Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Experimental/observational research and simulation research are important pillars for R&D. Data assimilation is a research field that connects experiments/observations and simulations and maximizes the use of information from both. Simulations are calculated according to the governing equations and can reproduce detailed phenomena that cannot be obtained by experiments or observations, but there is a gap between actual experiments and observations due to uncertainties in the model and initial boundary conditions. On the other hand, experiments and observations are real data, and while they are trustworthy data extracted from the real world, it is often difficult to prepare a large number of measurement points and to make measurements that are dense in terms of area and space. Data assimilation makes it possible to integrate simulations and experimental/observational data in a statistically appropriate manner, thereby compensating for each other’s deficiencies and achieving better forecasts. Until now, data assimilation has been mainly utilized in the field of meteorology and oceanography, and the know-how to utilize it for engineering design has been limited. In this presentation, applications of data assimilation to fluid engineering will be demonstrated.