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.

Effects of fixed night shift work on 24 hour blood pressure regulation, state anxiety levels and total sleep time

Nearly 22 million Americans operate as shift workers, and shift work has been linked to the development of cardiovascular disease (CVD). This study is aimed at identifying pivotal risk factors of CVD by assessing 24 hour ambulatory blood pressure, state anxiety levels and sleep patterns in 12 hour fixed shift workers. We hypothesized that night shift work would negatively affect blood pressure regulation, anxiety levels and sleep patterns. A total of 28 subjects (ages 22-60) were divided into two groups: 12 hour fixed night shift workers (n=15) and 12 hour fixed day shift workers (n=13). 24 hour ambulatory blood pressure measurements (Space Labs 90207) were taken twice: once during a regular work day and once on a non-work day. State anxiety levels were assessed on both test days using the Speilberger’s State Trait Anxiety Inventory. Total sleep time (TST) was determined using self recorded sleep diary. Night shift workers demonstrated increases in 24 hour systolic (122 ± 2 to 126 ± 2 mmHg, P=0.012); diastolic (75 ± 1 to 79 ± 2 mmHg, P=0.001); and mean arterial pressures (90 ± 2 to 94 ± 2mmHg, P<0.001) during work days compared to off days. In contrast, 24 hour blood pressures were similar during work and off days in day shift workers. Night shift workers reported less TST on work days versus off days (345 ± 16 vs. 552 ± 30 min; P<0.001), whereas day shift workers reported similar TST during work and off days (475 ± 16 minutes to 437 ± 20 minutes; P=0.231). State anxiety scores did not differ between the groups or testing days (time*group interaction P=0.248), suggesting increased 24 hour blood pressure during night shift work is related to decreased TST, not short term anxiety. Our findings suggest that fixed night shift work causes disruption of the normal sleep-wake cycle negatively affecting acute blood pressure regulation, which may increase the long-term risk for CVD.

Evaluation of factors affecting speed perception in a driving simulator

The present study was conducted to determine the effects of different variables on the perception of vehicle speeds in a driving simulator. The motivations of the study include validation of the Michigan Technological University Human Factors and Systems Lab driving simulator, obtaining a better understanding of what influences speed perception in a virtual environment, and how to improve speed perception in future simulations involving driver performance measures. Using a fixed base driving simulator, two experiments were conducted, the first to evaluate the effects of subject gender, roadway orientation, field of view, barriers along the roadway, opposing traffic speed, and subject speed judgment strategies on speed estimation, and the second to evaluate all of these variables as well as feedback training through use of the speedometer during a practice run. A mixed procedure model (mixed model ANOVA) in SAS® 9.2 was used to determine the significance of these variables in relation to subject speed estimates, as there were both between and within subject variables analyzed. It was found that subject gender, roadway orientation, feedback training, and the type of judgment strategy all significantly affect speed perception. By using curved roadways, feedback training, and speed judgment strategies including road lines, speed limit experience, and feedback training, speed perception in a driving simulator was found to be significantly improved.