(formerly) R & D in Media Computing, Academic Center for Computing and Media Studies

Staff

Naoshi NISHIMURA, Professor, Dr. Eng.


  Education
    B.Eng.(1977), M.Eng.(1979), Dr.Eng.(1988), Kyoto Univ.
    in Civil Eng. 
  Field of interest
    Applied Mechanics, Computational Mechanics, Boundary Integral
    Equation Method
  Major Courses Taught
    Engineering Mathematics B1, Numerical Analysis, Synthetic Complex Dynamical Systems B, Fundamentals of Complex Systems A
Projects



I. Applications of Integral Equation Method to Initial- Boundary Value
Problems.

  Boundary Integral Equation Method (BIEM), also called Boundary
Element Method (BEM), is one of the most promising methods of
numerical analysis for initial- boundary value problems, and is
applicable to a wide range of practical problems in engineering. This
project aims at studying mathematical foundations as well as numcrical
techniques for BIEM, and at applying this method to various problems
of practical interest. Some basic problems such as mathematical
principles, supercomputing algorithm and high accuracy numerical
schemes are investigated. This project also includes studies on fast
BIEM based on Fast Multipole Methods (FMM) and the use of wavelet
basis.

II. Studies on Non-Destructive Evaluation with Ultrasonics. 

  This project investigates NDE techniques to detect cracks and
cavities in materials using ultrasound. Particular attention is paid
to laser techniques of measuring velocities on the surface of the
specimen. This technique enables one to determine the waveform of the
reflected waves from defects. The combined use of the experimental
technique thus developed and the inverse analysis based on BIEM
determines the location and the shape of defects.

III. Studies on Inverse Problems. 

  This project aims at developing numerical techniques related to nonlinear
inverse problems of determining locations and shapes of unknown domains or
boundaries from measurements. Some of main interests in this projects are
(a) the computation of shape derivatives (b) effective algorithms for
computing costs and their shape derivatives (c) efficient implementations
of the inversion (d) applications to NDE.