0328 Fundamental numerical methods towards accurate, efficient and practical simulations in industrial, environmental and biological applications

  • Satoshi Ii, Tokyo Metropolitan University
  • Ryosuke Akoh, Okayama University
  • Chungang Chen, Xi’an Jiaotong University
  • Xingliang Li, China meteorological administration

In numerical simulations of industry, environment and biology, a fundamental study for numerical technology is indispensable. For example, high-order discretization shows a strong power in terms of numerical error for smooth problems, but it causes deterioration of the numerical accuracy due to the Gibbs phenomenon for a discontinuous problem; in multiphase flow analysis using a fixed mesh system, a method for capturing a quantity representing the medium phase is required without numerical diffusion and oscillation; in an analysis including long-term integration, appropriate discretization methods and computational approaches are required so that numerical damping and oscillation do not occur and the physical conserved quantity is maintained; and also, analyses with massively multiple conditions require a practical and efficient numerical method.

In practical problems, there are many cases facing numerical difficulty such as moving interfaces with mass transfer, multiphysics systems of flow and chemical reaction, unstable flow due to interaction between shock waves and bubbles, and strong nonlinearity in ocean and atmospheric flows, and multi-scale coupling analysis. Although there are such numerical analysis problems and solutions in different fields, there are many similarities as numerical methods.

This minisymposium is open for research topics on fundamental numerical methods in high-accurate, efficient and practical simulations for various applications such as industry, environment and biology. We aim to share the numerical methods being worked on in each field and develop each other. Here, we also welcome topics working on not only basic numerical methods, but also methods using approaches that are useful in actual problems such as data assimilation and machine learning, and applications for actual problems in each field with these novel numerical methods and techniques.

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