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Journal of Flow Visualization and Image Processing

Published 4 issues per year

ISSN Print: 1065-3090

ISSN Online: 1940-4336

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.6 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.6 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00013 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.14 SJR: 0.201 SNIP: 0.313 CiteScore™:: 1.2 H-Index: 13

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ANALYSIS OF IN-CYLINDER FLOW FIELDS USING PROPER ORTHOGONAL DECOMPOSITION-BASED QUADRUPLE DECOMPOSITION

Volume 30, Issue 3, 2023, pp. 57-93
DOI: 10.1615/JFlowVisImageProc.2022044063
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ABSTRACT

In order to meet increasingly stringent emission norms coupled with a heightened requirement of performance, there has been an unabated effort toward improvement in the combustion process of modern internal combustion engines. One of the major impediments of enhanced combustion in spark-ignited port fueled engines are combustion variations. These variations are especially dominant at low-load, low-speed operations. Cycle-to-cycle variation (CCV) in in-cylinder flow fields is one of the major contributors of such combustion variations. Therefore, in this work, CCV of in-cylinder flow fields of an optical port fuel injection engine was analyzed at part load (50% throttle opening) and low speed (1200 rpm) with the help of proper orthogonal decomposition. Flow fields were subsequently decomposed into four components, namely, mean, coherent, transition, and turbulent parts. CCV of flow fields was studied using several metrics based on kinetic energy and the relevance index. It was found that the share of mean energy is a better metric for CCV quantification based on kinetic energy. Interestingly, it was observed that the mean part, though consistent in its flow structure for various cycles, has a lot of variation in kinetic energy at early compression stroke. Also, a weak mean flow coupled with a strong coherent flow structure opposing the mean flow produces the largest deviation in a flow field from its corresponding ensemble-averaged field. Furthermore, even though the coherent and transition parts are comprised of comparable energy, it was the coherent part that showed large variations in kinetic energy. Hence, the mean and coherent parts are mainly responsible for CCV in flow fields.

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