Characterization of Lubricant-derived Ash Deposition Within Pores of Diesel Particulate Filters Through Non-destructive Advanced Imaging Techniques

Characterization of Lubricant-derived Ash Deposition Within Pores of Diesel Particulate Filters Through Non-destructive Advanced Imaging Techniques
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Total Pages : 80
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ISBN-10 : OCLC:920897833
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Book Synopsis Characterization of Lubricant-derived Ash Deposition Within Pores of Diesel Particulate Filters Through Non-destructive Advanced Imaging Techniques by : Carolyn A. Wozniak

Download or read book Characterization of Lubricant-derived Ash Deposition Within Pores of Diesel Particulate Filters Through Non-destructive Advanced Imaging Techniques written by Carolyn A. Wozniak and published by . This book was released on 2015 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diesel Particulate Filters (DPF) have been studied for the past thirty years to trap and oxidize diesel engine exhaust gas particulate matter in order to meet increasingly stringent emission regulations. Due to engine lubrication oil inorganic additives and internal engine wear, ash particles tend to accumulate within the DPF, contributing to a sharp rise in pressure drop during the early stages of the filter life and subsequently decreasing overall engine efficiency. The objective of this work is to understand specifically how ash accumulates within the filter pores during early filter life, calling attention to the effect that the physical and geometric properties of the porous medium has on particulate deposition. Early stage ash-substrate interactions have an especially large effect on filter pressure drop, but have been difficult to measure /investigate in detail due to size, location, and sample constraints. Furthermore, an emphasis will be placed on utilizing nondestructive imaging techniques with tools such as SEM, TEM, and X-ray CT to advance the current characterization of the initial pressure drop phase. Destructive sample preparation and imaging techniques will also be used. The data acquired from this experimentation will then be used to improve upon the current state of DPF analytical pressure modeling, identify differences between various additive chemistries, and highlight potential strategies for optimizing DPF usage and design.


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