Numerical simulation of soot filtration and combustion within diesel particulate filters

The numerous benefits offered by diesel engines, compared to gasoline ones, are balanced by a drawback of increasing concern, namely soot emissions. Nowadays, soot emissions can be reduced by physically trapping the particles within on-board diesel particulate filters (DPF). The filter gets progressively loaded by filtering the soot laden flue gases, thus causing an increasing pressure drop, until regeneration takes place. The aim of this work is to develop a fully predictive three-dimensional mathematical model able to accurately describe the soot deposition process into the filter, the consequent gradual modification of the properties of the filter itself (i.e. permeability and porosity), the formation of a soot filtration cake, and the final regeneration step. The commercial computational fluid dynamics (CFD) code Fluent 6.2.16, based on a finite-volume numerical scheme, is used to simulate the gas and particulate flow fields in the DPF, whereas particle filtration sub-models and regeneration kinetics are implemented through user-defined-subroutines (UDS).Model predictions highlight uneven soot deposition profiles in the first steps of the filtration process; however, the very high resistance to the gas flow of the readily formed cake layer determines the evolution into an almost constant layer of soot particles. The ignition of the loaded soot was simulated under different operating conditions, and two regeneration strategies were investigated: a “mild regeneration” at low temperature and oxygen concentration, that operated a spatially homogeneous ignition of the deposited soot, and a “fast regeneration”, with an uneven soot combustion along the axial coordinate of the filter, due to strong temperature gradients inside the filter itself. These findings are supported by comparison and validation with experimental data.     

Excretion of 35S-Tobias acid (2-naphthylamino, 1-sulphonic acid) by the rat after oral and intravenous administration

The lipid-lowering effects of 3 g of the nicotinic acid derivative pentaerythritoltetranicotinate (niceritrol) given either 1 g X 3 or 1.5 g X 2 have been evaluated in 18 subjects with hyperlipoproteinaemia. When 1 g niceritrol was given three times daily, the serum TG concentration fell from 3.14 +/- 0.48 to 1.86 +/- 0.18 mmol/1 (41% reduction) and the serum cholesterol concentration from 282 +/- 9 to 227 +/- 11 mg/100 ml (20% reduction). The same daily dose, given 1.5 g twice, did not significantly lower the serum TG concentration, and serum cholesterol was lowered by only 12%. Niceritrol tablets prepared with a dissolution time of 60 or 90 min had identical lipid-lowering properties. Although patients may find it practical to take niceritrol only twice daily, such a dose regimen has considerably less effect on elevated serum lipids than a thrice-daily regimen.     

Powder interlayer bonding of geometrically complex Ti-6Al-4V parts

The International Journal of Advanced Manufacturing Technology - Powder interlayer bonding (PIB) is a novel joining technique, which has been developed to facilitate high-integrity repairs of...     

ARMIDA TM: Multimedia Applications across ATM-Based Networks Accessed via Internet Navigation

ARMIDA TM (Applications Retrieving Multimedia Information Distributed over ATM) is a prototypical system for experimental applications based on the interactive retrieval of multimedia information from remote data bases over ATM networks. ARMIDA TM aims at being compliant with the specifications issued by the Digital Audio Visual Council (DAVIC) for interactive multimedia services and applications, as well as at representing a sample implementation of the system specified in DAVIC 1.0. The present paper illustrates the way ARMIDA TM works to provide these applications, by describing the system hardware and software architecture and its main components, with a particular concern towards the way they interact to implement the required functionality.     

Droplet breakage and coalescence in liquid–liquid dispersions: Comparison of different kernels with EQMOM and QMOM

Droplet coalescence and breakage in turbulent liquid–liquid dispersions is simulated by using computational fluid dynamics (CFD) and population balance modeling. The multifractal (MF) formalism that takes into account internal intermittency was here used for the first time to describe breakage and coalescence in a surfactant‐free dispersion. The log‐normal Extended Quadrature Method of Moments (EQMOM) was for the first time coupled with a CFD multiphase solver. To assess the accuracy of the model, predictions are compared with experiments and other models (i.e., Coulalogou and Tavlarides kernels and Quadrature Method of Moments [QMOM]). EQMOM and QMOM resulted in similar predictions, but EQMOM provides a continuous reconstruction of the droplet‐size distribution. Transient predictions obtained with the MF kernels result in a better agreement with the experiments. © 2016 American Institute of Chemical Engineers AIChE J, 63: 2293–2311, 2017     

