MARC details
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02395nam a2200301Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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MX-MdCICY |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20250625164352.0 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
CICY |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
B-21306 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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250602s9999 xx |||||s2 |||| ||und|d |
| 245 10 - TITLE STATEMENT |
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| Title |
Artificial intelligence in real-time diagnostics and prognostics of composite materials and its uncertainties - A review |
| 490 0# - SERIES STATEMENT |
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| Series statement |
Smart Materials and Structures. 30(8), 83001, 2021, DOI: 10.1088/1361-665X/ac099f |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
In the era of the 4th industrial revolution of big data, artificial intelligence (AI) is widely used in each and every field of composite materials which includes design and analysis, material storage, manufacturing, non-destructive testing, structural health monitoring (SHM) and prognostics of its remaining useful life, material state (MS) and damage modes. While these AI models are rapidly developed and integrated into the industrial internet of things to keep track of the health of a composite material from its birth to death, these integrations remain uncertain for prognostics without the certainty of its previous MS. This article is a comprehensive review of the AI models being developed over the past few decades in the field of SHM and prognostics health management of polymer matrix composites. It further analyzes the real gaps between these developments and the nature of uncertainty of these methods. Finally, the pipeline for the real-time prognostics from birth to death, hybrid approaches, uncertainty quantification of data-driven and physics-based systems, and its reliability standards to such complex advanced composite materials are discussed. This paper will be focused as a basic guide for researchers implementing AI in composites for diagnosis, prognosis, and control. © 2021 IOP Publishing Ltd. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
ARTIFICIAL INTELLIGENCE |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPOSITE MATERIALS |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
CONDITION BASED MAINTENANCE |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
DAMAGE |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
MACHINE LEARNING |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
PROGNOSTICS HEALTH MANAGEMENT |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
STRUCTURAL HEALTH MONITORING |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Elenchezhian M.R.P. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Vadlamudi V. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Raihan R. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Reifsnider K. |
| 700 12 - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Reifsnider E. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="https://drive.google.com/file/d/1BgzQLbZrCpm8arOnY9gH3ySepilz3P3g/view?usp=drivesdk">https://drive.google.com/file/d/1BgzQLbZrCpm8arOnY9gH3ySepilz3P3g/view?usp=drivesdk</a> |
| Public note |
Para ver el documento ingresa a Google con tu cuenta @cicy.edu.mx |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Clasificación local |
| Koha item type |
Documentos solicitados |
