CFD Simulation of Soot Dynamics in the Exhaust System of an Engine to Meet Particulate Standards of 2020 and Beyond

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Abstract

This study presents a computational model for the detailed prediction of particulate matter size distribution in thermal precipitators systems by coupling CFD with population balance models (ACRi, 2016 [1]; Ni et al. in Fuel 228:215–225, 2018 [23]; Rajagopal et al. in Energy for propulsion. Springer, Singapore, pp. 345–364, 2018 [31]; Rodrigues et al. in Combust Flame 190:477–499, 2018 [32]). Detailed size distributions of particulate matter are very helpful in the design of after-treatment devices for removing soot from vehicle exhaust systems and enabling vehicles to meet emission norms of 2020 and beyond (Di Natale et al. in Fuel Process Technol 175:76–89, 2018 [22]). An existing and well-validated, reacting flow, Navier-Stokes solver (ACRi, 2016 [1]) is enhanced with numerical schemes to solve the population balance equations using the sectional method (Rajagopal et al. in Energy for propulsion. Springer, Singapore, pp. 345–364, 2018 [31]). This numerical scheme takes account of particle aggregation through the Fuchs kernel for transition regime, and deposition processes, including gravitational settling, thermophoresis, and inertial deposition. The numerical models for each of the aerosol processes were validated with analytical or numerical solutions. The combined particulate flow model was validated against results from open literature for deposition of sodium chloride and sodium fluorescein particles in a rectangular duct, and deposition of soot particles in a plate precipitator under conditions relevant to diesel engine exhaust systems. The validated soot tool would find application in gas turbine combustor as well with appropriate combustion models.

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Rajagopal, P. S., Magar, A., Shinde, J., Rao, M. M., & Runchal, A. K. (2021). CFD Simulation of Soot Dynamics in the Exhaust System of an Engine to Meet Particulate Standards of 2020 and Beyond. In Green Energy and Technology (pp. 463–479). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-5667-8_18

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