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Computational fluid dynamics (CFD) shape optimization technology is playing an increasingly significant role in the development of products that satisfy various demands, including trade-off relationships. It offers the possibility of designing or improving product shape with respect to a given cost function, subject to geometrical constraints. However, conventional CFD shape optimization technology that uses parametric shape modification has two following issues: (1) expensive computational cost to obtain the final shape, (2) performance variations of the obtained shape depends on the skill or experience of the designer who determined the locations to be modified. In this study, to resolve those problems, an efficient shape optimization technology was developed that uses the adjoint method to perform sensitivity analysis of a cost function on the design parameters. It is composed of a combination of topology optimization and surface geometry optimization.

The use of predictive models in the study of Internal Combustion Engines (ICE) allows reducing developing cost and times. However, those models are challenging due to the complex and multi-phase phenomena occurring in the combustion chamber, but also because of the different spatial and temporal scales in different components of the injection systems. This work presents a methodology to accurately simulate the spray by Discrete Droplet Models (DDM) without experimentally measuring the injector mass flow rate and/or momentum flux. Transient nozzle flow simulations are used instead to define the injection conditions of the spray model. The methodology is applied to a multi-hole Gasoline Direct injection (GDi) injector. Firstly, the DDM constant values are calibrated comparing simulation results to Diffused Back-light Illumination (DBI) experimental technique results. Secondly, transient nozzle flow simulations are carried out.