〓 Research Area : Numerical Analysis of Flow Phenomena

Data-driven computing for prediction and control ofwall-bounded turbulenceWall-bounded turbulence significantly contributes to heat transfer and drag on
a wall surface, and the prediction and control of turbulent phenomena leads
to the efficient use of energy, and the time-series data of turbulent flow fields
have been obtained by the numerical simulation. In the future, it is necessary
to develop the data-driven prediction and control technique based on a deep
understanding of the turbulent flow for the wide application in engineering.
We will carry out numerical calculations for various engineering problems andchallenge the turbulent flow problem, which is so-called the final problem ofclassical mechanics, using new techniques of information science such as
The coherent vortical structures in turbulent plane Poiseuille flow.
machine learning in addition to statistical analysis and dynamic system theory. Flow is from left to right. (red) cloclwise, (blue) anti-clockwise vortices.

Data-driven dynamical system for modeling and optimization of nonlinear phenomena〓 Assoc. Prof.
SEKIMOTO Atsushi

We can consider turbulent flow as a vector with a large dimension of freedom and a dynamical system, then we can numerically find invariant solutions such as equilibrium solutions and periodic orbits of Navier‐Stokes equations or turbulence model equations. Understanding the role of invariant
solutions in the turbulent flow phenomenon would provide some insights into the developmentof turbulence models and flow control techniques. The dynamical system approach can also beapplied for the understanding of the mathematical model itself obtained by machine learning
such as deep learning, since it must be common for the phenomenon with strong nonlinearity.
Our research aims are following:development of simulation technique of the complicated process in which we can obtain thedata of real phenomena, such as multiphase flow, chemical reaction, combustion, mixing of various particles, separation and aggregation processes, although the knowledge of macroscopic
or statistical behavior is limited or the detailed simulation is not realistic; and then, development
The stratified homogeneous shear turbulence.
(Red, blue), low and high density fluctuation, (gray) of the technique of optimization and control method which can be applied in a wide range of thevortical structures.
engineering field.

〓 Research Area : Environmental Statistics

Statistical Science for environmental and life science
In modern society, we are required to have grounds forjudgement in various situations. For example, in order tosolve environmental issues, it is important to have calm discussions with showing scientific evidences, without being
influenced by personal feelings.
The statistical science provides the most effective meansof showing such grounds objectively. We wish to contributeto solving issues on environmental and life science throughresearches on statistical science, with making use of computer ability developing drastically.

Statistical modeling and computation for analyzing environmental and epidemiological data〓 Prof.
SAKAMOTO Wataru

We develop statistical models foranalyzing complicated phenomena that occur in environmental andlife science, such as penalized
spline regression models, mixed
effect models, and Markov random fields, and develop methodsof selecting an optimal model.
The figure shows a graphical model for spatial analysis of disease
mapping data.

Graduate School of Environmental and Life Science, Okayama University33