Determination of uncertainty in the description of crack widths using artificial neural networks

Anton van der Esch; Rob J.M. Wolfs; Simon N.M. Wijte

Determination of uncertainty in the description of crack widths using artificial neural networks

Anton van der Esch, Rob J.M. Wolfs, Simon N.M. Wijte

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

Abstract

Crack width formulations, such as the one described in Eurocode 2, present a single value to describe the crack width in reinforced concrete structures, but provide limited insight into the uncertainty of the description of crack widths. This paper describes how the uncertainty in the descriptions of these crack widths can be calculated by constructing Prediction Intervals for concrete members loaded in tension. Results showed that accurate and robust prediction intervals could be constructed using artificial neural networks combined with the Lower Upper Bound Estimation method. Furthermore, it was shown that the quantification of uncertainty provides more insight into the description of crack widths.

Original language	English
Title of host publication	14th fib Phd Symposium in Civil Engineering, 2022, Proceedings
Editors	Marco di Prisco, Alberto Meda, Gyorgy L. Balazs
Publisher	International Federation for Structural Concrete
Pages	889-896
Number of pages	8
ISBN (Electronic)	978-2-940643-17-2
ISBN (Print)	9782940643172
Publication status	Published - 7 Sept 2022
Event	14^th fib International PhD Symposium in Civil Engineering - Rome, Italy Duration: 5 Sept 2022 → 7 Sept 2022 Conference number: 14

Publication series

Name	fib Symposium
ISSN (Print)	2617-4820

Conference

Conference	14^th fib International PhD Symposium in Civil Engineering
Country/Territory	Italy
City	Rome
Period	5/09/22 → 7/09/22

Cite this

@inproceedings{306edc150dd54bb0b64931ed3e887698,

title = "Determination of uncertainty in the description of crack widths using artificial neural networks",

abstract = "Crack width formulations, such as the one described in Eurocode 2, present a single value to describe the crack width in reinforced concrete structures, but provide limited insight into the uncertainty of the description of crack widths. This paper describes how the uncertainty in the descriptions of these crack widths can be calculated by constructing Prediction Intervals for concrete members loaded in tension. Results showed that accurate and robust prediction intervals could be constructed using artificial neural networks combined with the Lower Upper Bound Estimation method. Furthermore, it was shown that the quantification of uncertainty provides more insight into the description of crack widths.",

author = "{van der Esch}, Anton and Wolfs, {Rob J.M.} and Wijte, {Simon N.M.}",

year = "2022",

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booktitle = "14th fib Phd Symposium in Civil Engineering, 2022, Proceedings",

note = "14<sup>th</sup> fib International PhD Symposium in Civil Engineering ; Conference date: 05-09-2022 Through 07-09-2022",

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van der Esch, A , Wolfs, RJM & Wijte, SNM 2022, Determination of uncertainty in the description of crack widths using artificial neural networks. in M di Prisco, A Meda & GL Balazs (eds), 14th fib Phd Symposium in Civil Engineering, 2022, Proceedings. fib Symposium, International Federation for Structural Concrete, pp. 889-896, 14^th fib International PhD Symposium in Civil Engineering, Rome, Italy, 5/09/22.

Determination of uncertainty in the description of crack widths using artificial neural networks. / van der Esch, Anton ; Wolfs, Rob J.M.; Wijte, Simon N.M.
14th fib Phd Symposium in Civil Engineering, 2022, Proceedings. ed. / Marco di Prisco; Alberto Meda; Gyorgy L. Balazs. International Federation for Structural Concrete, 2022. p. 889-896 (fib Symposium).

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

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T1 - Determination of uncertainty in the description of crack widths using artificial neural networks

AU - van der Esch, Anton

AU - Wolfs, Rob J.M.

AU - Wijte, Simon N.M.

N1 - Conference code: 14

PY - 2022/9/7

Y1 - 2022/9/7

N2 - Crack width formulations, such as the one described in Eurocode 2, present a single value to describe the crack width in reinforced concrete structures, but provide limited insight into the uncertainty of the description of crack widths. This paper describes how the uncertainty in the descriptions of these crack widths can be calculated by constructing Prediction Intervals for concrete members loaded in tension. Results showed that accurate and robust prediction intervals could be constructed using artificial neural networks combined with the Lower Upper Bound Estimation method. Furthermore, it was shown that the quantification of uncertainty provides more insight into the description of crack widths.

AB - Crack width formulations, such as the one described in Eurocode 2, present a single value to describe the crack width in reinforced concrete structures, but provide limited insight into the uncertainty of the description of crack widths. This paper describes how the uncertainty in the descriptions of these crack widths can be calculated by constructing Prediction Intervals for concrete members loaded in tension. Results showed that accurate and robust prediction intervals could be constructed using artificial neural networks combined with the Lower Upper Bound Estimation method. Furthermore, it was shown that the quantification of uncertainty provides more insight into the description of crack widths.

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M3 - Conference contribution

SN - 9782940643172

T3 - fib Symposium

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BT - 14th fib Phd Symposium in Civil Engineering, 2022, Proceedings

A2 - di Prisco, Marco

A2 - Meda, Alberto

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T2 - 14<sup>th</sup> fib International PhD Symposium in Civil Engineering

Y2 - 5 September 2022 through 7 September 2022

ER -

Determination of uncertainty in the description of crack widths using artificial neural networks

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