Computer Code for Materials Diagnosis Using Monte Carlo Method and Neural Networks
| Autor: | Hocine Bendjama, Djallel Mahdi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Engineering
Source code Artificial neural network business.industry Mechanical Engineering media_common.quotation_subject Monte Carlo method 02 engineering and technology Perceptron 01 natural sciences 010104 statistics & probability Computer engineering Mechanics of Materials Nondestructive testing Solid mechanics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science Attenuation law State (computer science) 0101 mathematics Safety Risk Reliability and Quality business Simulation media_common |
| Zdroj: | Journal of Failure Analysis and Prevention. 16:931-937 |
| ISSN: | 1864-1245 1547-7029 |
| Popis: | Non-destructive testing (NDT) is a highly valuable technique in evaluation and evolution of materials and products. X-ray imaging is an important NDT technique that is used widely in the metal industry in order to control the quality of materials. Sometimes it may be difficult to get a measurement. The simulation of X-ray imaging is often performed using computer codes. This paper presents a new simulation method for materials diagnosis. The simulation is based primarily on the X-ray attenuation law and it is performed using a combination between Monte Carlo method and multi-layer perceptron neural network. The main goal of the proposed method is to obtain more detailed information about the state of the materials. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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