Data assimilation for estimation of internal state of composites

Ryosuke Matsuzaki, Junya Ishizuka, Takeshi Tachikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The present study investigated internal state estimation during heat curing of composite materials. For estimation of the internal state with surface measurements, we used a data assimilation technique that integrated temperature measurements with numerical simulations of heat curing. By integrating measurements and numerical simulation, information missing in measurements is compensated by the simulation. In addition, the unknown model parameter in numerical simulation can be identified. To validate the effectiveness of the proposed method, we conducted numerical experiments for two models: a central low thermal conductivity model and a random conductivity model. The results showed that the temperature and degree of cure can be estimated with higher accuracy using data assimilation than that without data assimilation.

Original languageEnglish
Title of host publicationECCM 2018 - 18th European Conference on Composite Materials
PublisherApplied Mechanics Laboratory
ISBN (Electronic)9781510896932
Publication statusPublished - 1 Jan 2020
Event18th European Conference on Composite Materials, ECCM 2018 - Athens, Greece
Duration: 24 Jun 201828 Jun 2018

Publication series

NameECCM 2018 - 18th European Conference on Composite Materials

Conference

Conference18th European Conference on Composite Materials, ECCM 2018
CountryGreece
CityAthens
Period24/06/1828/06/18

Fingerprint

Composite materials
Curing
Computer simulation
Surface measurement
State estimation
Temperature measurement
Thermal conductivity
Experiments
Temperature
Hot Temperature

Keywords

  • Data assimilation
  • Heat curing
  • Process simulation
  • Thermal conductivity

Cite this

Matsuzaki, R., Ishizuka, J., & Tachikawa, T. (2020). Data assimilation for estimation of internal state of composites. In ECCM 2018 - 18th European Conference on Composite Materials (ECCM 2018 - 18th European Conference on Composite Materials). Applied Mechanics Laboratory.
Matsuzaki, Ryosuke ; Ishizuka, Junya ; Tachikawa, Takeshi. / Data assimilation for estimation of internal state of composites. ECCM 2018 - 18th European Conference on Composite Materials. Applied Mechanics Laboratory, 2020. (ECCM 2018 - 18th European Conference on Composite Materials).
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Matsuzaki, R, Ishizuka, J & Tachikawa, T 2020, Data assimilation for estimation of internal state of composites. in ECCM 2018 - 18th European Conference on Composite Materials. ECCM 2018 - 18th European Conference on Composite Materials, Applied Mechanics Laboratory, 18th European Conference on Composite Materials, ECCM 2018, Athens, Greece, 24/06/18.

Data assimilation for estimation of internal state of composites. / Matsuzaki, Ryosuke; Ishizuka, Junya; Tachikawa, Takeshi.

ECCM 2018 - 18th European Conference on Composite Materials. Applied Mechanics Laboratory, 2020. (ECCM 2018 - 18th European Conference on Composite Materials).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Data assimilation for estimation of internal state of composites

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AU - Ishizuka, Junya

AU - Tachikawa, Takeshi

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Y1 - 2020/1/1

N2 - The present study investigated internal state estimation during heat curing of composite materials. For estimation of the internal state with surface measurements, we used a data assimilation technique that integrated temperature measurements with numerical simulations of heat curing. By integrating measurements and numerical simulation, information missing in measurements is compensated by the simulation. In addition, the unknown model parameter in numerical simulation can be identified. To validate the effectiveness of the proposed method, we conducted numerical experiments for two models: a central low thermal conductivity model and a random conductivity model. The results showed that the temperature and degree of cure can be estimated with higher accuracy using data assimilation than that without data assimilation.

AB - The present study investigated internal state estimation during heat curing of composite materials. For estimation of the internal state with surface measurements, we used a data assimilation technique that integrated temperature measurements with numerical simulations of heat curing. By integrating measurements and numerical simulation, information missing in measurements is compensated by the simulation. In addition, the unknown model parameter in numerical simulation can be identified. To validate the effectiveness of the proposed method, we conducted numerical experiments for two models: a central low thermal conductivity model and a random conductivity model. The results showed that the temperature and degree of cure can be estimated with higher accuracy using data assimilation than that without data assimilation.

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Matsuzaki R, Ishizuka J, Tachikawa T. Data assimilation for estimation of internal state of composites. In ECCM 2018 - 18th European Conference on Composite Materials. Applied Mechanics Laboratory. 2020. (ECCM 2018 - 18th European Conference on Composite Materials).