Estimation of a stochastic spatio-temporal model of the flow-front dynamics with varying parameters

Michael Nauheimer; Rishi Relan; Uffe Høgsbro Thygesen; Henrik Madsen

doi:10.1063/1.5045960

Estimation of a stochastic spatio-temporal model of the flow-front dynamics with varying parameters

Michael Nauheimer^*, Rishi Relan, Uffe Høgsbro Thygesen, Henrik Madsen

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

For control and monitoring purposes, knowledge of the current state of the flow-front in a vacuum assisted resin transfer moulding (VARTM) process is essential. The permeability of the medium and viscosity of the epoxy can change during the infusion process. Especially for online monitoring of the infusion process there is a need for a fast and fairly accurate, possibly virtual sensor system which can handle such parameter variations. Stochastic-differential equations (SDEs) based estimation of the flow-front dynamics can offer a good trade-off between physics and data-driven estimators. In this paper, we analyze the effect of parameter variations on an SDE based spatio-temporal estimator of the flow-front dynamics in a VARTM process.

Original language	English
Article number	020098
Journal	AIP Conference Proceedings
Volume	1981
Issue number	1
Number of pages	5
ISSN	0094-243X
DOIs	https://doi.org/10.1063/1.5045960
Publication status	Published - 2018
Event	9^th International Conference on Times of Polymers and Composites - Hotel Continental Terme , Ischia, Italy Duration: 17 Jun 2018 → 21 Jun 2018

Conference

Conference	9^th International Conference on Times of Polymers and Composites
Location	Hotel Continental Terme
Country/Territory	Italy
City	Ischia
Period	17/06/2018 → 21/06/2018

Keywords

Partial differential equations
Stochastic differential equations
Varying parameters
Parameter estimation

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title = "Estimation of a stochastic spatio-temporal model of the flow-front dynamics with varying parameters",

abstract = "For control and monitoring purposes, knowledge of the current state of the flow-front in a vacuum assisted resin transfer moulding (VARTM) process is essential. The permeability of the medium and viscosity of the epoxy can change during the infusion process. Especially for online monitoring of the infusion process there is a need for a fast and fairly accurate, possibly virtual sensor system which can handle such parameter variations. Stochastic-differential equations (SDEs) based estimation of the flow-front dynamics can offer a good trade-off between physics and data-driven estimators. In this paper, we analyze the effect of parameter variations on an SDE based spatio-temporal estimator of the flow-front dynamics in a VARTM process.",

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author = "Michael Nauheimer and Rishi Relan and Thygesen, {Uffe H{\o}gsbro} and Henrik Madsen",

year = "2018",

doi = "10.1063/1.5045960",

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volume = "1981",

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AU - Nauheimer, Michael

AU - Relan, Rishi

AU - Thygesen, Uffe Høgsbro

AU - Madsen, Henrik

PY - 2018

Y1 - 2018

N2 - For control and monitoring purposes, knowledge of the current state of the flow-front in a vacuum assisted resin transfer moulding (VARTM) process is essential. The permeability of the medium and viscosity of the epoxy can change during the infusion process. Especially for online monitoring of the infusion process there is a need for a fast and fairly accurate, possibly virtual sensor system which can handle such parameter variations. Stochastic-differential equations (SDEs) based estimation of the flow-front dynamics can offer a good trade-off between physics and data-driven estimators. In this paper, we analyze the effect of parameter variations on an SDE based spatio-temporal estimator of the flow-front dynamics in a VARTM process.

AB - For control and monitoring purposes, knowledge of the current state of the flow-front in a vacuum assisted resin transfer moulding (VARTM) process is essential. The permeability of the medium and viscosity of the epoxy can change during the infusion process. Especially for online monitoring of the infusion process there is a need for a fast and fairly accurate, possibly virtual sensor system which can handle such parameter variations. Stochastic-differential equations (SDEs) based estimation of the flow-front dynamics can offer a good trade-off between physics and data-driven estimators. In this paper, we analyze the effect of parameter variations on an SDE based spatio-temporal estimator of the flow-front dynamics in a VARTM process.

KW - Partial differential equations

KW - Stochastic differential equations

KW - Varying parameters

KW - Parameter estimation

U2 - 10.1063/1.5045960

DO - 10.1063/1.5045960

M3 - Conference article

SN - 0094-243X

VL - 1981

JO - AIP Conference Proceedings

JF - AIP Conference Proceedings

IS - 1

M1 - 020098

T2 - 9<sup>th</sup> International Conference on Times of Polymers and Composites

Y2 - 17 June 2018 through 21 June 2018

ER -

Estimation of a stochastic spatio-temporal model of the flow-front dynamics with varying parameters

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Keywords

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