Library / Zero-dimensional Modelling

Zero-dimensional Modelling Zero-dimensional modelling of a producer gas-based reciprocating engine From the article: A zero-dimensional modelling study has been conducted using wrinkled flame theory for flame propagation to understand the in-cylinder pressure behaviour with time in a reciprocating internal combustion engine. These are compared with experiments conducted on the engine operated on biomass derived from producer gas and air mixture. The required inputs on the laminar burning velocity and turbulence parameters are obtained from separate studies. The data related to laminar burning velocity for producer gas and air mixture at thermodynamic conditions typical of unburned mixture in an engine cylinder were obtained from one-dimensional flame calculations. The turbulence parameters were obtained by conducting a three-dimensional computational fluid dynamics study on a bowl-in-piston geometry to simulate motored or non-firing conditions. The above mentioned data were used in the zero-dimensional model to make pressure– time (p–u) computation over the complete engine cycle, for a range of test cases at varying compression ratio (CR) and ignition timing. The computational results matched reasonably well with experimental p–u curves at advanced ignition timing at all CRs. The error in computed indicated power (IP) at advanced ignition setting (188–278 CA) is around 3–4 per cent for CR ¼ 17.0 and 11.5, and between 6 and 9 per cent for CR ¼ 13.5. However, at less advanced ignition setting, the error in computed IP is larger and this is attributed to enhanced fluid dynamic effect due to reverse squish effect. And, whenever major part of the combustion occurred during this period, the deviation in the computed result appeared to be larger. This model has also been used to predict output of a commercially available producer gas engine of 60 kW. The optimum ignition timing on this particular engine was experimentally found to be 228–248 before top centre. The zero-dimensional model has been used in a predictive mode and results compared with brake power under wide throttle open condition. About Us Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Vestibulum tortor quam, feugiat vitae, ultricies eget, tempor sit amet, ante. Pellentesque habitant morbi tristique senectus. Address Twitter, Inc. 795 Folsom Ave, Suite 600 San Francisco, CA 94107 P: (123) 456-7890

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