Global emission standards for engines and vehicles continue to become more stringent over time. Due to this, accurate tailpipe emission sampling remains critically important to successfully meeting these requirements. Modern diesel aftertreatment systems utilize a nitrogen oxide (NOx) sensor placed downstream of a selective catalytic reduction (SCR) catalyst to determine the tailpipe NOx concentration. Sampling inaccuracies can be introduced into the system due to nonuniformities in the distribution of NOx and ammonia coming from the SCR Outlet. One common solution to sampling inaccuracy is through the installation of a NOx sampling device, placed in the cross-section of the exhaust flow, which allows a greater area of exhaust to be sampled from and which funnels the sampled constituent directly to the probe of the sensor. To aid in the design process, computational fluid dynamics (CFD) analyses are conducted to quantitatively assess performance metrics such as tailpipe NOx sensor accuracy and component pressure drop. This design process, when conducted manually, can be time consuming. Thus, a workflow was created to couple a multidisciplinary optimization driver (modeFRONTIER) with a CFD solver (ANSYS Fluent) to automate the geometry modification, perform the CFD analyses, and optimize the geometric design of the sampling device. Optimization objectives were defined to minimize the sensor sampling error and to minimize the pressure drop over the sampling device. Key geometric features (probe hole diameters, probe hole spacing, number of sampling locations) were parameterized to be used as inputs to the design of experiments. Constraints on the parameterized geometric features were imposed to ensure creation of realistic geometric designs and to control the design space investigated.
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