Towards predictive ash accumulation and transport modeling

G. Koltsakis, M. Mitsouridis, I. MylonidisExothermia SA

K. Baumgard, R. Duddukuri, W. ZhouJohn Deere Power Systems

S. George, S. Viswanathan, A. HeibelCorning Incorporated

CLEERS 2020

Effect of ash on pressure drop & filtration

15-Sep-2020

• Kamp, C., et al. Soot and Ash Deposition Characteristics at the Catalyst-Substrate Interface and Intra-Layer Interactions in Aged Diesel Particulate Filters Illustrated using Focused Ion Beam (FIB) Milling, SAE Int. J. Fuels Lub, 2012

• Sappok A., et al. Individual and Synergistic Effects of Lubricant Additive Components on Diesel Particulate Filter Ash Accumulation and Performance, ASME ICES2012-81237, 2012

• Custer, N., et al. Lubricant-Derived Ash Impact on Gasoline Particulate Filter Performance, SAE International, 2016

• Boger, T. and Cutler, W. System integration and application for a three way catalyst coated gasoline particulate filter, SAE International, 2019

Filtration efficiency increases with ash

Impact of ash on Pressure drop depends (at least) on soot loading

Motivation

15-Sep-2020

Develop predictive model for ash accumulation/migration and deltaP impact

Use model for system design and controls optimization at early design phase

Data from ~ 500 h transient engine tests

Earlier modeling works

15-Sep-2020

Conceptual particulate transport mechanisms

• Sappok A., et al. Theoretical and Experimental Analysis of Ash Accumulation and Mobility in Ceramic Exhaust Particulate Filters and Potential for Improved Ash Management, SAE Int. J. Fuels Lubr, 2014

Literature models aim to describe discreet ash migration events of pre-accumulated ash under steady flow.

The present work aims at ‘life cycle’ transient analysis.

Ash agglomerate

Ash precursors

• 𝐹: laminar channel flow friction factor• 𝜂: gas viscosity• 𝑢 𝑧 : inlet channel local mean axial velocity• 𝑏𝑙𝑜: open width of the inlet channel

considering the ash deposit profile

1-D approach1-D model based on a simple force balance on the soot/ash particle and an empirical parameter to describe the critical particle removal/detachment stress:

3-D approach3-D CFD model estimating the drag and lift forces imposed on the particle by the exhaust flow under steady state conditions.

Modeling

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Modeling framework and requirements

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Channel and wall flow distribution

Filtration of soot and ash particles (in-wall and cake)

Pressure drop incl impact of ash layer and plug

Heat transfer

Soot reactions and exothermic effects

Species transfer

Wall catalytic reactions

Soot-borne & agglomerated ash particles

Soot migration

Ash agglomeration

Ash agglomerate migration

Well described in the literature

Focus of present study

Modeling and simulation platform used here: exothermia suite (former axisuite)

Soot- & gas-borne ash precursors

15-Sep-2020

• Wang, Y., et al. The Origin, Transport, and Evolution of Ash in Engine Particulate Filters, Applied Energy, 2020• Lambert C., et al. Analysis of High Mileage Gasoline Exhaust Particle Filters, SAE International, 2016• McGeehan, J., et al. Extending the Boundaries of Diesel Particulate Filter Maintenance With Ultra-Low Ash - Zero-Phosphorus Oil, SAE International, 2012• Pirjola, L., et al. Effects of Fresh Lubricant Oils on Particle Emissions Emitted by a Modern Gasoline Direct Injection Passenger Car, Environ. Sci. Technol., 2015• Morcos, M., et al. Characterization of DPF Ash for Development of DPF Regeneration Control and Ash Cleaning Requirements, SAE International, 2011• Fang, H., et al. Spectroscopic Study of Biodiesel Degradation Pathways, SAE International, 2006

Low ash/soot ratio High ash/soot ratio

Ash particles on carbon particles Formation of solid ash nanoparticles

Model assumptions– Soot-borne ash is filtered together with

soot and remains in the deposit after soot oxidation

– Gas-borne ash is introduced as ‘filterable’ multi-disperse aerosol

Flow-induced soot migration submodel

15-Sep-2020

Detachment condition:

• 𝜏𝑖 > 𝜏𝑑𝑒𝑡𝑎𝑐ℎ, 𝜏𝑖 =𝑓∙𝜌∙𝑣𝑖

2

8

𝑁

𝑚2

Reattachment condition:

• 𝜏𝑖 < 𝜏𝑟𝑒𝑑𝑒𝑝𝑜𝑠𝑖𝑡𝑁

𝑚2

The model simulates the migration of pre-deposited ash-containing soot based on a simple shear stress submodel

Soot-borne ash is indirectly migrated

• Sappok A., et al. Theoretical and Experimental Analysis of Ash Accumulation and Mobility in Ceramic Exhaust Particulate Filters and Potential for Improved Ash Management, SAE Int. J. Fuels Lubr, 2014

• Sappok, A., et all. In-Situ Optical Analysis of Ash Formation and Transport in Diesel Particulate Filters During Active and Passive DPF Regeneration Processes, SAE Int. J. Fuels Lubr, 2013

• Dittler A. Ash Transport in Diesel Particle Filters, SAE Technical Paper 2012-01-1732, 2012

Ash accumulation & agglomeration

15-Sep-2020

Localized oxidation of the soot cake on the filter surface, characterized by the inward shrinking islands of soot, which serve to concentrate and agglomerate the ash

