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To resolve two major problems of conventional CFD-based shape optimization technology: (1) dependence of the outcome on the selection of design parameters, and (2) high computational costs, two types of innovative inverse analysis technologies based on a mathematical theory called the Adjoint Method were developed in previous studies for maximizing an arbitrary hydrodynamic performance aspect as the cost function: surface geometry deformation sensitivity analysis to identify the locations to be modified, and topology optimization to generate an optimal shape. Furthermore, these technologies were extended to transient flows by the application of the transient Adjoint Method theory. However, there are many cases around flow path shapes in vehicles where performance with respect to heat or concentration, such as the total amount of heat transfer or the flow rate of a specific gas component, is very important.

Conventional CFD-based shape optimization technology that uses parametric shape modification and optimal solutions searching algorithms has the two problems: (1) outcome of optimized shapes depend on the selection of design parameters made by the designer, and (2) high computational costs. To resolve those problems, two innovative inverse analysis technologies based on the Adjoint Method were developed in previous study: surface geometry deformation sensitivity analysis to identify the locations to be modified, and topology optimization to generate an optimal shape for maximizing the cost function in the constrained design space. However, these technologies are only applicable to steady flows. Since most flows in a vehicle (such as engine in-cylinder flow) are transient, a practical technology for surface geometry sensitivity analysis has been developed based on the Transient Adjoint Method.

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 analysis of spray characteristics is important to examine the combustion characteristics of DI (Direct Injection) gasoline engines because the fuel-air mixture formation is controlled by spray characteristics and in-cylinder gas motion. However, the mixture formation process has not been well clarified yet. In this study, the characteristics of a fan-shaped spray caused from a slit-type injector, such as the droplet size, its velocity and the droplet distribution were simultaneously measured on a 2D plane by using improved ILIDS (Interferometric Laser Imaging for Droplet Sizing) method. ILIDS method is an optical measurement technique using interference fringes by illuminating a transparent spherical particles with a coherent laser light. In the measurement of the wall-impinging spray, effects of the distance to the wall and the wall temperature on the spray characteristics were investigated.

The behavior of spray injections to turbulent duct flows from a slit injector for direct-injection gasoline engines was investigated using a combination of large eddy simulation (LES) and Lagrangian discrete droplet model (DDM). As a result, diffusion of droplets in stronger turbulent flows was observed at a later stage of the injection. Moreover, we compared calculation and experimental results by generating a pseudo-particle image from the calculation result.