[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123095-en":3,"doc-seo-123095-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123095,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Estimating the Bitumen Ratio to be Used in Highway Asphalt Concrete by Machine Learning","Hot mix asphalt used in road pavements relies on an appropriate bitumen proportion, which differs by pavement layer. Traditionally, the bitumen ratio is estimated with the Marshall design method, but it is costly and time-consuming. This study applies the Naive Bayes machine learning approach to practical estimation. Using 102 asphalt concrete designs from wearing course, binder course, asphalt concrete base course, and stone mastic asphalt wearing course, each layer is categorized into three classes based on bitumen ratio, then trained and used to predict ratios. Results show estimation accuracy between 75% and 90%, indicating economical and practical feasibility for layer-wise bitumen ratio determination.","ISSN 1822-427X/e ISSN 1822-4288 2024 Volume 19 Issue 2: 23–42  \n[https://doi.org/10.7250/bjrbe.2024-19.634](https://doi.org/10.7250/bjrbe.2024-19.634)  \nTHE BALTIC JOURNAL OF ROAD  \nAND BRIDGE ENGINEERING  \n2024/1 9(2)  \nESTIMATING THE BITUMEN RATIO TO BE USED IN HIGHWAY ASPHALT CONCRETE  \nBY MACHINE LEARNING  \nMUHAMMED YASIN ÇODUR1, HALIS BAHADIR KASİL2 , EMRE KUŞKAPAN2,*  \n1College of Engineering and Technology,  \nAmerican University of the Middle East, Egaila, 54200, Kuwait  \n2Engineering and Architecture Faculty, Erzurum Technical University, Erzurum, Turkey  \nReceived 25 July 2023; accepted 11 March 2024  \nAbstract. Hot mix asphalt, which is frequently used in road pavements, contains bitumen in certain proportions. This bitumen ratio varies according to the layers in the road pavements. The bitumen ratio in each pavement is usually estimated by the Marshall design method. However, this method is costly as well as time-consuming. In this study, the Naive Bayes method, which is a machine learning algorithm, was used to estimate the bitumen ratio practically. In the study, a total of 102 asphalt concrete designs were examined, which were taken from the wearing course, binder course, and asphalt concrete base course and stone mastic asphalt wearing course layers. Each road pavement layer was divided into three different classes according to the bitumen ratios and the algorithm was trained with machine learning. Then the bitumen ratio was estimated for each data set. As a result of this process, the bitumen ratios of the layers were estimated with an accuracy between 75% and 90% . In this study, it was revealed that the bitumen ratio in the road pavement layers could be estimated practically and economically.  \n* Corresponding author. E-mail: [emre.kuskapan@erzurum.edu.tr](emre.kuskapan@erzurum.edu.tr)  \nMuhammed Yasin ÇODUR (ORCID ID 0000-0001-7647-2424)  \nHalis Bahadır KASİL (ORCID ID 0000-0002-6678-7868)  \nEmre KUŞKAPAN (ORCID ID 0000-0003-0711-5567)  \nCopyright © 2024 The Author(s). Published by RTU Press  \nThis is an Open Access article distributed under the terms of the Creative Commons Attribution License ([http://creativecommons. org/licenses/by/4.0/](http://creativecommons. org/licenses/by/4.0/)), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.  \nTHE BALTIC JOURNAL  \nOF ROAD  \nAND BRIDGE  \nENGINEERING  \n2024/1 9(2)  \nKeywords: asphalt concrete, bitumen ratio, highway, road, machine learning, Marshall method.  \nIntroduction  \nThe physical properties of hot mix asphalt (HMA) affect the service life of road pavements under external influences such as cyclic loadsand temperature. HMAs are obtained by mixing bitumen, aggregate and additives at different rates at a certain temperature. The properties of HMAs are affected by these components and their ratios. The designs made before the production of HMA cover the determination of the optimal ratio of aggregate and bitumen to meet the technical requirements of the mixture in asphalt pavement application. HMAdesigns are made using one of the Marshall, Hveem or Superpave design methods in the MS-2 Asphalt Mix Design Method book published by the Asphalt Institute (MS-2 Asphalt Mix Design Methods, 2015) . Marshall method is widely used in HMA design in Turkey.  \nIt is possible to list the expected performances of bituminous pavements as stability, fatigue resistance, flexibility, impermeability, durability, friction resistance and workability. When each of them is associated with the percentage of bitumen, an excess of the bitumen ratio makes it difficult to workability and accordingly compaction, while also causing a decrease in stability. A low bitumen ratio causes fatigue resistance to decrease. This situation reduces impermeability and durability. At the same time, a high bitumen ratio increases flexibility and reduces skid resistance (Bituminous Mixtures Laboratory Handbook, 2021) .  \nOptim","cbCaih3BzCBqOq53","https://ap.wps.com/l/cbCaih3BzCBqOq53","pdf",1921681,1,20,"English","en",105,"# Introduction\n## Hot mix asphalt properties and performance\n## Optimum bitumen content and limitations of conventional design\n## Bituminous binders and applications in road and airport pavements\n## Need for determining optimum bitumen ratio","[{\"question\":\"Why is estimating bitumen ratio in hot mix asphalt important?\",\"answer\":\"Bitumen proportion strongly affects mixture properties and performance, influencing stability, fatigue resistance, impermeability, durability, flexibility, and friction-related behavior.\"},{\"question\":\"What method is traditionally used to estimate bitumen ratio, and what are its drawbacks?\",\"answer\":\"The Marshall design method is commonly used, but it is costly and time-consuming, requiring substantial effort and time during determination.\"},{\"question\":\"How does the Naive Bayes machine learning approach estimate the bitumen ratio in this study?\",\"answer\":\"A dataset of 102 asphalt concrete designs is divided into three bitumen-ratio classes for each pavement layer, then Naive Bayes is trained on these classes to estimate bitumen ratio for each dataset.\"}]","Estimating the Bitumen Ratio to be Used in Highway Asphalt Concrete by Machine Learning | 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is estimating bitumen ratio in hot mix asphalt important?","Question",{"text":75,"@type":76},"Bitumen proportion strongly affects mixture properties and performance, influencing stability, fatigue resistance, impermeability, durability, flexibility, and friction-related behavior.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What method is traditionally used to estimate bitumen ratio, and what are its drawbacks?",{"text":80,"@type":76},"The Marshall design method is commonly used, but it is costly and time-consuming, requiring substantial effort and time during determination.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the Naive Bayes machine learning approach estimate the bitumen ratio in this study?",{"text":84,"@type":76},"A dataset of 102 asphalt concrete designs is divided into three bitumen-ratio classes for each pavement layer, then Naive Bayes is trained on these classes to estimate bitumen ratio for each 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