Material transport prediction

FIRAC is a computer code designed to estimate radioactive and chemical source-terms as.sociaied with a fire and predict fire-induced flows and thermal and material transport within facilities, especially transport through a ventilation system. It includes a fire compartment module based on the FIRIN computer code, which calculates fuel mass loss rates and energy generation rates within the fire compartment. A second fire module, FIRAC2, based on the CFAST computer code, is in the code to model fire growth and smoke transport in multicompartment stmetures. 

The basic nature of the turbulent exchange process is not yet well enough known to allow accurate prediction of behavior without recourse to experiment. Correlation of the growing body of experimental knowledge in this field, however, offers the possibility of evaluating time-averaged point values of thermal and material transport for many conditions of industrial interest. It is the purpose of this discussion to present some of the more elementary considerations of the nature of turbulent flow with particular emphasis upon thermal and material transport. 

The prediction of material transport involves expressions similar to those encountered for thermal transport except that the behavior of each component must be taken into account. For example, in onedimensional flow the flux of one component past a section is given by... 

Equation (57) applies to material transport in tubes and yields an average deviation of 9.5% from the experimental data. An expression of similar form yielded an average deviation of 14.8% for the thermal transport. The ratio of thermal to material transport was found to be 1.09 with an average deviation of 13.7% (S3). Somewhat better agreement with predicted behavior was encountered for the studies on packed beds (S2). These data serve to illustrate the uncertainties which presently exist in the prediction of simultaneous material and thermal transfer under a variety of conditions. Satterfield s work has made a distinct contribution to understanding the macroscopic influences of combined thermal and material transport. Some of the discrepancy he noted may relate to assumptions concerning the nature of the chemical reaction associated with the decomposition of hydrogen peroxide. 

At present the development of more effective basic correlations of thermal and material transport in turbulent shear flow rests primarily upon an extension of the understanding of the mechanics of turbulence. Howarth and K rm n (Kl, K4) and Batchelor (B6) contributed materially to the knowledge of isotropic, homogeneous turbulence, but the prediction of the behavior in shear flow still must be based on experiment (L3) even for steady, uniform flow. The absence of a basic understanding of the growth and decay of turbulence (K5) prevents a microscopic analysis of thermal and material transport under nonuniform or unsteady conditions. 

The method developed in this book is also used to provide input parameters for composite models which can be used to predict the thermoelastic and transport properties of multiphase materials. The prediction of the morphologies and properties of such materials is a very active area of research at the frontiers of materials modeling. The prediction of morphology will be discussed in Chapter 19, with emphasis on the rapidly improving advanced methods to predict thermodynamic equilibrium phase diagrams (such as self-consistent mean field theory) and to predict the dynamic pathway by which the morphology evolves (such as mesoscale simulation methods). Chapter 20 will focus on both analytical (closed-form) equations and numerical simulation methods to predict the thermoelastic properties, mechanical properties under large deformation, and transport properties of multiphase polymeric systems. 

Particle-fluid flow has been in existence in industrial processes since the nineteenth century. Applications include pneumatic conveying, which deals with pipe flow of solid material transported by a gas, slurry transport and processing of solids in a fluid. The necessity of predicting blower or pumping power for a given amount of material to be conveyed led to measurements of pressure drops and attempts in the correlation of physical parameters. That anomaly exists in the correlation in terms of simple parameter is one of the motivations for the exploration into the details of distributions in density and velocity and the present state of development of instrumentation. 

It is obvious that it is practically not feasible to exactly quantify the physico-chemical aquifer properties but estimates and simplifications, e.g. average or effective values must be applied. In view of an application of the SMART modelling strategy and concept for transport predictions, it is important to know how wrong estimates of the physicochemical properties of the aquifer material will take effect on the simulation results. Therefore, the objective of a first suite of simulations is to assess the impact of the composition of the aquifer material and its physicochemical properties on the transport of PHE and to examine the sensitivity of lithological composition and grain... 

Effective medium theory (EMT) is commonly used to describe the microstructure-property relationships in heterogeneous materials and predict the effective physical properties. It has recently been revised to predict the thermal conduction of nanocomposites. For nanocomposites with nanopartides on the order of or smaller than the phonon mean free path, the interface density of nanopartides is a primary factor in determining the thermal conductivity. In graphite nanosheet polymer composites, the interfacial thermal resistance still plays a role in the overall thermal transport. However, the thermal conductivity depends strongly on the aspect ratio and on the orientation of graphite nanosheets. 

For application to hot pressing the applied pressure is approximately equivalent in importance to the particle size. If the raw materials and compacts formed from them are characterized completely, it seems to me that reproducibility in behavior is reasonable to expect, but predictability is lacking because the precise interrelationships among the variables are lacking with the multiplicity of possible material transport mechanisms taking place. 

To predict the comfort of a material, a combination of hand evaluation, eg, using the Kawabata system, as well as deterrnination of the heat and moisture transport properties, is necessary. Often, these values are correlated with a sensory evaluation of the tactile qualities of the material by a human subject panel. A thorough discussion of the many physical and psychological factors affecting comfort is available (134,135). 

In addition to material balance, two transport equations can be used to predict the flux of water and solute. For instance, the following simplified model can be used (Dandavati etai, 1975 Evangelista, 1986). 

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