https:\/\/doi.org\/10.2514\/1.B35943<\/a><\/p>\n\n\n\nAbstract<\/h2>\n\n\n\n
Aviation-produced particulate matter has a direct impact on climate, atmospheric composition at flight altitudes, and local air quality in the vicinity of airports. The formation of soot and gaseous aerosol precursors inside the combustor and during gas expansion in turbine stages and nozzles must be addressed before the real impact of aircraft engines with respect to particulate matter emissions can be assessed. To design strategies to reduce particulate matter emissions, the development of a zero-\/one-dimensional gas-turbine model is proposed, taking into account combustor and postcombustor flow operating over the landing\/takeoff cycles with a detailed kerosene jet-A1 kinetics scheme, including a soot-dynamics model. This approach is very efficient computationally and may be clearly satisfying for parametric studies or in a predesign step. First, the model\u2019s predictive capacity for capturing the main features of gas-turbine combustion as well as the expansion of combustion products in the turbine and nozzle has appeared acceptable as concentrations of International Civil Aviation Organization standard emissions and sulfur-species conversion agree reasonably well with measurements, whatever the operating conditions. In particular, the results showed that\u00a0SO3\u00a0and\u00a0H2SO4\u00a0concentrations still exhibited variations in the postcombustor zone until exiting the engine nozzle. Using a revised surface-growth mechanism combined with the condensation of six major polycyclic aromatic hydrocarbons has significantly improved predictions of computed particles diameters. Such values now agree very closely with experimental data collected over the landing\/takeoff cycle, whereas the concentration of polycyclic aromatic hydrocarbons, as well as ethylene and benzene, were better predicted for the highest power setting (i.e., takeoff and climb configurations).<\/p>","protected":false},"excerpt":{"rendered":"
Auteur(s): J. Bisson, Patrice Seers, M. Huegel, Fran\u00e7ois Garnier Date de publication: Janvier 2016 Journal: AIAA Journal of Propulsion and Power DOI: https:\/\/doi.org\/10.2514\/1.B35943<\/a> Abstract Aviation-produced particulate matter has a direct impact on climate, atmospheric composition at flight altitudes, and local air quality in the vicinity of airports. The formation of soot and gaseous aerosol precursors […]<\/p>\n","protected":false},"author":238496019,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_crdt_document":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"_wpas_customize_per_network":false},"categories":[6359],"tags":[],"class_list":["post-1134","post","type-post","status-publish","format-standard","hentry","category-article-de-journal"],"yoast_head":"\n(2016) Numerical Prediction of Gaseous Aerosol Precursors and Particles in an Aircraft Engine - Chaire A\u00e9ropropulsion ETS<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/aeroetslab.ca\/en\/2023\/11\/22\/2016-numerical-prediction-of-gaseous-aerosol-precursors-and-particles-in-an-aircraft-engine\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"(2016) Numerical Prediction of Gaseous Aerosol Precursors and Particles in an Aircraft Engine - Chaire A\u00e9ropropulsion ETS\" \/>\n<meta property=\"og:description\" content=\"Auteur(s): J. 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