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Probability-based damage thresholds for bridges’ inspection-based deterioration curves
https://orcid.org/0000-0003-1077-4942
Highlights A change of variable is defined to convert any distribution of bridges’ deterioration ratings into a normal distribution. Durability damage thresholds can be established based on an admissible probability of failure. Service and Ultimate Limit State damage thresholds can be applied to inspection-based deterioration curves of bridges. This research bridges the gap between the traditional analysis of inspection databases and more advance probability-based approaches. The probability of failure of deteriorated bridges can be estimated based on inspection records, allowing decision-making on necessary actions to be taken.
Abstract A probability-based procedure is presented to define damage thresholds of bridges’ deterioration curves, which is applied to a large bridge database of real on-site inspections. The procedure is based on a change of variable to transform any distribution of bridge durability deterioration ratings into a normal distribution. This allows probability-based calculations of damage thresholds associated to certain criteria (e.g. Serviceability or Ultimate Limit State), for immediate application to deterioration prediction curves. This research defines a novel procedure for a probability-based analysis of inspection-based data and, de facto, provides a reliable statistical support system to traditional infrastructure management systems of bridges.
Probability-based damage thresholds for bridges’ inspection-based deterioration curves
https://orcid.org/0000-0003-1077-4942
Highlights A change of variable is defined to convert any distribution of bridges’ deterioration ratings into a normal distribution. Durability damage thresholds can be established based on an admissible probability of failure. Service and Ultimate Limit State damage thresholds can be applied to inspection-based deterioration curves of bridges. This research bridges the gap between the traditional analysis of inspection databases and more advance probability-based approaches. The probability of failure of deteriorated bridges can be estimated based on inspection records, allowing decision-making on necessary actions to be taken.
Abstract A probability-based procedure is presented to define damage thresholds of bridges’ deterioration curves, which is applied to a large bridge database of real on-site inspections. The procedure is based on a change of variable to transform any distribution of bridge durability deterioration ratings into a normal distribution. This allows probability-based calculations of damage thresholds associated to certain criteria (e.g. Serviceability or Ultimate Limit State), for immediate application to deterioration prediction curves. This research defines a novel procedure for a probability-based analysis of inspection-based data and, de facto, provides a reliable statistical support system to traditional infrastructure management systems of bridges.
Probability-based damage thresholds for bridges’ inspection-based deterioration curves
https://orcid.org/0000-0003-1077-4942
Highlights A change of variable is defined to convert any distribution of bridges’ deterioration ratings into a normal distribution. Durability damage thresholds can be established based on an admissible probability of failure. Service and Ultimate Limit State damage thresholds can be applied to inspection-based deterioration curves of bridges. This research bridges the gap between the traditional analysis of inspection databases and more advance probability-based approaches. The probability of failure of deteriorated bridges can be estimated based on inspection records, allowing decision-making on necessary actions to be taken.
Abstract A probability-based procedure is presented to define damage thresholds of bridges’ deterioration curves, which is applied to a large bridge database of real on-site inspections. The procedure is based on a change of variable to transform any distribution of bridge durability deterioration ratings into a normal distribution. This allows probability-based calculations of damage thresholds associated to certain criteria (e.g. Serviceability or Ultimate Limit State), for immediate application to deterioration prediction curves. This research defines a novel procedure for a probability-based analysis of inspection-based data and, de facto, provides a reliable statistical support system to traditional infrastructure management systems of bridges.
Probability-based damage thresholds for bridges’ inspection-based deterioration curves
Alonso Medina, Pablo (author) / León González, Francisco Javier (author) / Todisco, Leonardo (author)
Engineering Structures ; 294
2023-07-24
Article (Journal)
Electronic Resource
English
<math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>BMS</mi></mrow></math> , Bridge Management System , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>DPI</mi></mrow></math> , Durability Performance Index (relative, values from 0 to 1), part of any distribution of values , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>DPI</mi> <mo>′</mo></mrow></math> , modified Durability Performance Index (relative, values from 0 to 1), part of a normal distribution of values , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>F</mi> <mn>0</mn></msub> <mrow><mo>(</mo> <mi>x</mi> <mo>)</mo></mrow></mrow></math> , population cumulative distribution , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mtext>G</mtext></mrow></math> , weight (importance) of a specific damage , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>ID</mi></mrow></math> , inspection damage or condition index , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mrow><mi>ID</mi></mrow> <mrow><mi>max</mi></mrow></msub></mrow></math> , maximum value of all inspections registered in the Management System , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>K</mi> <mn>1</mn></msub></mrow></math> , extent of a specific damage , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>K</mi> <mn>2</mn></msub></mrow></math> , intensity of a specific damage , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>N</mi></mrow></math> , number of values of a histogram or distribution of values , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>P</mi> <mi>f</mi></msub></mrow></math> , probability of failure , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>P</mi> <mi>s</mi></msub></mrow></math> , reliability , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>RC</mi></mrow></math> , reinforced concrete , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>S</mi> <mi>N</mi></msub> <mrow><mo>(</mo> <mi>x</mi> <mo>)</mo></mrow></mrow></math> , observed cumulative step-function of a sample , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>SLS</mi></mrow></math> , Service Limit State , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>ULS</mi></mrow></math> , Ultimate Limit State , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>a</mi></mrow></math> , Miyamoto’s model regression parameter , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>d</mi></mrow></math> , minimum distance between <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>F</mi> <mn>0</mn></msub> <mrow><mfenced><mrow><mi>x</mi></mrow></mfenced></mrow></mrow></math> and <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>S</mi> <mi>N</mi></msub> <mrow><mfenced><mrow><mi>x</mi></mrow></mfenced></mrow></mrow></math> , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>d</mi> <mrow><mi>max</mi></mrow></msub></mrow></math> , maximum acceptable distance <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>d</mi></mrow></math> for a certain significance <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>α</mi></mrow></math> , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>k</mi></mrow></math> , optimal number of intervals of a histogram , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>m</mi></mrow></math> , number of different types of damages identified during an inspection , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>n</mi></mrow></math> , number of elements affected by a certain damage identified during an inspection , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>t</mi></mrow></math> , time (years) , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msup><mrow><mi>Φ</mi></mrow> <mrow><mo>-</mo> <mn>1</mn></mrow></msup> <mo>(</mo> <mspace></mspace> <mo>)</mo></mrow></math> , inverse of the standard normal distribution function , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>α</mi></mrow></math> , level of significance , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>β</mi></mrow></math> , reliability index , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>Δ</mi> <mi>β</mi></mrow></math> , reduction of the reliability index for application to existing structures , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>β</mi> <mi>M</mi></msub></mrow></math> , Miyamoto’s model exponent , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>η</mi></mrow></math> , parameter of certain change of variable functions , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>η</mi> <mrow><mi>min</mi></mrow></msub></mrow></math> , minimum value of <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>η</mi></mrow></math> which makes a certain change of variable result in normality , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>μ</mi> <mrow><mi>DPI</mi> <mo>′</mo></mrow></msub></mrow></math> , average value of a <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>DPI</mi> <mo>′</mo></mrow></math> normal distribution , <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><msub><mi>σ</mi> <mrow><mi>DPI</mi> <mo>′</mo></mrow></msub></mrow></math> , standard deviation of a <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>DPI</mi> <mo>′</mo></mrow></math> normal distribution , Durability , Ageing prediction , Damage threshold , Reinforced concrete deterioration , Deterioration curve
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