Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 341-354 |
| Seitenumfang | 14 |
| Fachzeitschrift | International journal of fatigue |
| Jahrgang | 112 |
| Frühes Online-Datum | 22 März 2018 |
| Publikationsstatus | Veröffentlicht - Juli 2018 |
| Extern publiziert | Ja |
Abstract
This work presents the lifetime prediction of elastomer component based on the particle distribution in the specimen, the crack growth properties and the appropriate crack criterion. A lifetime prediction using numerical simulation saves both cost and time and can be very helpful in the development phase of a product. On the basis of the obtained results, lifetime can be estimated and thus an appropriate measure such as geometry change or load adjustment can be adopted. The prediction is demonstrated using two kinds of elastomer samples: EPDM and NR under different load amplitudes. Lifetime prediction is accomplished by Monte Carlo simulation, which is based on the correlation between the value of J-integral and total energy density of the single-edge notched tension (SENT) sample. Due to the choice of an inelastic material law the J-integral is evaluated after establishment of stable load cycles as the stable value for a J-integral contour curve as a function of the contour curve distance from the crack tip. For lifetime prediction, a Python script was implemented for the commercial FEA system Abaqus as a postprocessing routine. The script is based on local lifetime evaluation, where evaluation is done element by element followed up by an accumulation. In addition, physical experiments are used for counting the particles in the materials, to characterise the crack growth and also to measure lifetime.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Modellierung und Simulation
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
- Ingenieurwesen (insg.)
- Werkstoffmechanik
- Ingenieurwesen (insg.)
- Maschinenbau
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: International journal of fatigue, Jahrgang 112, 07.2018, S. 341-354.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Lifetime prediction of filled elastomers based on particle distribution and the J-integral evaluation
AU - El Yaagoubi, Mohammed
AU - Juhre, Daniel
AU - Meier, Jens
AU - Kröger, Nils
AU - Alshuth, Thomas
AU - Giese, Ulrich
PY - 2018/7
Y1 - 2018/7
N2 - This work presents the lifetime prediction of elastomer component based on the particle distribution in the specimen, the crack growth properties and the appropriate crack criterion. A lifetime prediction using numerical simulation saves both cost and time and can be very helpful in the development phase of a product. On the basis of the obtained results, lifetime can be estimated and thus an appropriate measure such as geometry change or load adjustment can be adopted. The prediction is demonstrated using two kinds of elastomer samples: EPDM and NR under different load amplitudes. Lifetime prediction is accomplished by Monte Carlo simulation, which is based on the correlation between the value of J-integral and total energy density of the single-edge notched tension (SENT) sample. Due to the choice of an inelastic material law the J-integral is evaluated after establishment of stable load cycles as the stable value for a J-integral contour curve as a function of the contour curve distance from the crack tip. For lifetime prediction, a Python script was implemented for the commercial FEA system Abaqus as a postprocessing routine. The script is based on local lifetime evaluation, where evaluation is done element by element followed up by an accumulation. In addition, physical experiments are used for counting the particles in the materials, to characterise the crack growth and also to measure lifetime.
AB - This work presents the lifetime prediction of elastomer component based on the particle distribution in the specimen, the crack growth properties and the appropriate crack criterion. A lifetime prediction using numerical simulation saves both cost and time and can be very helpful in the development phase of a product. On the basis of the obtained results, lifetime can be estimated and thus an appropriate measure such as geometry change or load adjustment can be adopted. The prediction is demonstrated using two kinds of elastomer samples: EPDM and NR under different load amplitudes. Lifetime prediction is accomplished by Monte Carlo simulation, which is based on the correlation between the value of J-integral and total energy density of the single-edge notched tension (SENT) sample. Due to the choice of an inelastic material law the J-integral is evaluated after establishment of stable load cycles as the stable value for a J-integral contour curve as a function of the contour curve distance from the crack tip. For lifetime prediction, a Python script was implemented for the commercial FEA system Abaqus as a postprocessing routine. The script is based on local lifetime evaluation, where evaluation is done element by element followed up by an accumulation. In addition, physical experiments are used for counting the particles in the materials, to characterise the crack growth and also to measure lifetime.
KW - Fatigue of filled elastomers
KW - J-integral
KW - Lifetime prediction
KW - Model of Rubber Phenomenology
KW - Particle distribution
UR - http://www.scopus.com/inward/record.url?scp=85044932456&partnerID=8YFLogxK
U2 - 10.1016/j.ijfatigue.2018.03.024
DO - 10.1016/j.ijfatigue.2018.03.024
M3 - Article
AN - SCOPUS:85044932456
VL - 112
SP - 341
EP - 354
JO - International journal of fatigue
JF - International journal of fatigue
SN - 0142-1123
ER -