Evaluation Of Dispersion Coefficients Research Articles

Numerical and Experimental Evaluation of Dispersion Coefficient for Resin Transfer Modeling

Resin transfer molding (RTM) is a composite manufacturing process. A preformed fiber is placed in a closed mold and a viscous resin is injected into the mold. In this article, a model is developed to predict the flow pattern, extent of reaction, and temperature change during the filling and curing in a thin rectangular mold. A numerical simulation is presented to predict the free surface and its interactions with heat transfer and cure for flow of a shear-thinning resin through the preformed fiber.To simulate this process, using local thermal equilibrium assumption, it is essential to include the thermal dispersion term in energy equation. The best method to achieve this result is experimental simulation and preparing proportionate system at simple conditions without curing. By comparison of recorded temperature values (using installed instruments at various locations), and the corresponding results from numerical solution for different estimated values of dispersion coefficient, this coefficient has been evaluated based on the best matching estimate. The results show that, to simulate composite manufacturing process by RTM method, the effect of dispersion term in energy equation shall not be neglected.

A new methodology for determining dispersion coefficient using ordinary and partial differential transport equations

The present study proposes a methodology for determining the effective dispersion coefficient based on the field measurements performed in Gwangju (GJ) Creek in South Korea which is environmentally degraded by the artificial interferences such as weirs and culverts. Many previous works determining the dispersion coefficient were limited in application due to the complexity and artificial interferences in natural stream. Therefore, the sequential combination of N-Tank-In-Series (NTIS) model and Advection-Dispersion-Reaction (ADR) model was proposed for evaluating dispersion process in complex stream channel in this study. The series of water quality data were intensively monitored in the field to determine the effective dispersion coefficient of E. coli in rainy day. As a result, the suggested methodology reasonably estimates the dispersion coefficient for GJ Creek with 1.25 m(2)/s. Also, the sequential combined method provided Number of tank-Velocity-Dispersion coefficient (NVD) curves for convenient evaluation of dispersion coefficient of other rivers or streams. Comparing the previous studies, the present methodology is quite general and simple for determining the effective dispersion coefficients which are applicable for other rivers and streams.

Evaluation of Dispersion Coefficients in Meandering Channels from Transient Tracer Tests

Mixing characteristics of conservative pollutants were examined two-dimensionally in a laboratory meandering channel, and a method to compute the dispersion coefficients was developed based on the measured concentration data. To investigate how the hydrodynamics influences pollutant mixing in meandering channels, both flow and tracer experiments were conducted in an S-curved laboratory channel. A two-dimensional routing procedure was presented to evaluate the longitudinal dispersion coefficient as well as the transverse dispersion coefficient under the unsteady concentration condition. The results of the tracer experiments showed that the tracer cloud behaved quite differently depending on whether or not the tracer cloud was transported following the filament of maximum velocity. Also, separation and reemerging of the tracer cloud were promoted by secondary currents. The observed transverse dispersion coefficients obtained by the routing procedure were close to those obtained by existing moment methods. The transverse dispersion coefficient tended to increase with an increasing aspect ratio, whereas it is not sensitive to the injection location. However, the longitudinal dispersion coefficient was sensitive to the injection location as well as the aspect ratio.

On the evaluation of dispersion coefficients from visualization experiments in artificial porous media

High-resolution single source–solute transport experiments in glass-etched pore networks presented in a previous publication are used for quantifying the hydrodynamic dispersion as a function of Peclet number ( Pe). This type of artificial porous media is ideal for understanding the effects of pore-scale phenomena on solute dispersion thanks to its well characterized topology and pore geometry. The hydrodynamic dispersion coefficients are estimated by matching the spatial and temporal distributions of the solute concentration over various regions of the network with the numerical solution of the advection–dispersion equation and using a parameter space analysis to ensure well conditioning of the parameters. The source release function and assumptions on boundary conditions are found to affect significantly the reliability of the dispersion coefficient estimates. The estimated longitudinal dispersion coefficients are in close quantitative agreement with literature data for dispersion in porous media. The extracted transverse dispersivity ( α T) values indicate an apparent decrease of α T with increasing flow velocity, which is at variance of constant dispersivity approximation adopted commonly in soil hydrology models and is attributed to incomplete diffusive mixing at the pore intersections. Calculated values of an effective mixing ratio at pore junctions are in agreement with published theoretical estimates and reveal a transition from partial mixing to streamline routing as Pe increases within the range investigated here.

岩石内浸透流における溶質分散係数の決定

When we deal with the solute dispersion problems in rock ground, the evaluation of dispersion coefficient becomes important as well as the determination of hydraulic parameters like the permeability. This paper presents how to determine the dispersion coefficient of rocks in a laboratory, and the values of dispersion coefficients for many kinds of rocks collected from different locations in this country were determined by using a newly designed apparatus.The results in this study are summarized as follows:1) The utility of apparatus proposed in this study was confirmed by the experimental results.2) The rock dispersion coefficients were 4.75×10-6-4.80×10-9m2/s for all rock samples.3) The dispersion coefficient increases with increasing Reynolds number.

Evaluation of dispersion coefficients in axially dispersed plug-flow systems using a general analytical expression for a random input pulse

The simplest way of testing flow systems for non-ideal flow behaviour is based on the axially dispersed plug-flow model. A very simple experimental technique involves manually injecting a dose of tracer into the system and following the resulting response(s) down-stream. A method is proposed using a general description fitting to such pulses in the form ▪ The solution of the basic partial differential equation for the axially dispersed plug-flow model (ADPF) with this relation for the input function is far more realistic than, for example, the assumption of a perfect step or δ pulse and, as is shown, gives better results than the method of moments. It is far simpler, however, than the frequency response method at a comparable accuracy, as all calculations are carried out in the time domain only. The advantages of the proposed method manifest themselves best in the case of curves having extended tail sections.

The accurate numerical determination of two- and three-body dispersion forces

A new computational method for the evaluation of dispersion coefficients between atoms is described. Results are given for the two-body coefficients through R-10 for a representative selection of one and two-electron atoms, the uncoupled Hartree approximation being employed in the latter case, and also the leading non-additive three-body terms are calculated for triplets of hydrogen and helium. Particular refined computations are described for atomic hydrogen, values of 6.499 026 705 and 21.642 464 54 au being obtained for the dipole-dipole and triple-dipole coefficients respectively.

Evaluation of dispersion coefficients in axially dispersed plug-flow systems using a general analytical expression for a random input pulse

Evaluation of dispersion coefficients in axially dispersed plug-flow systems using a general analytical expression for a random input pulse