Reliability Analysis of Prestressed Concrete Bridges in Mexico: Assessment and Live Load Factors Proposal

Salgado-Estrada, Rolando; Zamora-Castro, Sergio A.; Herrera-May, Agustín L.; Sánchez-Moreno, Yessica A.; Sánchez-Moreno, Yair S.

doi:10.1007/s40999-020-00590-9

“…To further analyze the fuzzy random sensitivity and distinguish the importance of each parameter to the overall reliability of the wellbore structure 37 , 38 , the conventional sensitivity mean value and standard deviation of each major parameter can be compared with the fuzzy random sensitivity mean value and fuzzy random standard deviation 39 , 40 . The results are shown in Figs.…”

Section: Resultsmentioning

confidence: 99%

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

Yao,

Zhu,

Li

et al. 2024

Sci Rep

0

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To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

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“…To further analyze the fuzzy random sensitivity and distinguish the importance of each parameter to the overall reliability of the wellbore structure [35,36], the conventional sensitivity mean value and standard deviation of each major parameter can be compared with the fuzzy random sensitivity mean value and fuzzy random standard deviation. The results are shown in Figs.…”

Section: Engineering Examplesmentioning

confidence: 99%

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on HMM model

Yafeng,

Yan,

Yongheng

et al. 2024

Preprint

0

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To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

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“…ese factors are highly complex, and there are certain connections between them, which increases the degree of danger during the movement of vehicles and directly a ects the reliability of highway alignment [14][15][16][17][18]. e structural reliability of vehicles traveling on the road and the characteristics of drivers indirectly affect the reliability of highway alignment [19,20].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Reliability Calculation Method of Highway Alignment

Fu

¹

,

Chen

²

,

Zhao

³

2022

Mathematical Problems in Engineering

0

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Considering the randomness and fuzziness of highway route design parameters, based on the reliability theory and triangular fuzzy numbers, the fuzzy variables are transformed into random variables. Three new fuzzy reliability calculation methods of highway alignment are derived, namely, the equivalent density function method, the information entropy method, and the general density function method. The proposed calculation methods are applied to the reliability analysis of highway horizontal curve design. The results show that if the fuzzy variables are symmetric fuzzy numbers, the equivalent mean values obtained by the three methods are equal. If the fuzzy variables are asymmetric fuzzy numbers, the equivalent mean values and equivalent standard deviations of the three methods are different. Compared with the traditional reliability calculation method, the values obtained by the proposed method have a large reliability index, small failure probability, and high calculation accuracy. Compared with the other two methods, the general density function method has the fastest convergence and higher accuracy. The general density function method is then applied to the calculation of highway circular curve radius, under the condition of a superelevation failure rate of 5%, to generate the recommended values of the safety and reliability index.

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Reliability Analysis of Prestressed Concrete Bridges in Mexico: Assessment and Live Load Factors Proposal

Cited by 5 publications

References 26 publications

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model

Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on HMM model

Fuzzy Reliability Calculation Method of Highway Alignment

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