This strategic program focuses on fluid dynamics, fluid mechanics, fluid engineering and related elds. This strategic program is to establish a common fluid research base aiming at construction of constitutive law integrating mathematical and physical approaches and a data-driven approach as a common goal. This proposes research and development strategy to promote creation of new scientific principles and basic technologies for industrial application at the same time. Note that, in this strategic program, a common fluid research base includes research in science and technology in the fluid-related fields as well as research programs, research personnel and a research environment.

Until now, in fluid-related fields, a significant amount of specific research to respond to the demand on its outcome has been implemented. However, much less study has been done on the universal turbulence model and the nature of fluid is yet to be revealed. Therefore, individual issues are being addressed in each application field by using parameters. In order to break through this barrier, a theme, which is not limited to specific applied research but also includes cross-disciplinary common phenomena and examples, needs to be set. Moreover, in addition to specific research and cross-disciplinary research, an institutional design to promote their interaction is essential. The common knowledge obtained from them can be applied to related elds and contribute to innovation. The following are three proposals for the specific research and development issues.

• 1) Construction of constitutive law integrating mathematical and physical approaches and a data-driven approach and elucidation of complex flow phenomena
• 2) Prediction and control of complex flow phenomena based on the understanding of 1)
• 3) Applied research (energy, environment, aircraft, bio, medical and so on)

In recent years, improvement of measuring and analytical equipment has realized the acquisition of fluid big data and enhancement of computing power has realized sophisticated direct numerical simulation. As a result of germinating research during the last few years, it is becoming clear that machine learning is suitable for such fluid big data analytics.

In the target field of this program, experiment, theory and data science including numerical calculation and machine learning are all entering a new phase. It is necessary to coordinate them closely and to integrate them with the existing knowledge such as the laws of physics, theories and empirical knowledge toward elucidation of complex flow phenomena. Moreover, it is necessary to nd universality in principles to apply it to prediction and control of fluid flow.

Originally, fluid flow problems have been driving development of mathematics in many aspects. By promoting this eld, a spillover effect to applied mathematics can also be expected through extraction of new mathematical description methods, concepts, discrete structures, algebraic structures, geometric structures and so on, and through their interaction with conventional methods. In addition, since it is insufficient to adapt machine learning to flow phenomena as a mere tool, it is also expected that the knowledge of fluid dynamics would be proactively introduced in the machine learning side through development of machine learning devoted to flow phenomena and so on. It is necessary to incorporate the global trend of mathematics and information science to make fluid science needs and seeds of mathematics and physics, to search for new scientific principles in both elds and to evolve together.

As for the method of promotion, it is important to construct a network with elds related to elucidation, prediction and control of complex flow phenomena. Moreover, by integrating physical and mathematical ideas and machine learning, construction of knowledge to elucidate universal principles of complex flow phenomena and realization of advanced prediction and integrated control are aimed at.

In December 2020, the Green Growth Strategy was formulated aiming at achieving carbon neutrality in 2050. In the elds indispensable for carbon neutrality such as offshore wind power generation, hydrogen-fired power generation, vehicles, aircraft and vessels, it is requested to accelerate technology establishment and social implementation. Improvement of efficiency of wind and hydrogen- red power generation and highly efficient energy use for vehicles, aircraft and vessels are almost always related to fluid-related fields. In addition, fluid-related fields are among the core technologies for manufacturing; therefore, it is also important to strengthen the international competitiveness of Japanese industry.

The importance of fluid-related elds has been recognized also in other elds. For example, the dispersion simulation of the coronavirus by the supercomputer Fugaku visualizes invisible droplets and air flows, which is widely utilized for risk reduction measures of coronavirus infection. This simulation is implemented by utilizing the computing power of the supercomputer Fugaku, and by incorporating detailed physical models adequately therein. The basic science of fluid dynamics is the core of the simulation. Moreover, damage caused by typhoons and sudden downpours almost every year can also be cited as examples closely related to fluid science. In order to minimize the damage, construction of an early prediction system for disaster prevention and reduction incorporating a development mechanism of cumulonimbus is an urgent issue.

This common fluid research base is an important scientific and technological basis for realization of a carbon neutral society by 2050, for strengthening of the industrial competitiveness of Japan, and also for construction of a safe and secure society. Including a wide range of scientific and industrial elds, its promotion in a medium- to long-term timeline is desirable.