Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.

ENHANCING COMMUNICATION THROUGH SUCCESSFUL REPAIR: EXAMINING FLUENCY AND MECHANISMS FOR SYNTACTIC PROGRESS IN APHASIC AND NON-APHASIC SPEECH

The fields of Rhetoric and Communication usually assume a competent speaker who is able to speak well with conscious intent; however, what happens when intent and comprehension are intact but communicative facilities are impaired (e.g., by stroke or traumatic brain injury)? What might a focus on communicative success be able to tell us in those instances? This project considers this question in examining communication disorders through identifying and analyzing patterns of (dis) fluent speech between 10 aphasic and 10 non-aphasic adults. The analysis in this report is centered on a collection of data provided by the Aphasia Bank database. The database’s collection protocol guides aphasic and non-aphasic participants through a series of language assessments, and for my re-analysis of the database’s transcripts I consider communicative success is and how it is demonstrated during a re-telling of the Cinderella narrative. I conducted a thorough examination of a set of participant transcripts to understand the contexts in which speech errors occur, and how (dis) fluencies may follow from aphasic and non-aphasic participant’s speech patterns. An inductive mixed-methods approach, informed by grounded theory, qualitative, and linguistic analyses of the transcripts functioned as a means to balance the classification of data, providing a foundation for all sampling decisions. A close examination of the transcripts and the codes of the Aphasia Bank database suggest that while the coding is abundant and detailed, that further levels of coding and analysis may be needed to reveal underlying similarities and differences in aphasic vs. non-aphasic linguistic behavior. Through four successive levels of increasingly detailed analysis, I found that patterns of repair by aphasics and non-aphasics differed primarily in degree rather than kind. This finding may have therapeutic impact, in reassuring aphasics that they are on the right track to achieving communicative fluency.