• Journal of Mechanical Science and Technology
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• v.20 no.9
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• pp.1459-1474
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• 2006

The present study is focused on the development of the RIF (Representative Interactive Flamelet) model which can overcome the shortcomings of conventional approach based on the steady flamelet library. Due to the ability for interactively describing the transient behaviors of local flame structures with CFD solver, the RIF model can effectively account for the detailed mechanisms of $NO_x$ formation including thermal NO path, prompt and nitrous $NO_x$ formation, and reburning process by hydrocarbon radical without any ad-hoc procedure. The flamelet time of RIFs within a stationary turbulent flame may be thought to be Lagrangian flight time. In context with the RIF approach, this study adopts the Eulerian Particle Flamelet Model (EPFM) with mutiple flamelets which can realistically account for the spatial inhomogeneity of scalar dissipation rate. In order to systematically evaluate the capability of Eulerian particle flamelet model to predict the precise flame structure and NO formation in the multi-dimensional elliptic flames, two methanol bluffbody flames with two different injection velocities are chosen as the validation cases. Numerical results suggest that the present EPFM model has the predicative capability to realistically capture the essential features of flame structure and $NO_x$ formation in the bluff-body stabilized flames.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1837-1845
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• 2015

The longitudinal velocity is necessary for accurate vehicular positioning in urban environment. The pitch angle, which is a road slope, should be calculated to acquire the longitudinal velocity. However, it is impossible to consider very accurate pitch, when using a sensor and an algorithm. That's why process noise and positioning stimation error of IMU should be adjusted to the driving environment and fuse GPS, OBD data with ACF which consist of AKF, CF in this paper. Then, final pitch angle which is appropriate for driving environment is estimated by IMMKF in order to optimize the system model according to road slope models.