{"title":"2014-2018年交通负荷演化模型标定与比较","authors":"Olli Asp, Anssi Laaksonen","doi":"10.7250/bjrbe.2023-18.612","DOIUrl":null,"url":null,"abstract":"The national calibration of Eurocode load model 1 (LM1) for road bridges was made by a calibration of the load effects of LM1 against the corresponding load effects of a former load model used in Finland. Due to the increased gross vehicle weights in legislation, a national calibration of LM1 was necessary and the stochastic simulation was needed. The aim of this study is to generate a traffic model together with a predictive model for simulation purposes by using and combining long-time monitoring data measured on a road network in different surveys. In this paper, the performance of the predictive model of increases in axle loads and gross vehicle weights is evaluated against short-term bridge weight in motion (BWIM) measurements. The results achieved with a simulation can be used to gain more information of statistical parameters and the evolution of load effects caused on bridges by road traffic in Finland. The simulation model presented in this study served as a basis for updated national calibration of load model LM1. The follow-up comparison between predictive model and traffic monitoring shows the suitability of the estimation of the evolution of traffic loads and also necessity of the raise of LM1.","PeriodicalId":55402,"journal":{"name":"Baltic Journal of Road and Bridge Engineering","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Traffic Load Model Calibration and Comparison to Evolving Traffic Loads In 2014–2018\",\"authors\":\"Olli Asp, Anssi Laaksonen\",\"doi\":\"10.7250/bjrbe.2023-18.612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The national calibration of Eurocode load model 1 (LM1) for road bridges was made by a calibration of the load effects of LM1 against the corresponding load effects of a former load model used in Finland. Due to the increased gross vehicle weights in legislation, a national calibration of LM1 was necessary and the stochastic simulation was needed. The aim of this study is to generate a traffic model together with a predictive model for simulation purposes by using and combining long-time monitoring data measured on a road network in different surveys. In this paper, the performance of the predictive model of increases in axle loads and gross vehicle weights is evaluated against short-term bridge weight in motion (BWIM) measurements. The results achieved with a simulation can be used to gain more information of statistical parameters and the evolution of load effects caused on bridges by road traffic in Finland. The simulation model presented in this study served as a basis for updated national calibration of load model LM1. The follow-up comparison between predictive model and traffic monitoring shows the suitability of the estimation of the evolution of traffic loads and also necessity of the raise of LM1.\",\"PeriodicalId\":55402,\"journal\":{\"name\":\"Baltic Journal of Road and Bridge Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Baltic Journal of Road and Bridge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7250/bjrbe.2023-18.612\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Baltic Journal of Road and Bridge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7250/bjrbe.2023-18.612","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Traffic Load Model Calibration and Comparison to Evolving Traffic Loads In 2014–2018
The national calibration of Eurocode load model 1 (LM1) for road bridges was made by a calibration of the load effects of LM1 against the corresponding load effects of a former load model used in Finland. Due to the increased gross vehicle weights in legislation, a national calibration of LM1 was necessary and the stochastic simulation was needed. The aim of this study is to generate a traffic model together with a predictive model for simulation purposes by using and combining long-time monitoring data measured on a road network in different surveys. In this paper, the performance of the predictive model of increases in axle loads and gross vehicle weights is evaluated against short-term bridge weight in motion (BWIM) measurements. The results achieved with a simulation can be used to gain more information of statistical parameters and the evolution of load effects caused on bridges by road traffic in Finland. The simulation model presented in this study served as a basis for updated national calibration of load model LM1. The follow-up comparison between predictive model and traffic monitoring shows the suitability of the estimation of the evolution of traffic loads and also necessity of the raise of LM1.
期刊介绍:
THE JOURNAL IS DESIGNED FOR PUBLISHING PAPERS CONCERNING THE FOLLOWING AREAS OF RESEARCH:
road and bridge research and design,
road construction materials and technologies,
bridge construction materials and technologies,
road and bridge repair,
road and bridge maintenance,
traffic safety,
road and bridge information technologies,
environmental issues,
road climatology,
low-volume roads,
normative documentation,
quality management and assurance,
road infrastructure and its assessment,
asset management,
road and bridge construction financing,
specialist pre-service and in-service training;