Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Temperature Effects on Weigh-in-Motion Accuracy Using Steering Axle Load Spectrum
https://orcid.org/https://orcid.org/0000-0002-7252-8002
https://orcid.org/https://orcid.org/0009-0001-7275-8414
Weigh-in-Motion (WIM) systems serve as valuable sources of traffic load data. The determination of axle load spectra using WIM data is pivotal for calculating load equivalency factors and predicting pavement distresses through Mechanistic-Empirical Pavement Design Guide (M-EPDG). Among various factors affecting WIM accuracy, temperature changes stand out as particularly influential. This chapter examines the influence of temperature on WIM-collected data, utilizing the steering axle load spectrum. Data was gathered from 77 WIM stations situated on Poland’s national roads and motorways. Observations reveal that temperature fluctuations introduce biases into the axle load spectrum, significantly impacting several key statistics, including Truck Factors (TFs) and the number of Equivalent Standard Axle Loads (ESALs) or the percentage of overloaded vehicles. Notably, a shift in air temperature from −10 to +30 °C leads to axle load spectrum biases ranging from 5% to 35%. The technology of axle load sensors plays a crucial role in this phenomenon. The analysis indicates that the uncertainty of truck factors and the subsequent calculation of ESALs using the fourth power equation can increase by up to 1.5 times when the axle load spectrum bias reaches 20%.
Temperature Effects on Weigh-in-Motion Accuracy Using Steering Axle Load Spectrum
https://orcid.org/https://orcid.org/0000-0002-7252-8002
https://orcid.org/https://orcid.org/0009-0001-7275-8414
Weigh-in-Motion (WIM) systems serve as valuable sources of traffic load data. The determination of axle load spectra using WIM data is pivotal for calculating load equivalency factors and predicting pavement distresses through Mechanistic-Empirical Pavement Design Guide (M-EPDG). Among various factors affecting WIM accuracy, temperature changes stand out as particularly influential. This chapter examines the influence of temperature on WIM-collected data, utilizing the steering axle load spectrum. Data was gathered from 77 WIM stations situated on Poland’s national roads and motorways. Observations reveal that temperature fluctuations introduce biases into the axle load spectrum, significantly impacting several key statistics, including Truck Factors (TFs) and the number of Equivalent Standard Axle Loads (ESALs) or the percentage of overloaded vehicles. Notably, a shift in air temperature from −10 to +30 °C leads to axle load spectrum biases ranging from 5% to 35%. The technology of axle load sensors plays a crucial role in this phenomenon. The analysis indicates that the uncertainty of truck factors and the subsequent calculation of ESALs using the fourth power equation can increase by up to 1.5 times when the axle load spectrum bias reaches 20%.
Temperature Effects on Weigh-in-Motion Accuracy Using Steering Axle Load Spectrum
https://orcid.org/https://orcid.org/0000-0002-7252-8002
https://orcid.org/https://orcid.org/0009-0001-7275-8414
Weigh-in-Motion (WIM) systems serve as valuable sources of traffic load data. The determination of axle load spectra using WIM data is pivotal for calculating load equivalency factors and predicting pavement distresses through Mechanistic-Empirical Pavement Design Guide (M-EPDG). Among various factors affecting WIM accuracy, temperature changes stand out as particularly influential. This chapter examines the influence of temperature on WIM-collected data, utilizing the steering axle load spectrum. Data was gathered from 77 WIM stations situated on Poland’s national roads and motorways. Observations reveal that temperature fluctuations introduce biases into the axle load spectrum, significantly impacting several key statistics, including Truck Factors (TFs) and the number of Equivalent Standard Axle Loads (ESALs) or the percentage of overloaded vehicles. Notably, a shift in air temperature from −10 to +30 °C leads to axle load spectrum biases ranging from 5% to 35%. The technology of axle load sensors plays a crucial role in this phenomenon. The analysis indicates that the uncertainty of truck factors and the subsequent calculation of ESALs using the fourth power equation can increase by up to 1.5 times when the axle load spectrum bias reaches 20%.
Temperature Effects on Weigh-in-Motion Accuracy Using Steering Axle Load Spectrum
Carter, Alan (Herausgeber:in) / Vasconcelos, Kamilla (Herausgeber:in) / Dave, Eshan (Herausgeber:in) / Rys, Dawid (Autor:in) / Wieckowski, Przemyslaw (Autor:in)
International Symposium on Asphalt Pavement & Environment ; 2024 ; Montreal, QC, Canada
14th International Conference on Asphalt Pavements ISAP2024 Montreal ; Kapitel: 79 ; 473-478
24.12.2024
6 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Bridge-weigh-in-motion for axle-load estimation
| TIBKAT | 2015
Weigh-in-Motion Data Quality Assurance Based on 3-S2 Steering Axle Load Analysis
| British Library Online Contents | 1996
Weigh-in-Motion Data Quality Assurance Based on 3-S2 Steering Axle Load Analysis
| British Library Conference Proceedings | 1996