Soot with elevated ash content

• Sappok, A., et all. In-Situ Optical Analysis of Ash Formation and Transport in Diesel Particulate Filters During Active and Passive DPF Regeneration Processes, SAE Int. J. Fuels Lubr, 2013

• Ishizawa, T., et al. Investigation into Ash Loading and Its Relationship to DPF Regeneration Method, SAE International, 2009

• Custer, N., et al. Lubricant-Derived Ash Impact on Gasoline Particulate Filter Performance, SAE International, 2016

Temperature induced ash agglomeration submodel

15-Sep-2020

𝑅𝑎 𝑇 = 𝐴 ∗ 𝑒−𝐵

𝑇∗ 𝑓𝑎𝑠ℎ𝐶 , 𝑓𝑎𝑠ℎ =

Vash

Vcake

Thermal agglomeration mechanism:

The filtered deposit consists of:• Soot agglomerates• Soot-borne ash• Filtered ash primary particles

Soot oxidation exposes further primary ash particlesAsh primary particles form ash agglomerates. The rate depends on local temperature and ash/soot ratio

Flow-induced agglomerated ash migration submodel

15-Sep-2020

Ash detachment conditions:(1) Local soot cake inhibits ash detachment

𝑚𝑠𝑐𝑖 < 𝑚𝑠𝑐𝑑𝑒𝑡𝑎𝑐ℎ

𝑘𝑔

𝑚2

(2) Detachment depends on local velocity and local ash agglomerate size

𝑊𝑖 > 𝑊𝑑𝑒𝑡𝑎𝑐ℎ, 𝑊𝑖~𝑣𝑖 ∙ 𝐷𝑎

Ash redeposition condition:

• 𝑊𝑖 < 𝑊𝑟𝑒𝑑𝑒𝑝𝑜𝑠𝑖𝑡𝑚2

𝑠

Triggered by flow rate increase➔ Shear stresses increase, gradually overcoming the adhesion forces between ash agglomerates and substrate➔ Ash agglomerates detach

Testing campaign

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Burner rig

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• Separate flow paths for combustion & cooling air

• Ability to independently control soot, ash, NOx, exhaust flow & temperature etc.

• Instrumented for Δp, temperature, gaseous emissions, PM & PN measurements

Testing protocol• Part loaded to target ash load at desired

conditions• Periodic high flow routine for ash compaction

and transport• Periodic filter weights for monitoring ash

accumulation

• Periodic checks• 700ºC regeneration• Pressure drop evaluation: Flow scan

• Ash plug depth measurements: Borescope• 9 different locations spread across the cross

section of the filter• 3 channels at each location

Ash loads

High flows

Weights

Test protocol variationsCT-scans with ~ 30 g/l ash

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Low flow rate

Filter Aw/o HFs

w/o soot

Ash

on

lySo

ot

and

ash

Low flow rate with high flow events

Formation of ‘stochastic’ ash bridges

Ash accumulates mostly in the wall and as a layer

Substantial plug ash formation

High flow events affect plug length and/or density

Ash loading without soot @ low flow rate

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Initial in-wall ash accumulation followed by layer ash

Pressure drop model tuning to identify ash loaded wall & ash layer permeability

Non-destructive analysis of ash loaded filter (CT scan and borescope based ash plug measurements) at 30 g/l ash

Ash loading with soot and high flow events

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Pressure drop information and measurements of plug length were used to tune the ash model migration parameters

Predicted layer to plug ash migration during

high flow event

Soot loading

Soot oxidation

Ash loading

Ash loading with soot and high flow events

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Soot accumulation Soot oxidation Ash accumulation Ash migrationAsh accumulation

Transient engine dyno

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Ash plug formation & model validation

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The target of predictivity in terms of lifecycle pressure drop prediction is met

Encouraging results about model predictivity in terms of ash migration

~ 500 hours of transient engine operation

Predicting the effect of cell-structure

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The 300/7 asymmetric cell structure offers large deltaP advantage at soot loaded condition.

Simulation of 500 h of consecutive NRTCs with 2 different cell densities

Predicting the effect of forced regeneration frequency

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wal

l so

ot

effe

ct

Wall soot accumulation prevented by the ash layer

Simulation of 500 h of consecutive NRTCs with 2 different regen frequencies

Baseline vs 2 times more frequent activation of forced regeneration

Higher regen frequency associated with lower average soot loadings and deltaP

Plug ash pattern is fairly similar

Predicting the effect of regeneration strategy

15-Sep-2020

For the purely passive regeneration case, the model predicts virtually no plug ash.

wal

l so

ot

effe

ct

Wall soot accumulation prevented by the ash layer

Simulation of 500 h of consecutive NRTCs with 2 different regen strategies

Passive regeneration predicted assuming 20% higher inlet temperature

Conclusions

15-Sep-2020

A ‘mostly physical’ ash formation and migration model was developed accounting for:

– Soot layer detachment

– Thermally induced ash agglomeration

– Ash layer detachment

The model was calibrated vs burner test rig and applied in transient engine data.

The results are viewed as a first step towards life-cycle filter analysis supporting design and control optimization at early stage.

Further research topics identified with respect to– ash fate in the wall pores, intra pore migration and impact of coatings

– plug ash density as function of ash agglomerate size

– ash bridging

Thank you!

15-Sep-2020