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Ichiro Hagiwara

Researcher at Meiji University

Publications -  328
Citations -  2389

Ichiro Hagiwara is an academic researcher from Meiji University. The author has contributed to research in topics: Finite element method & Modal analysis. The author has an hindex of 21, co-authored 319 publications receiving 2176 citations. Previous affiliations of Ichiro Hagiwara include Tokyo Institute of Technology.

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Structural topology and shape optimization for a frequency response problem

TL;DR: In this paper, a modified optimization criterion method (MOC) was proposed to solve the frequency response optimization problem for both the optimal layout and the reinforcement of an elastic structure, which is based on a simpler idea that employs a shifted Lagrangian function to make a convex approximation.
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Sensitivity Analysis Methods for Coupled Acoustic-Structural Systems Part I: Modal Sensitivities

TL;DR: In this article, an analytical method is proposed for calculating the sensitivities of the eigenvalues and eigenvectors of coupled acoustic-structural systems for the purpose of reducing vehicle interior noise.
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Topological Optimization Technique for Free Vibration Problems

TL;DR: In this article, a topological optimization technique using the conception of OMD (Optimal Material Distribution) is presented for free vibration problems of a structure, which is derived by using a new convex generalized linearization approach via a shift parameter which corresponds to the Lagrange multiplier and the use of the dual method.
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Active control system

TL;DR: In this paper, an active control system is provided with an actuator which controls a noise and/or vibration state of an automotive vehicle, a detector which detects the noise and or vibration states of the vehicle, and a control unit which receives an output signal of the noise detector and outputs a signal to control the actuator, the control unit having a neural net which compares a control predicted value based on the output signal with a control target value so that a correction for connection weights in the neural net is carried out on the basis of the comparison result.
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Software Tools Using CSRBFs for Processing Scattered Data

TL;DR: A set of software tools that use compactly supported radial basis functions (CSRBFs) to process scattered data to solve problems concerning the processing of scattered data in such applications as reconstruction of functionally defined geometric objects, surface retouching, and shape modifications is proposed.