Application of Genetic Algorithms to Accelerated Determination of Material Parameters Needed in Creep-Fatigue Life Evaluation.
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Accession number;03A0138525
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| Title;Application of Genetic Algorithms to Accelerated Determination of Material Parameters Needed in Creep-Fatigue Life Evaluation. |
| Author;
TOKIMASA KATSUYUKI
(Kinki Univ., School of Biology-Oriented Sci. and Technol., JPN)
TAKAHATA SATOSHI
(Kinki Univ., Graduate School, JPN)
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Journal Title;Journal of the Society of Materials Science, Japan
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Journal Code:F0385A
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ISSN:0514-5163
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VOL.52;NO.2;PAGE.173-178(2003)
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| Figure&Table&Reference;FIG.5, TBL.4, REF.9 |
| Pub. Country;Japan |
| Language;Japanese |
| Abstract;The present paper investigates the applicability of Genetic Algorithms (GA) to accelerated determination of the material parameters required in order to evaluate creep-fatigue life and remaining life of Mod.9Cr-1Mo steel. The GA program, which was written in Visual C++, was developed in order to estimate the values of 23 material parameters required to describe the partitioned inelastic strain range versus life equations and the creep-fatigue damage growth model based on the strain range partitioning concept. Three types of test, constant-strain amplitude creep-fatigue tests, constant-amplitude creep-fatigue crack growth tests and variable-strain waveform creep-fatigue tests, were needed in order to determine the above-described parameters experimentally. The GA analysis was able to determine the parameters without using the creep-fatigue crack growth test data. The effects of the number of data used in the GA analysis for the estimation accuracy of the material parameters and the creep-fatigue life were evaluated. The obtained results suggest that the number of tests required for GA determination of material parameters is half of the number of creep-fatigue tests (175) that must be conducted in order to determine the material parameters experi-mentally. (author abst.) |
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