Frost durability of cementitious materials: What's next?
Frost durability, a critical parameter for concrete, especially in harsh exposure regions, has been extensively researched, with almost four thousand papers published since the 1970s. However, a systematic mapping of this research is yet to be explored. This paper presents a novel approach based on...
Published in: | Case Studies in Construction Materials |
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Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Luleå tekniska universitet, Byggkonstruktion och brand
2024
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Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-110991 https://doi.org/10.1016/j.cscm.2024.e04014 |
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author | Rajczakowska, Magdalena Novakova, Iveta Adediran, Adeolu Perumal, Priyadharshini Wallevik, Ólafur Haralds Cwirzen, Andrzej |
author_facet | Rajczakowska, Magdalena Novakova, Iveta Adediran, Adeolu Perumal, Priyadharshini Wallevik, Ólafur Haralds Cwirzen, Andrzej |
author_sort | Rajczakowska, Magdalena |
collection | Luleå University of Technology Publications (DiVA) |
container_start_page | e04014 |
container_title | Case Studies in Construction Materials |
container_volume | 21 |
description | Frost durability, a critical parameter for concrete, especially in harsh exposure regions, has been extensively researched, with almost four thousand papers published since the 1970s. However, a systematic mapping of this research is yet to be explored. This paper presents a novel approach based on Natural Language Processing (NLP) and machine learning to semi-automatically analyze the existing literature on frost durability of cementitious materials. The aim is to identify research gaps and provide insights for future work, offering a comprehensive understanding of the freeze and thaw (FT) research area. Data sets containing academic abstracts on FT tests have been created, and the identified articles are topically structured using a latent Dirichlet allocation (LDA) topic modeling approach. The publication volume associated with each topic over time has been quantified, providing an overview of the research landscape. The results show that NLP and t-SNE effectively review large volumes of technical text data, identifying 12 dominant themes in FT research, such as mechanical properties and material composition. Over recent decades, there has been a shift from focusing on structural performance to emerging topics like cracking and Supplementary Cementitious Materials (SCMs). Additionally, t-SNE and K-means clustering revealed four main clusters, suggesting future research should focus on the FT durability of eco-friendly materials, accelerated testing, and enhanced FT durability materials. These findings not only facilitate the identification of gaps and opportunities for future work but also have practical implications for developing more durable and sustainable concrete. Validerad;2024;Nivå 2;2024-12-09 (signyg); Funder: Interreg Northern Periphery and Arctic program; Fulltext license: CC BY |
format | Article in Journal/Newspaper |
genre | Arctic |
genre_facet | Arctic |
geographic | Arctic |
geographic_facet | Arctic |
id | ftluleatu:oai:DiVA.org:ltu-110991 |
institution | Open Polar |
language | English |
op_collection_id | ftluleatu |
op_doi | https://doi.org/10.1016/j.cscm.2024.e04014 |
op_relation | Case Studies in Construction Materials, 2024, 21, doi:10.1016/j.cscm.2024.e04014 ISI:001372259300001 |
op_rights | info:eu-repo/semantics/openAccess |
publishDate | 2024 |
publisher | Luleå tekniska universitet, Byggkonstruktion och brand |
record_format | openpolar |
spelling | ftluleatu:oai:DiVA.org:ltu-110991 2025-01-16T20:46:20+00:00 Frost durability of cementitious materials: What's next? Rajczakowska, Magdalena Novakova, Iveta Adediran, Adeolu Perumal, Priyadharshini Wallevik, Ólafur Haralds Cwirzen, Andrzej 2024 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-110991 https://doi.org/10.1016/j.cscm.2024.e04014 eng eng Luleå tekniska universitet, Byggkonstruktion och brand Faculty of Science and Technology, The Arctic University of Norway, Narvik N-8505, Norway Fibre and Particle Engineering Research Unit, University of Oulu, Pentti Kaiteran katu 1, Oulu 90014, Finland Reykjavik University & Innovation Center Iceland, Arleyni 2, Reykjavik IS-112, Iceland Case Studies in Construction Materials, 2024, 21, doi:10.1016/j.cscm.2024.e04014 ISI:001372259300001 info:eu-repo/semantics/openAccess Freeze-thaw Concrete Natural language processing (NLP) Topic modeling Construction Management Byggproduktion Article in journal info:eu-repo/semantics/article text 2024 ftluleatu https://doi.org/10.1016/j.cscm.2024.e04014 2024-12-31T15:29:23Z Frost durability, a critical parameter for concrete, especially in harsh exposure regions, has been extensively researched, with almost four thousand papers published since the 1970s. However, a systematic mapping of this research is yet to be explored. This paper presents a novel approach based on Natural Language Processing (NLP) and machine learning to semi-automatically analyze the existing literature on frost durability of cementitious materials. The aim is to identify research gaps and provide insights for future work, offering a comprehensive understanding of the freeze and thaw (FT) research area. Data sets containing academic abstracts on FT tests have been created, and the identified articles are topically structured using a latent Dirichlet allocation (LDA) topic modeling approach. The publication volume associated with each topic over time has been quantified, providing an overview of the research landscape. The results show that NLP and t-SNE effectively review large volumes of technical text data, identifying 12 dominant themes in FT research, such as mechanical properties and material composition. Over recent decades, there has been a shift from focusing on structural performance to emerging topics like cracking and Supplementary Cementitious Materials (SCMs). Additionally, t-SNE and K-means clustering revealed four main clusters, suggesting future research should focus on the FT durability of eco-friendly materials, accelerated testing, and enhanced FT durability materials. These findings not only facilitate the identification of gaps and opportunities for future work but also have practical implications for developing more durable and sustainable concrete. Validerad;2024;Nivå 2;2024-12-09 (signyg); Funder: Interreg Northern Periphery and Arctic program; Fulltext license: CC BY Article in Journal/Newspaper Arctic Luleå University of Technology Publications (DiVA) Arctic Case Studies in Construction Materials 21 e04014 |
spellingShingle | Freeze-thaw Concrete Natural language processing (NLP) Topic modeling Construction Management Byggproduktion Rajczakowska, Magdalena Novakova, Iveta Adediran, Adeolu Perumal, Priyadharshini Wallevik, Ólafur Haralds Cwirzen, Andrzej Frost durability of cementitious materials: What's next? |
title | Frost durability of cementitious materials: What's next? |
title_full | Frost durability of cementitious materials: What's next? |
title_fullStr | Frost durability of cementitious materials: What's next? |
title_full_unstemmed | Frost durability of cementitious materials: What's next? |
title_short | Frost durability of cementitious materials: What's next? |
title_sort | frost durability of cementitious materials: what's next? |
topic | Freeze-thaw Concrete Natural language processing (NLP) Topic modeling Construction Management Byggproduktion |
topic_facet | Freeze-thaw Concrete Natural language processing (NLP) Topic modeling Construction Management Byggproduktion |
url | http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-110991 https://doi.org/10.1016/j.cscm.2024.e04014 |