1.

Record Nr.

UNINA9910366610503321

Autore

Sygusch Nikolai

Titolo

Stochastic Approach to Rupture Probability of Short Glass Fiber Reinforced Polypropylene based on Three-Point-Bending Tests / / by Nikolai Sygusch

Pubbl/distr/stampa

Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Vieweg, , 2020

ISBN

3-658-27113-2

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (x, 145 pages) : illustrations

Collana

Mechanik, Werkstoffe und Konstruktion im Bauwesen, , 2512-3238 ; ; 52

Disciplina

666.157

Soggetti

Building materials

Buildings—Design and construction

Building

Construction

Engineering, Architectural

Building—Superintendence

Construction industry—Management

Construction superintendence

Building Materials

Building Construction and Design

Construction Management

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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

Sommario/riassunto

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, Rüsselsheim am Main.