Mooson Kwauk

Exploring complex systems in chemical engineering—the multi-scale methodology

Challenges in quantitative design of chemical processes mainly reside in their complex structures, which are usually multi-scale in nature, and are difficult to analyze by the average approach as commonly used. The multi-scale methodology has thus received more and more attention in recent years. There are three kinds of multi-scale methodology: descriptive for distinguishing the phenomenological difference of structures at different scales; and correlative for formulating phenomena at higher scales by analyzing the mechanisms at lower scales; and variational for revealing the dominant mechanisms of the structure aid the relationship between the scales. This paper presents an overview of multi-scale methodologies with emphasis on the variational methodology, and proposes the possibility of establishing a generalized multi-scale methodology, effective for analyzing single-phase turbulent flow in pipe, gas-solid two-phase fluidization, and gas-solid-liquid three-phase fluidization. The variational multi-scale methodology consists of the following steps: Phenomenological resolution with respect to scales of structures. Identification of dominant mechanisms. Establishment of conservation conditions with respect to different scales and correlation between different scales. Formulation of variational criterion to identify what dominates the stability of structure and what compromise exists between different dominant mechanisms. Integration between conservation conditions with stability conditions

Fluidization of fine particles

Experiments on the fluidization of fine particles (Geldart group C) with mean sizes 0.01-18.1 mu m and densities 100-8600 kg/m(3) were conducted. Experimental results show that the process of fluidizing fine particles usually involves plugging, channeling, disrupting, and agglomerating. When fluidized, the entities fluidized generally consist of particle agglomerates varying in size from the largest at the bottom of the bed (some even defluidized) to the smallest at the top (some even unassociated to discrete particles). Best to fluidize are the agglomerates which have reached a uniform equilibrium size after repeated solids circulation. Lowering agglomerate density proves to be an effective measure for improving the fluidization quality of fine particles. The fluidizing behavior of fine-particle agglomerates, compared with that of normal discrete particles, is illustrated diagrammatically. The large amount of factual findings poses a challenging problem for analysis, and even possible quantitative correlation, between particle properties and fluidization behavior

Micro-visualization of clusters in a fast fluidized bed

Micrographs in a 10-m high by 90-mm ID FCC-air fast fluidized bed were taken by using a video camera provided with a special probe, which consists of a set of lenses and an optical fiber flashlight transmitter, inserted radially into the bed. These micrographs, taken at different radial and axial positions, can distinguish two phases in the fast fluidized bed: a dispersed phase and a cluster phase. In the dispersed phase, the solid particles are noted to be present essentially individually, while in the cluster phase the solid particles agglomerate with one another and are enmeshed in the dispersed phase. The shape of clusters is in general irregular, and their size, highly variable. It seems that the clusters transform from strands at the center of the bed into spheres near the wall. The radial distribution of cluster concentration corresponds to that of solids suspension density.

From Multiscale Modeling to Meso-Science

Multiscale modeling is becoming essential for accurate, rapid simulation in science and engineering. This book presents the results of three decades of research on multiscale modeling in process engineering from principles to application, and its generalization for different fields. This book considers the universality of meso-scale phenomena for the first time, and provides insight into the emerging discipline that unifies them, meso-science, as well as new perspectives for virtual process engineering. Multiscale modeling is applied in areas including: multiphase flow and fluid dynamicschemical, biochemical and process engineeringmineral processing and metallurgical engineeringenergy and resourcesmaterials science and engineeringJinghai Li is Vice-President of the Chinese Academy of Sciences (CAS), a professor at the Institute of Process Engineering, CAS, and leader of the EMMS (Energy-minimizing multiscale) Group. Wei Ge, Wei Wang, Ning Yang and Junwu Wang are professors at the EMMS Group, part of the Institute of Process Engineering, CAS. Xinhua Liu, Limin Wang, Xianfeng He and Xiaowei Wang are associate professors at the EMMS Group, part of the Institute of Process Engineering, CAS. Mooson Kwauk is an emeritus director of the Institute of Process Engineering, CAS, and is an advisor to the EMMS Group.

Aggregative and particulate fluidization—The two extremes of a continuous spectrum

Solid particles belonging to Geldart Group A, B and D were fluidized in liquids of changing viscosity and in CO2 under ambient to supercritical conditions. Local bed voidage signals were collected and processed in conjunction with global expansion characteristics to give quantitative indexes for evaluating fluidization quality. Results showed that the fluidized state changes progressively from aggregative to particulate when fluidized separately by gas, supercritical fluid and liquids, indicating an infinite number of intermediate states existing between aggregative and particulate fluidization. A discrimination number Dn is proposed to describe the transition from particulate to aggregative. A heterogeneity index δ and a nonideality index fh are proposed to quantify, respectively, the local and the global characteristics of the intermediate states.

