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Stochastic approach to rupture proba...

Sygusch, Nikolai.

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Stochastic approach to rupture probability of short glass fiber reinforced polypropylene based on three-point-bending tests

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic approach to rupture probability of short glass fiber reinforced polypropylene based on three-point-bending tests/ by Nikolai Sygusch.
Author:	Sygusch, Nikolai.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2020.,
Description:	x, 145 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- State of the Art -- Mechanical Testing -- Statistical Analysis -- Material Modeling -- Numerical Results -- Summary and Outlook -- Bibliograph -- List of symbols -- Appendix.
Contained By:	Springer eBooks
Subject:	Glass fibers. -
Online resource:	https://doi.org/10.1007/978-3-658-27113-8
ISBN:	9783658271138

Stochastic approach to rupture probability of short glass fiber reinforced polypropylene based on three-point-bending tests
Sygusch, Nikolai.

Stochastic approach to rupture probability of short glass fiber reinforced polypropylene based on three-point-bending tests[electronic resource] /by Nikolai Sygusch. - Wiesbaden :Springer Fachmedien Wiesbaden :2020. - x, 145 p. :ill., digital ;24 cm. - Mechanik, werkstoffe und konstruktion im bauwesen,band 522512-3238 ;. - Mechanik, werkstoffe und konstruktion im bauwesen ;band 52..

Introduction -- State of the Art -- Mechanical Testing -- Statistical Analysis -- Material Modeling -- Numerical Results -- Summary and Outlook -- Bibliograph -- List of symbols -- Appendix.

A method for incorporating and comparing stochastic scatter of macroscopic parameters in crash simulations is developed in the present work and applied on a 30 wt.% short glass fiber reinforced polypropylene. Therefore, a statistical testing plan on the basis of three point bending tests with 30 samples for each configuration is carried out. The tests are conducted at 0°, 30°, 45° and 90° orientation angles and at strain rates of 0.021/s and 85/s. The obtained results are evaluated statistically by means of probability distribution functions. An orthotropic elastic plastic material model is utilized for the numerical investigations. Monte Carlo Simulations with variations in macroscopic parameters are run to emulate the stochastic rupture behavior of the experiments. The author Nikolai Sygusch was Research Associate at the Institute of Mechanics and Materials, Working Group Kolling, TH Mittelhessen, Gießen and has been a Ph.D. student from 2015 until 2018 at the crash simulation at Opel Automobile GmbH, Russelsheim am Main.

ISBN: 9783658271138

Standard No.: 10.1007/978-3-658-27113-8doiSubjects--Topical Terms:

649432
Glass fibers.

LC Class. No.: TA450

Dewey Class. No.: 620.144

Stochastic approach to rupture probability of short glass fiber reinforced polypropylene based on three-point-bending tests
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505 0 $a Introduction -- State of the Art -- Mechanical Testing -- Statistical Analysis -- Material Modeling -- Numerical Results -- Summary and Outlook -- Bibliograph -- List of symbols -- Appendix.
520 $a A method for incorporating and comparing stochastic scatter of macroscopic parameters in crash simulations is developed in the present work and applied on a 30 wt.% short glass fiber reinforced polypropylene. Therefore, a statistical testing plan on the basis of three point bending tests with 30 samples for each configuration is carried out. The tests are conducted at 0°, 30°, 45° and 90° orientation angles and at strain rates of 0.021/s and 85/s. The obtained results are evaluated statistically by means of probability distribution functions. An orthotropic elastic plastic material model is utilized for the numerical investigations. Monte Carlo Simulations with variations in macroscopic parameters are run to emulate the stochastic rupture behavior of the experiments. The author Nikolai Sygusch was Research Associate at the Institute of Mechanics and Materials, Working Group Kolling, TH Mittelhessen, Gießen and has been a Ph.D. student from 2015 until 2018 at the crash simulation at Opel Automobile GmbH, Russelsheim am Main.
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