Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

Investigating within-canopy variation of functional traits and cellular structure of sugar maple (Acer saccharum) leaves

Patterns of increasing leaf mass per area (LMA), area-based leaf nitrogen (Narea), and carbon isotope composition (δ13C) with increasing height in the canopy have been attributed to light gradients or hydraulic limitation in tall trees. Theoretical optimal distributions of LMA and Narea that scale with light maximize canopy photosynthesis; however, sub-optimal distributions are often observed due to hydraulic constraints on leaf development. Using observational, experimental, and modeling approaches, we investigated the response of leaf functional traits (LMA, density, thickness, and leaf nitrogen), leaf carbon isotope composition (δ13C), and cellular structure to light availability, height, and leaf water potential (Ψl) in an Acer saccharum forest to tease apart the influence of light and hydraulic limitations. LMA, leaf and palisade layer thickness, and leaf density were greater at greater light availability but similar heights, highlighting the strong control of light on leaf morphology and cellular structure. Experimental shading decreased both LMA and area-based leaf nitrogen (Narea) and revealed that LMA and Narea were more strongly correlated with height earlier in the growing season and with light later in the growing season. The supply of CO2 to leaves at higher heights appeared to be constrained by stomatal sensitivity to vapor pressure deficit (VPD) or midday leaf water potential, as indicated by increasing δ13C and VPD and decreasing midday Ψl with height. Model simulations showed that daily canopy photosynthesis was biased during the early growing season when seasonality was not accounted for, and was biased throughout the growing season when vertical gradients in LMA and Narea were not accounted for. Overall, our results suggest that leaves acclimate to light soon after leaf expansion, through an accumulation of leaf carbon, thickening of palisade layers and increased LMA, and reduction in stomatal sensitivity to Ψl or VPD. This period of light acclimation in leaves appears to optimize leaf function over time, despite height-related constraints early in the growing season. Our results imply that vertical gradients in leaf functional traits and leaf acclimation to light should be incorporated in canopy function models in order to refine estimates of canopy photosynthesis.