Automated detection of alkali-silica reaction in concrete using linear array ultrasound data

Dwight A. Clayton; Hector Santos-Villalobos; N. Dianne Bull Ezell; Joseph Clayton; Justin Baba

doi:10.1007/978-3-319-68454-3_11

Automated detection of alkali-silica reaction in concrete using linear array ultrasound data

Dwight A. Clayton, Hector Santos-Villalobos, N. Dianne Bull Ezell, Joseph Clayton, Justin Baba

Nuclear and Extreme Environment Measurem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper documents the development of signal processing and machine learning techniques for the detection of Alkali-silica reaction (ASR). ASR is a chemical reaction in either concrete or mortar between hydroxyl ions of the alkalis from hydraulic cement, and certain siliceous minerals present in some aggregates. The reaction product, an alkali-silica gel, is hygroscopic having a tendency to absorb water and swell, which under certain circumstances, leads to abnormal expansion and cracking of the concrete. This phenomenon affects the durability and performance of concrete cause significant loss of mechanical properties. Developing reliable methods and tools that can evaluate the degree of the ASR damage in existing structures, so that informed decisions can be made toward mitigating ASR progression and damage, is important to the long-term operation of nuclear power plants especially if licenses are extended beyond 60 years. The paper examines the differences in the time-domain and frequency-domain signals of healthy and ASR-damaged specimens. More precisely, we explore the use of the Fast Fourier Transform to observe unique features of ASR damaged specimens and an automated method based on Neural Networks to determine the extent of ASR damage in laboratory concrete specimens.

Original language	English
Title of host publication	Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors
Editors	Michael Wright, Denise Paraventi, John H. Jackson
Publisher	Springer International Publishing
Pages	119-129
Number of pages	11
ISBN (Print)	9783319684536
DOIs	https://doi.org/10.1007/978-3-319-68454-3_11
State	Published - 2018
Event	18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems - Water Reactors, 2017 - Portland, United States Duration: Aug 13 2017 → Aug 17 2017

Publication series

Name	Minerals, Metals and Materials Series
Volume	Part F11
ISSN (Print)	2367-1181
ISSN (Electronic)	2367-1696

Conference

Conference	18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems - Water Reactors, 2017
Country/Territory	United States
City	Portland
Period	08/13/17 → 08/17/17

Funding

This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Acknowledgements This work was funded by the U.S. Department of Energy Office of Nuclear Energy under the Light Water Reactor Sustainability program.

Keywords

Alkali-silica
Nondestructive evaluation
Ultrasound

Access to Document

10.1007/978-3-319-68454-3_11

Cite this

Clayton, D. A., Santos-Villalobos, H., Ezell, N. D. B., Clayton, J., & Baba, J. (2018). Automated detection of alkali-silica reaction in concrete using linear array ultrasound data. In M. Wright, D. Paraventi, & J. H. Jackson (Eds.), Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors (pp. 119-129). (Minerals, Metals and Materials Series; Vol. Part F11). Springer International Publishing. https://doi.org/10.1007/978-3-319-68454-3_11

Clayton, Dwight A. ; Santos-Villalobos, Hector ; Ezell, N. Dianne Bull et al. / Automated detection of alkali-silica reaction in concrete using linear array ultrasound data. Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors. editor / Michael Wright ; Denise Paraventi ; John H. Jackson. Springer International Publishing, 2018. pp. 119-129 (Minerals, Metals and Materials Series).

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abstract = "This paper documents the development of signal processing and machine learning techniques for the detection of Alkali-silica reaction (ASR). ASR is a chemical reaction in either concrete or mortar between hydroxyl ions of the alkalis from hydraulic cement, and certain siliceous minerals present in some aggregates. The reaction product, an alkali-silica gel, is hygroscopic having a tendency to absorb water and swell, which under certain circumstances, leads to abnormal expansion and cracking of the concrete. This phenomenon affects the durability and performance of concrete cause significant loss of mechanical properties. Developing reliable methods and tools that can evaluate the degree of the ASR damage in existing structures, so that informed decisions can be made toward mitigating ASR progression and damage, is important to the long-term operation of nuclear power plants especially if licenses are extended beyond 60 years. The paper examines the differences in the time-domain and frequency-domain signals of healthy and ASR-damaged specimens. More precisely, we explore the use of the Fast Fourier Transform to observe unique features of ASR damaged specimens and an automated method based on Neural Networks to determine the extent of ASR damage in laboratory concrete specimens.",

