Towards predictive ash accumulation and transport modeling
Grigorios Koltsakis, Aristotle University Thessaloniki
This work presents modeling and measurement results to support the prediction of ash accumulation patterns and its impact on pressure drop. The test campaign includes data collection on a burner rig where ash properties and layer vs plug ash formation are studied in the presence and absence of soot. The properties of layer and plug ash are identified by means of optical techniques and pressure drop measurements for a variety of operating scenarios emulating passive and active regeneration modes. A physics-based model accounting for ash particle filtration, agglomeration, detachment, and re-attachment is parameterized to match the results of the burner tests. The model is subsequently applied, fine-tuned and validated based on a second test campaign with transient cycle data collected on a Diesel engine operated for hundreds of hours under highly transient conditions (NRTC mode). The model showed good performance in terms of predicting the accumulation mode of ash (layer mode vs plug mode) and the resulting impact on pressure drop. Despite the model complexity, the promising results and the reasonable calculation times encourage application of predictive modeling towards life-cycle analysis of ash impact on real-world conditions to support filter design and control optimization.