Mustafa Mamduh Mustafa Awd
Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing
Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing
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- More about Machine Learning Algorithm for Fatigue Fields in Additive Manufacturing
Fatigue failure of structures needs to build a link between experimental characterization and numerical and artificially intelligent tools. A defect-correlated estimate of fatigue strength was developed using machine learning and Bayesian statistics, enabling the mapping of structural and process-induced fatigue characteristics into a geometry-independent load density chart.
Format: Paperback / softback
Length: 255 pages
Publication date: 02 January 2023
Publisher: Springer Fachmedien Wiesbaden
The failure of structures used in transportation, industry, medical equipment, and electronic components due to fatigue requires a strong connection between cutting-edge experimental characterization and probabilistically grounded numerical and artificially intelligent tools. The physics involved in this complex process chain is computationally challenging to understand using traditional computation methods. To address this challenge, a defect-correlated estimate of fatigue strength was developed using machine learning and Bayesian statistics.
Fatigue, as a random variable, is studied in a Bayesian-based machine learning algorithm. The stress-life model is employed based on the compatibility condition of life and load distributions. The proposed machine learning and Bayesian statistics algorithms were used to establish a defect-correlated assessment of fatigue strength. This breakthrough allowed for the mapping of structural and process-induced fatigue characteristics into a geometry-independent load density chart, spanning a wide range of fatigue regimes.
By leveraging machine learning and Bayesian statistics, researchers can gain a deeper understanding of the fatigue behavior of structures and develop more accurate models for predicting fatigue life. This has significant implications in various industries, where structures are subjected to harsh conditions and must be designed to withstand fatigue failure. The development of efficient and reliable fatigue assessment tools can help reduce the risk of accidents, improve the performance of structures, and ultimately save lives and resources.
Weight: 391g
Dimension: 210 x 148 (mm)
ISBN-13: 9783658402365
Edition number: 1st ed. 2022
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