Dynamic behaviors of heterogeneous flow structure in gas-solid fluidization

Abstract A method was established to quantitatively describe nonlinear dynamic behavior of heterogeneous flow structure in gas–solid fluidization by carrying out multiple resolution and time series reconstruction of experimental signals. Optimum sampling frequency was proposed by analyzing the dependence of Kolmogorov entropy of time series on sampling frequencies. Original signals could be resolved with respect first to scale, and then to time and amplitude into a periodic function and three irregular changes (micro-scale fluctuations, and meso-scale irregular amplitude and time fluctuations). Statistical analysis indicated that the three kinds of irregular components are of random characteristics, with a complicated evolution of their probability density distributions with changing operating conditions. A new distribution function, called Compound Weibull distribution with seven parameters, was developed to describe the irregular fluctuations of flow structure, leading to a nonlinear dynamic model for simulating dynamic behaviors of heterogeneous flow structure in gas–solid fluidization, which has been coded into a software package.

Levitation of discrete particles in oscillating liquids

Wet ion-exchange resins (ϱP=1.17 g/cm3, d=0.0435, 0.0401, 0.0334 or 0.0290 cm) were suspended, while vibrating about a fixed position, by either symmetrically or asymmetrically oscillating water. By taking into account convection acceleration, a proposed mathematical model [eq. (15)], was found to predict adequately the levitation frequency. It showed also that the effect of pressure gradient was more significant than drag force at causing a particle to levitate. Glass beads were also levitated in a 55% aqueous glycerol.

EXTENDING THE KNOWLEDGE BASE OF CHEMICAL ENGINEERING

Abstract The obvious current reversion to micro-scale investigations in basic chemical engineering, combined with the need, of a quite different nature, in the rapid growth of high added-value and small-lot functional materials, have been pointing to an area not yet sufficiently covered by the unit operations, transport phenomena and chemical reaction engineering. Although it is difficult to define accurately this area, a cursory scan of the activities already in progress has revealed a few common attributes: multi-phased (structured), multi-scaled, multi-disciplined, nonlinear, needs for resolution to reductionism-solvable subsystems, and pervasive in the process industry. From these activities, the present paper drafts a tentative scheme for studying the related problems: first to dissect a problem into various scales ? spatial, temporal or otherwise as best suits the case in hand ? in order to identify pertinent parameters which are then organized into model formulations. Together with inter-scale model formulations, a zoom-in/zoom-out process is carried out between the scales, by trial-and-error and through reasoning, to arrive at a global formulation of a quantitative solution, in order to derive, eventually, the general from the particular.

Partial Realization of the EMMS Paradigm

This chapter uses the top-down mode of the EMMS paradigm on CPU clusters to realize structural similarity between problem, model, and software, but not hardware. First we propose a set of structure-dependent conservation equations based on the structure of the problem. A computing scheme is then realized by integrating EMMS drag into the reduced SFM; that is, EMMS-based multi-fluid modeling (EFM). In this process, the structure of both model and software (coding) is consistent with that of the investigated multiscale problem. Simulation with the EFM starts with the global prediction of the macro-scale distribution. Using this as an initial condition greatly reduces the time needed to reach a steady state. Time-dependent, regional evolution is then simulated; its accuracy is guaranteed because of the meso-scale modeling of both drag and mass transfer coefficient. Extensive application of the EMMS paradigm identifies advantages over conventional computational fluid dynamics (CFD) approaches such as higher accuracy and efficiency. Complete realization of the EMMS paradigm with consistent hardware will be discussed in Chap. 7.

Oxidation of TiAl, Ni and Fe in a dynamic environmental SEM

Abstract A Dynamic Environmental Scanning Electron Microscope (DESEM) was developed in this laboratory for in situ monitoring of the morphology of metal surface during oxidation. The process of nucleation and growth of oxide grains/whiskers on Fe, Ni and TiAl during oxidation were successfully observed and recorded continuously by using our KYKY1500 ESEM. The experiments were carried out under different conditions of oxidation: temperature in the range of 500∼750 °C and oxygen partial pressure in the range of 10 −4 ∼45 Pa. In the light of the observed surface morphology and microstructure during the oxidation, the growth mechanism and reaction kinetics were discussed.