Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing (Paperback, 1st ed. 2022)

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.

General

Imprint:	Springer Vieweg
Country of origin:	Germany
Series:	Werkstofftechnische Berichte Reports of Materials Science and Engineering
Release date:	2023
First published:	2022
Authors:	Mustafa Mamduh Mustafa Awd
Dimensions:	210 x 148mm (L x W)
Format:	Paperback
Pages:	255
Edition:	1st ed. 2022
ISBN-13:	978-3-658-40236-5
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-658-40236-9
Barcode:	9783658402365

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!