Development of modified stokes expression to model the behavior of expanded beds containing polydisperse resins for protein adsorption

Expanded bed behavior was modeled by using the Richardson-Zaki correlation between the superficial velocity of the feed stream and the void fraction of the bed. A polydisperse material, Chelating excellose® (70-210 Μm in diameter, 1.21 g/cm³ in density), which has Ni²⁺ ions for the selective binding of histidine-tagged proteins, was used as the resin. A method to modify the Stokes expression to express the terminal settling velocity of the resins by introducing two empirical parameters, the effective diameter of the resins and an exponent for(ρ _p -ρ)/Μ term, was developed. Combined use of the Richardson-Zaki correlation and the modified Stokes expression was successful in modeling the bed expansion by incorporating physical properties of feed streams and the resins.     

Recent progress of crystal growth modeling and growth control

With the rapid growth of electronic and optoelectronic industry, the demand for crystal materials increased dramatically for the past two decades. The requirement for better, cheaper, and larger single crystals has driven extensive research and development in crystal growth. To understand the interplay of associated transport processes and phase transformation, as well as to provide a design basis, crystal growth modeling is becoming more important in both fundamentals and practice. In this article, we review some recent progress of numerical modeling in crystal growth through three subjects: (1) hot-zone design, (2) active growth control, and (3) morphological simulation. Examples are given through our research results in recent years. For better illustration and process understanding some visualization results using transparent materials are given. The needs and the challenges ahead for crystal growth modeling are also discussed.     

Predictive models for multibiometric systems

Recognizing a subject given a set of biometrics is a fundamental pattern recognition problem. This paper builds novel statistical models for multibiometric systems using geometric and multinomial distributions. These models are generic as they are only based on the similarity scores produced by a recognition system. They predict the bounds on the range of indices within which a test subject is likely to be present in a sorted set of similarity scores. These bounds are then used in the multibiometric recognition system to predict a smaller subset of subjects from the database as probable candidates for a given test subject. Experimental results show that the proposed models enhance the recognition rate beyond the underlying matching algorithms for multiple face views, fingerprints, palm prints, irises and their combinations.     

Explicit reference modeling methodology in parametric CAD system

Today parametric associative CAD systems must help companies to create more efficient virtual development processes. While dealing with complex parts (e.g. the number of surfaces of the solid) no CAD modeling methodology is existing. Based on the analysis of industrial designers' practices as well as student practices on CAD, we identified key factors that lead to better performance. Our objective in this article is to propose a practical method for complex parts modeling in parametric CAD system. An illustration of the performances and the results obtained by this method are presented comparing the traditional method with the proposed one while using an academic case and then an industrial case.     

4D MRI Flow Coupled to Physics‐Based Fluid Simulation for Blood‐Flow Visualization

Modern MRI measurements deliver volumetric and time‐varying blood‐flow data of unprecedented quality. Visual analysis of these data potentially leads to a better diagnosis and risk assessment of various cardiovascular diseases. Recent advances have improved the speed and quality of the imaging data considerably. Nevertheless, the data remains compromised by noise and a lack of spatiotemporal resolution. Besides imaging data, also numerical simulations are employed. These are based on mathematical models of specific features of physical reality. However, these models require realistic parameters and boundary conditions based on measurements. We propose to use data assimilation to bring measured data and physically‐based simulation together, and to harness the mutual benefits. The accuracy and noise robustness of the coupled approach is validated using an analytic flow field. Furthermore, we present a comparative visualization that conveys the differences between using conventional interpolation and our coupled approach.     

