Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing
Mamduh Mustafa Awd, Mustafa
Produktnummer:
185860e1683ea64c78be39330170203ddb
| Autor: | Mamduh Mustafa Awd, Mustafa |
|---|---|
| Themengebiete: | Additive Manufacturing Bayesian Statistics Fatigue Strength Fracture Mechanics Machine Learning Numerical Modelling |
| Veröffentlichungsdatum: | 02.01.2023 |
| EAN: | 9783658402365 |
| Sprache: | Englisch |
| Seitenzahl: | 255 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer Fachmedien Wiesbaden GmbH |
Produktinformationen "Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing"
Fatigue failure of structures used in transportation, industry, medical equipment, and electronic components needs to build a link between cutting-edge experimental characterization and probabilistically grounded numerical and artificially intelligent tools. The physics involved in this process chain is computationally prohibitive to comprehend using traditional computation methods. Using machine learning and Bayesian statistics, a defect-correlated estimate of fatigue strength was developed. Fatigue, which is a random variable, is studied in a Bayesian-based machine learning algorithm. The stress-life model was used based on the compatibility condition of life and load distributions. The defect-correlated assessment of fatigue strength was established using the proposed machine learning and Bayesian statistics algorithms. It enabled the mapping of structural and process-induced fatigue characteristics into a geometry-independent load density chart across a wide range of fatigue regimes.
Sie möchten lieber vor Ort einkaufen?
Sie haben Fragen zu diesem oder anderen Produkten oder möchten einfach gerne analog im Laden stöbern? Wir sind gerne für Sie da und beraten Sie auch telefonisch.
Juristische Fachbuchhandlung
Georg Blendl
Parcellistraße 5 (Maxburg)
8033 München
Montag - Freitag: 8:15 -18 Uhr
Samstags geschlossen