The Chemical Process Engineering Research Institute (CPERI) is one of the Institutes of the Centre for Research and Technology-Hellas (CERTH), a leading research organisation that carries out diverse research projects in close collaboration with European and US Industries in the areas of energy conservation, environmental processes, solid fuels, liquid fuels and hydrocarbons, chemical technology, polymers, membrane processes, electrochemical processes, and aerosol & particle technology.

The test case presented here is the exhaust after-treatment system of a light-duty (Euro III) direct injection Diesel engine. The motivation for the automotive application lies in the increasing market share of Diesel powered passenger automobiles and in the stricter emissions levels planned for both light- and heavy-duty Diesel vehicles, particularly in Europe and the USA. A Diesel exhaust after-treatment system is called upon to handle a number of pollutants, including nitrous oxides (NO, NO2), unburned hydrocarbons and particulate matter. The latter pollutant poses particular difficulties to the exhaust after-treatment system design which itself is constrained by the requirement of not adversely affecting engine operation and of maintaining the Diesel engine's fuel economy advantage. A number of exhaust after-treatment devices such as catalytic converters and filters, based on porous and/or honeycomb-structured materials, are placed along the exhaust line in order to remove/convert the aforementioned pollutants. The function of these components and their interaction is strongly affected by exhaust gas flow field at many physical scales, from the scale of the exhaust system to the scale of the material features (honeycomb structure). At the same time, the ever increasing complexity of the Diesel exhaust after-treatment system dictates that isolated optimisation of component devices is not sufficient. The approach taken here to achieve the needed system-level optimisation is to use APUS-CFD and the FlowGrid environment as the computational engine providing the exhaust gas flow field at the larger physical scales, while flow and mass/heat transfer phenomena at the smaller scales are handled by pre-existing models, which are coupled to the flow solution.

The primary objective of this case study is the use of APUS-CFD in conjunction with application-specific models for the optimisation of the after-treatment system design. With the use of a simulation tool based on 3-D CFD modelling, this optimisation is primarily concerned with the system shape/configuration and with the sizing of the devices. The figure below shows such configuration.

Device configuration for an exhaust after-treatment system

1. exhaust gas velocity and temperature profiles entering the DPF and DOC devices,
2. temperature distribution within the devices due to 3-D internal heat transfer and non-axisymmetric heat losses to the exterior.

1. time response of the DPF pressure drop (flow resistance)
2. time response of the DPF (internal) temperatures and outflow temperature,
3. distribution of soot mass loading within the filter during and after the regeneration sequence.

The flow resistance for the Diesel Oxidation Catalyst (DOC) and Diesel Particulate Filter (DPF) were modelled using momentum sinks. For turbulence, the standard k-e model was used. The regions occupied by the DPF and DOC monoliths are considered laminar zones (no production or dissipation of turbulence; momentum transfer is based on laminar viscosity). A mixed type mesh, consisting of hexahedral, wedges and tetrahedral elements was generated (1.5 Million) to capture the pipe wall boundary layer, the flow patterns created by bends in the exhaust, and the inflow diffuser cone flow pattern.

The 90° bend in the exhaust line creates non-axisymmetry in the exhaust flow (see Figure below) which the APUS-CFD solution shows to persist until the DPF. This non-axisymmetric flow field affects the operation of both the DOC and DPF.

Velocity contour on the middle-plane of the exhaust system

Velocity contours on DPF	Velocity contours on DOC

Further validation of APUS-CFD was performed by assessing the accuracy of the inflow profiles on the DPF. The comparison of the axial velocity profiles on diametric lines just upstream the DPF show quite good agreement between APUS-CFD and a reference solver (see Figures below). This comparison is considered quite strict due to the fact that it assesses the capture of the flow asymmetry at a location of interest which is relatively far downstream of the (secondary) geometry features which generate the asymmetry in the inflow profiles.

Axial Velocity profile along A-A	Axial Velocity profile along B-B

For the transient case, the accuracy of APUS-CFD was assessed using the case of transient DPF loading. The loading of the DPF is simulated by the transient DPF loading model, adapted for coupled execution with the flow solver. It should be noted that this model is based on cake-filtration and cannot capture the initial deep-bed filtration regime exhibited for the initial 200 seconds of the loading sequence. The same case was also run on a single workstation using 'third party' CFD solver with the corresponding user-programming also implementing the aforementioned DPF loading model. The comparison of results (see below) is satisfactory considering the simplification of the loading model implemented in the flow solvers. Compared to the single-channel DPF model result, the response of the back pressure predicted by the DPF model coupled to the flow solvers seem to better capture the curvature of the loading curve, a feature that can be attributed to the establishment of a soot loading distribution in the filter that forces a more uniform velocity inflow profile.

Comparison of Transient DPF loading between APUS-CFD, Reference Solver and test data

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