mean squared error, is of order O( n ^4/5). We also establish the asymptotic normality of the estimator. In a simulation study, we assess the accuracy of our asymptotic theory on mean squared error for finite sample sizes. One finding is that the choice m = n ^1/2, originally suggested by Geweke and Porter-Hudak (1983), can lead to performance which is markedly inferior to that of the optimal choice, even in reasonably small samples.     

Interface pattern formation in nonlinear dissipative systems

The problem of interface pattern selection in nonlinear dissipative systems is critical in many fields of science, occurring in physical, chemical and biological systems. One of the simplest pattern formations is the Saffman-Taylor finger pattern that forms when a viscous fluid is displaced by a less viscous fluid. Such finger-shaped patterns have been observed in distinctly different fields of science (hydrodynamics, combustion and crystal growth) and this has led to a search for a unified concept of pattern formation, as first proposed by the classic work of D'arcy Thomson. Two-dimensional finger-shaped patterns, observed in flame fronts and the ensembled average shape of the diffusion-limited aggregation pattern, have been shown to be similar to Saffman-Taylor finger shapes. Here we present experimental studies that establish that the cell shapes formed during directional solidification of alloys can be described by the form of the Saffman-Taylor finger shape equation when a second phase is present in the intercellular region.     

Effect of thermosolutal convection on microstructure formation in the Pb-Bi peritectic system

Experimental studies have been conducted in the two-phase region of the Pb-Bi peritectic system to investigate the effect of thermosolutal convection on the banded microstructure. A systematic study is carried out by varying convection effects through the use of thin cylindrical samples of different diameters. A strong oscillatory convection is found in a 6.0-mm-diameter sample that produces a large treelike primary phase in the center of the sample that is surrounded by the peritectic phase matrix. The length of the treelike structure is found to decrease as the diameter of a sample is reduced to 0.8 mm. When the sample diameter is further reduced to 0.4 mm, laminar flow is present that gives rise to discrete bands of the two phases. The banded microstructure, however, is found to be transient and only the peritectic phase forms after a few bands. Composition variations in the banded structure are measured to determine the nucleation undercoolings for both phases and to characterize the banding cycle. The banding cycle is determined by the nucleation undercoolings and is independent of convection in the melt, but the banding window closely depends on convection. The presence of the transient banding process is analyzed by using a boundary layer model, and the number of transient bands is found to agree with the model for samples of different compositions and lengths.     

Time-resolved Fourier transform infrared spectroscopic imaging

Fourier transform infrared (FT-IR) imaging allows simultaneous spectral characterization of large spatial areas due to its multichannel detection advantage. The acquisition of large amounts of data in the multichannel configuration results, however, in a poor temporal resolution of sequentially acquired data sets, which limits the examination of dynamic processes to processes that have characteristic time scales of the order of minutes. Here, we introduce the concept and instrumental details of a time-resolved infrared spectroscopic imaging modality that permits the examination of repetitive dynamic processes whose half-lives are of the order of milli-seconds. As an illustration of this implementation of step-scan FT-IR imaging, we examine the molecular responses to external electric-field perturbations of a microscopically heterogeneous polymer-liquid crystal composite. Analysis of the spectroscopic data using conventional univariate and generalized two-dimensional (2D) correlation methods emphasizes an additional capability for accessing of simultaneous spatial and temporal chemical measurements of molecular dynamic processes.     

A continuous-flow system for high-precision kinetics using small volumes

A generally applicable continuous-flow kinetic analysis system that gives data of a precision high enough to measure small kinetic isotope effects for enzymatic and nonenzymatic reactions is described. It employs commercially available components that are readily assembled into an apparatus that is easy to use. It operates under laminar flow conditions, which requires that the time between the initiation of the reaction in the mixer and the observation be long enough that molecular diffusion can effect a symmetrization of the concentration profile that results from a thin plug of reagents introduced at the mixer. The analysis of a second-order irreversible reaction under pseudo-first-order conditions is presented. The Yersinia pestis protein tyrosine phosphatase catalyzed hydrolysis of p-nitrophenyl phosphate is characterized with the system, and a proton inventory on kcat is presented.     

Robust named entity detection from optical character recognition output

In this paper, we focus on information extraction from optical character recognition (OCR) output. Since the content from OCR inherently has many errors, we present robust algorithms for information extraction from OCR lattices instead of merely looking them up in the top-choice (1-best) OCR output. Specifically, we address the challenge of named entity detection in noisy OCR output and show that searching for named entities in the recognition lattice significantly improves detection accuracy over 1-best search. While lattice-based named entity (NE) detection improves NE recall from OCR output, there are two problems with this approach: (1) the number of false alarms can be prohibitive for certain applications and (2) lattice-based search is computationally more expensive than 1-best NE lookup. To mitigate the above challenges, we present techniques for reducing false alarms using confidence measures and for reducing the amount of computation involved in performing the NE search. Furthermore, to demonstrate that our techniques are applicable across multiple domains and languages, we experiment with optical character recognition systems for videotext in English and scanned handwritten text in Arabic.     

Synthesis of magnetic nanocomposite microparticles for binding of chlorinated organics in contaminated water sources

In this work, the development of novel magnetic nanocomposite microparticles (MNMs) via free radical polymerization for their application in the remediation of contaminated water is presented. Acrylated plant-based polyphenols, curcumin multiacrylate (CMA) and quercetin multiacrylate (QMA), were incorporated as functional monomers to create high affinity binding sites for the capture of polychlorinated biphenyls (PCBs), as a model pollutant. The MNMs were characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy, dynamic light scattering, and UV–visible spectroscopy. The affinity of these novel materials for PCB 126 was evaluated and fitted to the nonlinear Langmuir model to determine binding affinities (K_D). The results suggest the presence of the polyphenolic moieties enhances the binding affinity for PCB 126, with K_D values comparable to that of antibodies. This demonstrates that these nanocomposite materials have promising potential as environmental remediation adsorbents for harmful contaminants.     

Energy efficient control of a BTX dividing-wall column

Dividing-wall column (DWC) is considered nowadays the new champion in distillation, as it can bring substantial reduction in the capital invested as well as savings in the operating costs. This work presents the simulation results of energy efficient control and dynamics of a dividing-wall column (DWC). In order to allow a fair comparison of the results with previously published references, the case-study considered here is the industrially relevant ternary separation of the mixture benzene-toluene-xylene (BTX) in a DWC. Rigorous simulations were carried out in Aspen Plus and Aspen Dynamics. Several conventional control structures based on PID control loops (DB/LSV, DV/LSB, LB/DSV, LV/DSB) were used as a control basis. These control structures were enhanced by adding an extra loop controlling the heavy component composition in the top of the prefractionator, by using the liquid split as an additional manipulated variable, thus implicitly achieving minimization of energy requirements. The results of the dynamic simulations show relatively short settling times and low overshooting especially for the DB/LSV and LB/DSV control structures. Moreover, the energy efficient control proposed in this work allows the operation of DWC with minimum energy requirements or maximum purity of products.