Flow maldistribution of the exhaust gas entering a Diesel
Particulate Filter (DPF) can cause uneven soot distribution during
loading and excessive temperature gradients during the regeneration
phase. Minimizing the magnitude of this maldistribution is
therefore an important consideration in the design of the inlet
pipe and diffuser, particularly in situations where packaging
constraints dictate bends in the inlet pipe close to the filter, or
a sharp diffuser angle. This paper describes the use of Particle
Image Velocimetry (PIV) to validate a Computational Fluid Dynamic
(CFD) model of the flow within the inlet diffuser of a DPF so that
CFD can be used with confidence as a tool to minimize this flow
maldistribution.
PIV is used to study the flow of gas into a DPF over a range of
steady state flow conditions. The distribution of flow approaching
the front face of the substrate was of particular interest to this
study. Optically clear diffusing cones were designed and placed
between pipe and substrate to allow PIV analysis to take place.
Stereoscopic PIV was used to eliminate any error produced by the
optical aberrations caused by looking through the curved wall of
the inlet cone.
In parallel to the experiments, numerical analysis was carried
out using a CFD program with an incorporated DPF model. Boundary
conditions for the CFD simulations were taken from the experimental
data, allowing an experimental validation of the numerical results.
The CFD model incorporated a DPF model, the cement layers seen in
segmented filters and the intumescent matting that is commonly used
to pack the filter into a metal casing. The mesh contained
approximately 580,000 cells and used the realizable k-ε turbulence
model. The CFD simulation predicted both pressure drop across the
DPF and the velocity field within the cone and at the DPF face with
reasonable accuracy, providing confidence in the use the CFD in
future work to design new, more efficient cones.