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author = "Clayton, {Dwight A.} and Hector Santos-Villalobos and Ezell, {N. Dianne Bull} and Joseph Clayton and Justin Baba",

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Clayton, DA, Santos-Villalobos, H, Ezell, NDB, Clayton, J & Baba, J 2018, Automated detection of alkali-silica reaction in concrete using linear array ultrasound data. in M Wright, D Paraventi & JH Jackson (eds), Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors. Minerals, Metals and Materials Series, vol. Part F11, Springer International Publishing, pp. 119-129, 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems - Water Reactors, 2017, Portland, United States, 08/13/17. https://doi.org/10.1007/978-3-319-68454-3_11

Automated detection of alkali-silica reaction in concrete using linear array ultrasound data. / Clayton, Dwight A.; Santos-Villalobos, Hector; Ezell, N. Dianne Bull et al.
Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors. ed. / Michael Wright; Denise Paraventi; John H. Jackson. Springer International Publishing, 2018. p. 119-129 (Minerals, Metals and Materials Series; Vol. Part F11).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Clayton, Dwight A.

AU - Santos-Villalobos, Hector

AU - Ezell, N. Dianne Bull

AU - Clayton, Joseph

AU - Baba, Justin

N1 - Publisher Copyright: © The Minerals, Metals & Materials Society 2018.

PY - 2018

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N2 - This paper documents the development of signal processing and machine learning techniques for the detection of Alkali-silica reaction (ASR). ASR is a chemical reaction in either concrete or mortar between hydroxyl ions of the alkalis from hydraulic cement, and certain siliceous minerals present in some aggregates. The reaction product, an alkali-silica gel, is hygroscopic having a tendency to absorb water and swell, which under certain circumstances, leads to abnormal expansion and cracking of the concrete. This phenomenon affects the durability and performance of concrete cause significant loss of mechanical properties. Developing reliable methods and tools that can evaluate the degree of the ASR damage in existing structures, so that informed decisions can be made toward mitigating ASR progression and damage, is important to the long-term operation of nuclear power plants especially if licenses are extended beyond 60 years. The paper examines the differences in the time-domain and frequency-domain signals of healthy and ASR-damaged specimens. More precisely, we explore the use of the Fast Fourier Transform to observe unique features of ASR damaged specimens and an automated method based on Neural Networks to determine the extent of ASR damage in laboratory concrete specimens.

AB - This paper documents the development of signal processing and machine learning techniques for the detection of Alkali-silica reaction (ASR). ASR is a chemical reaction in either concrete or mortar between hydroxyl ions of the alkalis from hydraulic cement, and certain siliceous minerals present in some aggregates. The reaction product, an alkali-silica gel, is hygroscopic having a tendency to absorb water and swell, which under certain circumstances, leads to abnormal expansion and cracking of the concrete. This phenomenon affects the durability and performance of concrete cause significant loss of mechanical properties. Developing reliable methods and tools that can evaluate the degree of the ASR damage in existing structures, so that informed decisions can be made toward mitigating ASR progression and damage, is important to the long-term operation of nuclear power plants especially if licenses are extended beyond 60 years. The paper examines the differences in the time-domain and frequency-domain signals of healthy and ASR-damaged specimens. More precisely, we explore the use of the Fast Fourier Transform to observe unique features of ASR damaged specimens and an automated method based on Neural Networks to determine the extent of ASR damage in laboratory concrete specimens.

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Clayton DA, Santos-Villalobos H, Ezell NDB, Clayton J, Baba J. Automated detection of alkali-silica reaction in concrete using linear array ultrasound data. In Wright M, Paraventi D, Jackson JH, editors, Proceedings of the 18th International Conference on Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors. Springer International Publishing. 2018. p. 119-129. (Minerals, Metals and Materials Series). doi: 10.1007/978-3-319-68454-3_11

Automated detection of alkali-silica reaction in concrete using linear array ultrasound data

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