フーリエ変換に基づく緩和スペクトルの数値計算手法の構築

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タイトル別名
  • NUMERICAL CALCULATION OF RELAXATION SPECTRUM BASED ON FOURIER TRANSFORM
  • フーリエ変換に基づく緩和スペクトルの数値計算手法の構築 : 木材の粘弾性に関する研究
  • フーリエ ヘンカン ニ モトズク カンワ スペクトル ノ スウチ ケイサン シュホウ ノ コウチク : モクザイ ノ ネンダンセイ ニ カンスル ケンキュウ
  • Study on viscoelasticity of wood
  • 木材の粘弾性に関する研究

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<p> The range of use of timber has expanded rapidly in recent years, and it is expected that the timber structures will become larger and taller in the future. As the scale increases, it is possible to apply a composite or hybrid structures which combines other material such as steel. It is difficult to accurately predict the burden stress of changing wood from moment to moment, and the evaluation of viscoelasticity of wood is indispensable. Based on these backgrounds, we have studied the purpose of clearly positioning viscoelasticity of wood in the rheology field.</p><p> </p><p> In this paper, we examined a method for obtaining the relaxation spectrum from static test conditions, which are a common problem in the rheology field. The method studied is not based on the current approximate solution, but based on the Fourier transform. To adopt this method, it is necessary to solve the ill-posed problem in numerical computation. We showed that it can be solved by adding three ideas; noise rejection, ensuring continuity and adding calculation assistance. These ideas are due to numerical problems associated with the discrete Fourier transform, and the optimal method for calculating the relaxation spectrum is shown in this paper. The study began with a numerical experiment using a simple Gaussian function, and then verified the applicability to a complex relaxation spectrum combining multiple Gaussian functions.</p><p> </p><p> In addition, we assumed that there is significant data only in a limited calculation range of about 3 months as experimental data that can be actually obtained, and we also examined the calculation method. It was confirmed that the required calculation accuracy was ensured by numerical tests that assumed experimental data contained measurement noise. In the case of limited data containing such noise, the conventional approximate solution method significantly decreases the calculation accuracy. On the other hand, it was confirmed that the calculation method based on the Fourier transform shown in this paper can obtain appropriate calculation results regardless of the presence or absence of noise.</p>

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