Soot mass estimation from electrical capacitance tomography imaging for a diesel particulate filter

dc.contributor.advisorAnwar, Sohel
dc.contributor.authorHassan, Salah E.
dc.contributor.otherEl-Mounayri, Hazim
dc.contributor.otherTovar, Andres
dc.date.accessioned2020-03-17T17:43:30Z
dc.date.available2020-03-17T17:43:30Z
dc.date.issued2020-05
dc.degree.date2020en_US
dc.degree.disciplineMechanical Engineeringen
dc.degree.grantorPurdue Universityen_US
dc.degree.levelM.S.M.E.en_US
dc.descriptionIndiana University-Purdue University Indianapolis (IUPUI)en_US
dc.description.abstractThe Electrical capacitance tomography (ECT) method has recently been adapted to obtain tomographic images of the cross section of a diesel particulate filter (DPF). However, a soot mass estimation algorithm is still needed to translate the ECT image pixel data to obtain soot load in the DPF. In this research, we propose an estimation method to quantify the soot load in a DPF through an inverse algorithm that uses the ECT images commonly generated by a back-projection algorithm. The grayscale pixel data generated from ECT is used in a matrix equation to estimate the permittivity distribution of the cross section of the DPF. Since these permittivity data has direct correlation with the soot mass present inside the DPF, a permittivity to soot mass distribution relationship is established first. A numerical estimation algorithm is then developed to compute the soot mass accounting for the mass distribution across the cross-section of the DPF as well as the dimension of the DPF along the exhaust flow direction. Firstly, ANSYS Electronic Desktop software is used to compute the capacitance matrix for different amounts of soot filled in the DPF, furthermore it also analyzed different soot distribution types applied to the DPF. The Analysis helped in constructing the sensitivity matrix which was used in the numerical estimation algorithm. Experimental data have been further used to verify the proposed soot estimation algorithm which compares the estimated values with the actual measured soot mass to validate the performance of the proposed algorithm.en_US
dc.identifier.urihttps://hdl.handle.net/1805/22344
dc.identifier.urihttp://dx.doi.org/10.7912/C2/2714
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0*
dc.subjectParticulate Matteren_US
dc.subjectSoot Estimatingen_US
dc.subjectElectrical Capacitance Tomographyen_US
dc.subjectLinear Back projectionen_US
dc.subjectDiesel Particulate Filteren_US
dc.subjectANSYS Electronicen_US
dc.titleSoot mass estimation from electrical capacitance tomography imaging for a diesel particulate filteren_US
dc.typeThesisen
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