Simulation of polydisperse multiphase systems using population balances and example application to bubbly flows

In this work the relationship between multiphase computational fluid dynamics models and population balance models is illustrated by deriving the main governing equations from the generalized population balance equation. The resulting set of equations, consisting of the well known two-fluid model coupled with a bivariate population balance model, is then implemented in the CFD code OpenFOAM. The implementation is used to simulate a particular multiphase problem: bubbly flow in a rectangular column. Results show that, although the different mesoscale models for drag force, coalescence, breakup and mass transfer, can be improved, the agreement with experiments is nevertheless good. Moreover, although the problem investigated is quite complex, as the evolution of bubbles is solved in real-space, time and phase-space (i.e. bubble size and composition) the resulting computational costs are reasonable. This is due to the fact that the bivariate population balance model is solved here with the so-called conditional quadrature method of moments, that very efficiently deals with these problems. The overall approach is demonstrated to be efficient and robust and is therefore suitable for the simulation of many polydisperse multiphase flows.     

Assessment of gel formation in colloidal dispersions during mixing in turbulent jets

Onset of gel formation upon mixing between colloidal dispersions and coagulant solutions in turbulent jets was studied using a combination of computational fluid dynamics (CFD) and population balance equation (PBE). To describe the interaction between turbulence fluctuations and particle aggregation, a micromixing model based on presumed probability density function was implemented inside the CFD code. Furthermore, effect of the solid phase on the fluid flow was modeled through an effective viscosity of the mixture evaluated from PBE. The results are presented in the parameter space of the primary particle diameter and the solid volume fraction where strong interplay between mixing and aggregation mechanisms controls the gelation phenomena and consequently also the fluid dynamics. Simulation results are in good agreement with observations from gelation experiments of concentrated nanoparticle suspensions injected into coagulant solutions. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4567–4581, 2013     

Comparison of Eulerian QBMM and classical Eulerian–Eulerian method for the simulation of polydisperse bubbly flows

The spatial gas distribution of poly-disperse bubbly flows depends greatly on the bubble size. To reflect the resulting polycelerity, more than two momentum balance equations (typically for the gas and liquid phases) have to be considered, as done in the multifluid approach. The inhomogeneous multiple-size group model follows this approach, also combined with a population balance model. As an alternative, in a previous work, an Eulerian quadrature-based moments method (E-QBMM) was implemented in OpenFOAM; however, only the drag force was included. In this work, different nondrag forces (lift, wall lubrication, and turbulent dispersion) are added to enable more complex test cases to be simulated. Simulation results obtained using E-QBMM are compared with the classical E–E method and validated against experimental data for different test cases. The results show that there is good agreement between E-QBMM and E–E methods for mono-disperse cases, but E-QBMM can better simulate the separation and segregation of small and large bubbles.     

A comparative study for nanoparticle production with passive mixers via solvent-displacement: Use of CFD models for optimization and design

Active and passive mixers, including a considerable variety of micro-devices, are nowadays widely used for the production of nanoparticles. Polymer nanoparticles for controlled drug delivery applications are investigated in this work with two specific objectives. The first one is to experimentally quantify the efficiency of confined impinging jets reactors and Tee-mixers in the production of nanoparticles constituted by two polymers: poly-?-caprolactone and poly(methoxypolyethyleneglycolcyanoacrylate-co-hexadecylcyanoacrylate). The second objective is the development of a simple and reliable mathematical model to be used for the design, optimization and scale up of mixers for polymer nanoparticle production. Although the behaviour of the polymers investigated is quite different, it is possible to conclude that confined impinging jets reactors are more efficient than Tee-mixers, in converting the pressure drop into turbulent kinetic energy and as a consequence in producing smaller particles. The very simple modelling approach proposed here (based on the evaluation of the mixing time) seems to be able to correlate well experimental data obtained under different operating conditions, independently on the type of device used. Moreover, in the case of poly-?-caprolactone it was also possible to successfully quantify the particle formation time with a simple power law, further exploiting the model.