3D CFD & Combustion Engineer, Ford Otomotiv Sanayi
Anıl Can Ağar is working as a CFD Analyst at Engine Computer Aided Engineering Department of Ford Otomotiv Sanayi A.S. in Turkey. He has graduated from Heat transfer and Fluid Flow Masters Programme of Istanbul Technical University Graduate School of Science, Engineering and Technology, in 2015. He is experienced in multi phase flows, exhaust gas dispersion, diesel combustion and project management. His current research interest multi objective geometry optimization of flow related structures.
Speeches
Compressor is one of the key components of an Air Induction System(AIS) of a diesel engine and have detrimental effect on engine’s performance. Compressor’s performance is effected by its design, operating conditions driven by engine and flow characteristics at its inlet. The flow behavior at compressor inlet is determined by design of the upstream components. In most of the cases, flow reaches to the compressor is ill-conditioned according to restrictions of design space. This situation can lead poor Noise-Vibration-Harshness (NVH) performance and low compressor efficiency. In order to tackle the problem, using a flow conditioning device, a structure enhances the flow with addition prewhirl at upstream of compressor, is deemed to be an effective method. The study is based on design and optimization of such device for a diesel engine to be installed into a Ford truck.
In order to meet and exceed the performance targets, the flow metrics such as swirl ratio, flow uniformity, flow eccentricity should be optimized in tandem with pressure loss. To perform this optimization in a robust, fast and automatized manner, a workflow is built by using ModeFrontier. The workflow incorporates CATIA, StarCCM+ and combines two operating systems (Windows and Linux) and automatized up to the push button level. Geometry is automatically updated based on the design of experiment (DoE) matrix in batch mode and CFD simulation is performed with aid of Javascripts. Upon completion of DoE, an optimization scheme using Genetic Algorithms built in ModeFrontier is used to attain a robust flow conditioning device.
The workflow is completed with minimum user interference, highly decreased delivery time, complete fulfillment of flow characteristics and acceptable rise in pressure loss. The developed methodology and scripts can also be used as surrogate for projects ahead.