Pathline glyphs

Visualization of pathlines is common and highly relevant for the analysis of unsteady flow. However, pathlines can intersect, leading to visual clutter and perceptual issues. This makes it intrinsically difficult to provide expressive visualizations of the entire domain by an arrangement of multiple pathlines, in contrast to well‐established streamline placement techniques. We present an approach to reduce these problems. It is inspired by glyph‐based visualization and small multiples: we partition the domain into cells, each corresponding to a downscaled version of the entire domain. Inside these cells, a single downscaled pathline is drawn. On the overview scale, our pathline glyphs lead to emergent visual patterns that provide insight into time‐dependent flow behavior. Zooming‐in allows us to analyze individual pathlines in detail and compare neighboring lines. The overall approach is complemented with a context‐preserving zoom lens and interactive pathline‐based exploration. While we primarily target the visualization of 2D flow, we also address the extension to 3D. Our evaluation includes several examples, comparison to other flow visualization techniques, and a user study with domain experts.     

Determination of effectiveness factor of a partial internal wetting catalyst from adsorption measurement

The effect of partial internal wetting of catalyst pellets on apparent reaction kinetics at elevated temperatures and pressures is investigated experimentally and by modeling for benzene hydrogenation. A new method that combines adsorption and chemical reaction is introduced to study the kinetics influenced by capillary condensation of reagents at steady-state conditions. It is shown that the extent of liquid filling in the pellet interior has a critical effect on the global kinetics, and the current state of the catalyst depends on the history. Under certain conditions two steady states of the effectiveness factor exist. Moreover, either a decrease in temperature or increase in total pressure can increase the effectiveness factor. The model exhibits good agreement with experimental results.     

Fluidization with hot compressed water in micro-reactors

In this paper the concept of micro-fluidized beds is introduced. A cylindrical quartz reactor with an internal diameter of only 1 mm is used for process conditions up to and 244 bar. In this way, fast, safe, and inherently cheap experimentation is provided. The process that prompted the present work on miniaturization is gasification of biomass and waste streams in hot compressed water (SCWG). Therefore, water is used as fluidizing agent. Properties of the micro-fluid bed such as the minimum fluidization velocity (U_mf), the minimum bubbling velocity (U_mb), bed expansion, and identification of the fluidization regime are investigated by visual inspection. It is shown that the micro-fluid bed requires a minimum of twelve particles per reactor diameter in order to mimic homogeneous fluidization at large scale. It is not possible to create bubbling fluidization in the cylindrical micro-fluid beds used. Instead, slugging fluidization is observed for aggregative conditions. Conical shaped micro-reactors are proposed for improved simulation of the bubbling regime. Measured values of U_mf and U_mb are compared with predictions of dedicated 2D and 3D discrete particle models (DPM) and (semi)-empirical relations. The agreement between the measurements and the model predictions is good and the model supports the concept and development of micro-fluid beds.     

Measurement and modeling solubility of bioactive coumarin and its derivatives in supercritical carbon dioxide

To design a supercritical fluid extraction process for the separation of bioactive substances from natural products, a quantitative knowledge of phase equilibria between target biosolutes and solvent is necessary. How-ever, mostly no such information is available in literature to date. Thus in the present study, illustratively the solubility of bioactive coumarin and its various derivatives (i.e., hydroxy-, methyl-, and methoxy-derivatives) in supercritical CO₂ were measured at 308.15–328.15 K and 10–30 MPa. Also, the pure physical properties such as normal boiling point, critical constants, acentric factor, molar volume and standard vapor pressure for coumarin and its derivatives were estimated. By these estimated information, the measured solubilities were quantitatively correlated by an approximate lattice equation of state proposed recently by the present authors.     

Analysis of cell aggregation in the culturing of cerebellar granule neurons

We have proposed previously that an increased concentration of growth factor secreted by neurons themselves has a direct effect on survival of the neurons, and thereby cell density serves as a regulator of survival of neurons. In this study, the same idea was used to analyze the aggregation of cerebellar granule neurons in culture experimentally and theoretically. Assuming the transport of growth factor and substrate within an aggregate is by molecular diffusion, the metabolic efficiency of neurons, on the basis of an autocatalytic phenomenon, was increased within an aggregate compared to an identical quantity of dispersed cells. A good agreement in the size of neuronal aggregate between the theoretical prediction and the experimental result was found. This illustrates that growth factors produced by neurons acting in either an autocrine or paracrine manner play an important role during the development of cultured neurons.