Application of Data-Driven Surrogate Models in Structural Engineering: A Literature Review.
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| Title: | Application of Data-Driven Surrogate Models in Structural Engineering: A Literature Review. |
|---|---|
| Authors: | Samadian, Delbaz1 (AUTHOR) d.samadian@tees.ac.uk, Muhit, Imrose B.1 (AUTHOR) i.muhit@tees.ac.uk, Dawood, Nashwan1 (AUTHOR) n.n.dawood@tees.ac.uk |
| Source: | Archives of Computational Methods in Engineering. Mar2025, Vol. 32 Issue 2, p735-784. 50p. |
| Subjects: | Structural engineers, Structural engineering, Evidence gaps, Technical literature, Structural models |
| Abstract: | In recent times, there has been an increasing prevalence of surrogate models and metamodeling techniques in approximating the responses of complex systems. These surrogate models have proven to be effective in various engineering and scientific disciplines due to their ability to handle demanding computational requirements. The utilisation of surrogates can significantly reduce the time and resources required for calculations. However, practitioners and researchers in structural engineering face challenges in selecting the appropriate surrogate model due to the multitude of approaches available in surrogate modelling development. Despite the numerous advantages of surrogate models, their application in civil engineering has only been explored in the past few years. Consequently, there is a need for recommendations to guide practitioners in the proper utilisation of surrogate models. Additionally, comprehensive review studies are necessary to examine the current state-of-the-art in this area. Currently, there is a lack of research that investigates the implementation of surrogate models specifically in the context of structural engineering. Therefore, this article aims to address this gap by reviewing notable papers that have employed data-driven surrogate modelling in calculations within the field of structural engineering. To achieve this, a thorough analysis is conducted, encompassing a review of 91 journal articles published from 2003 onwards. The primary purpose of this analysis is to describe the various surrogate models employed, and to highlight the domains in which surrogates have been utilised so far. The study demonstrates that the utilisation of data-driven surrogate models in the field of structural engineering provides significant benefits owing to their flexible computational methods that produce accurate outcomes. However, there exist certain significant research gaps in the existing literature that need to be addressed in future studies. [ABSTRACT FROM AUTHOR] |
| Copyright of Archives of Computational Methods in Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 183641070 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Application of Data-Driven Surrogate Models in Structural Engineering: A Literature Review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Samadian%2C+Delbaz%22">Samadian, Delbaz</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> d.samadian@tees.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Muhit%2C+Imrose+B%2E%22">Muhit, Imrose B.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> i.muhit@tees.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Dawood%2C+Nashwan%22">Dawood, Nashwan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> n.n.dawood@tees.ac.uk</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Archives+of+Computational+Methods+in+Engineering%22">Archives of Computational Methods in Engineering</searchLink>. Mar2025, Vol. 32 Issue 2, p735-784. 50p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Structural+engineers%22">Structural engineers</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+engineering%22">Structural engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence+gaps%22">Evidence gaps</searchLink><br /><searchLink fieldCode="DE" term="%22Technical+literature%22">Technical literature</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+models%22">Structural models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In recent times, there has been an increasing prevalence of surrogate models and metamodeling techniques in approximating the responses of complex systems. These surrogate models have proven to be effective in various engineering and scientific disciplines due to their ability to handle demanding computational requirements. The utilisation of surrogates can significantly reduce the time and resources required for calculations. However, practitioners and researchers in structural engineering face challenges in selecting the appropriate surrogate model due to the multitude of approaches available in surrogate modelling development. Despite the numerous advantages of surrogate models, their application in civil engineering has only been explored in the past few years. Consequently, there is a need for recommendations to guide practitioners in the proper utilisation of surrogate models. Additionally, comprehensive review studies are necessary to examine the current state-of-the-art in this area. Currently, there is a lack of research that investigates the implementation of surrogate models specifically in the context of structural engineering. Therefore, this article aims to address this gap by reviewing notable papers that have employed data-driven surrogate modelling in calculations within the field of structural engineering. To achieve this, a thorough analysis is conducted, encompassing a review of 91 journal articles published from 2003 onwards. The primary purpose of this analysis is to describe the various surrogate models employed, and to highlight the domains in which surrogates have been utilised so far. The study demonstrates that the utilisation of data-driven surrogate models in the field of structural engineering provides significant benefits owing to their flexible computational methods that produce accurate outcomes. However, there exist certain significant research gaps in the existing literature that need to be addressed in future studies. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Archives of Computational Methods in Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11831-024-10152-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 50 StartPage: 735 Subjects: – SubjectFull: Structural engineers Type: general – SubjectFull: Structural engineering Type: general – SubjectFull: Evidence gaps Type: general – SubjectFull: Technical literature Type: general – SubjectFull: Structural models Type: general Titles: – TitleFull: Application of Data-Driven Surrogate Models in Structural Engineering: A Literature Review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Samadian, Delbaz – PersonEntity: Name: NameFull: Muhit, Imrose B. – PersonEntity: Name: NameFull: Dawood, Nashwan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 11343060 Numbering: – Type: volume Value: 32 – Type: issue Value: 2 Titles: – TitleFull: Archives of Computational Methods in Engineering Type: main |
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