A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales
The grain microstructure and damage mechanisms at the grain level are the key factors that influence fatigue of metals at small scales. This is addressed in this work by establishing a new micro-mechanical model for prediction of multiaxial high cycle fatigue (HCF) at a length scale of 5-100?m. The...
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| Superior document: | Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
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| Year of Publication: | 2017 |
| Language: | English |
| Series: | Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie
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| Physical Description: | 1 electronic resource (X, 112 p. p.) |
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(CKB)4920000000100847 (oapen)https://directory.doabooks.org/handle/20.500.12854/54878 (EXLCZ)994920000000100847 |
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Eslami, Reza auth A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales KIT Scientific Publishing 2017 1 electronic resource (X, 112 p. p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie Open access Unrestricted online access star The grain microstructure and damage mechanisms at the grain level are the key factors that influence fatigue of metals at small scales. This is addressed in this work by establishing a new micro-mechanical model for prediction of multiaxial high cycle fatigue (HCF) at a length scale of 5-100?m. The HCF model considers elasto-plastic behavior of metals at the grain level and microstructural parameters, specifically the grain size and the grain orientation. English Mehrachsige hochzyklische Ermüdung (HCF) Korngröße und Kornorientierung Mikroschädigung Probabilistische Methoden MEMSMultiaxial high cycle fatigue (HCF) Grain size and grain orientation Micro-damage Probabilistic methods MEMS 3-7315-0583-5 |
| language |
English |
| format |
eBook |
| author |
Eslami, Reza |
| spellingShingle |
Eslami, Reza A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
| author_facet |
Eslami, Reza |
| author_variant |
r e re |
| author_sort |
Eslami, Reza |
| title |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_full |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_fullStr |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_full_unstemmed |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_auth |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_new |
A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| title_sort |
a novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| series |
Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
| series2 |
Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
| publisher |
KIT Scientific Publishing |
| publishDate |
2017 |
| physical |
1 electronic resource (X, 112 p. p.) |
| isbn |
1000059741 3-7315-0583-5 |
| illustrated |
Not Illustrated |
| work_keys_str_mv |
AT eslamireza anovelmicromechanicalmodelforpredictionofmultiaxialhighcyclefatigueatsmallscales |
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n |
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(CKB)4920000000100847 (oapen)https://directory.doabooks.org/handle/20.500.12854/54878 (EXLCZ)994920000000100847 |
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cr |
| hierarchy_parent_title |
Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
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A novel micro-mechanical model for prediction of multiaxial high cycle fatigue at small scales |
| container_title |
Schriftenreihe des Instituts für Angewandte Materialien, Karlsruher Institut für Technologie |
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1796651970386198529 |
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