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Journals / Politeknik Dergisi / 2020 / Cilt: 23 - Sayı: 1

A Monte-Carlo Simulation for the Estimation of Side-by-Side Loading Events on Oregon Bridges

Arcan YANİK
Christopher HİGGİNS
Pages
53–60
Publication Date
2020-03-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With respect to the statistical analysis, side-by-side loading probabilities were found to be smaller than the ones presented in American Association of State Highway and Transportation Officials LRFD calibration.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Obtaining the side-by-side probabilities accurately is a very important procedure during two lane loaded live load factor analysis.
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Key Findings & Data:Degree of correlation coefficient of GVW for side-by-side trucks were also obtained from Monte Carlo simulations. 290 bridges located at the prescribed mile markers on Interstate-5 (I-5) southbound on Oregon highways and 1-year of Oregon state-specific weigh-in-motion (WIM) data were used. 75,000 trucks were randomly selected from 1,787,612 trucks that correspond to 1-year WIM data from Woodburn NB traffic site that is located in Oregon.
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Conclusion & Impact:With respect to the statistical analysis, side-by-side loading probabilities were found to be smaller than the ones presented in American Association of State Highway and Transportation Officials LRFD calibration.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Bridge · civil engineering · highway

Abstract

Obtaining the side-by-side probabilities accurately is a very important procedure during two lane loaded live load factor analysis. To calculate the load factors properly, side-by-side loading events should be investigated very carefully. This study presents a statistical method to investigate the side-by-side events on the Oregon bridges. Numerical simulations were performed for this investigation. These simulations were developed in MATLAB. Gross vehicle weights (GVW) of the trucks were used during the analysis. Monte Carlo simulations were performed to analyze side-by-side loading events. Degree of correlation coefficient of GVW for side-by-side trucks were also obtained from Monte Carlo simulations. 290 bridges located at the prescribed mile markers on Interstate-5 (I-5) southbound on Oregon highways and 1-year of Oregon state-specific weigh-in-motion (WIM) data were used. 75,000 trucks were randomly selected from 1,787,612 trucks that correspond to 1-year WIM data from Woodburn NB traffic site that is located in Oregon. Inverse standard normal distribution functions and cumulative distribution functions of the truck data were generated. With respect to the statistical analysis, side-by-side loading probabilities were found to be smaller than the ones presented in American Association of State Highway and Transportation Officials LRFD calibration.

Özet

Obtaining the side-by-side probabilities accurately is a very important procedure during two lane loaded live load factor analysis. To calculate the load factors properly, side-by-side loading events should be investigated very carefully. This study presents a statistical method to investigate the side-by-side events on the Oregon bridges. Numerical simulations were performed for this investigation. These simulations were developed in MATLAB. Gross vehicle weights (GVW) of the trucks were used during the analysis. Monte Carlo simulations were performed to analyze side-by-side loading events. Degree of correlation coefficient of GVW for side-by-side trucks were also obtained from Monte Carlo simulations. 290 bridges located at the prescribed mile markers on Interstate-5 (I-5) southbound on Oregon highways and 1-year of Oregon state-specific weigh-in-motion (WIM) data were used. 75,000 trucks were randomly selected from 1,787,612 trucks that correspond to 1-year WIM data from Woodburn NB traffic site that is located in Oregon. Inverse standard normal distribution functions and cumulative distribution functions of the truck data were generated. With respect to the statistical analysis, side-by-side loading probabilities were found to be smaller than the ones presented in American Association of State Highway and Transportation Officials LRFD calibration.

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Cite This Article

YANİK, A., HİGGİNS, C. (2020). A Monte-Carlo Simulation for the Estimation of Side-by-Side Loading Events on Oregon Bridges. Politeknik Dergisi, Cilt: 23 - Sayı: 1, 53–60. https://ajindex.com/articles/422351

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