{"title":"Evaluating ground vibration attenuation through leca‐filled trenches: A support vector machine approach","authors":"Mohsen Naghizadeh Rokni, Omid Tavasoli, Reza Esmaeilabadi, Amirpouya Saraf","doi":"10.1002/eng2.12960","DOIUrl":null,"url":null,"abstract":"This paper investigates the effect of Leca‐filled barriers, both single and double‐walled trenches, on mitigating ground vibrations due to harmonic loads. A three‐dimensional finite element program, validated in comparison by aforementioned studies, was used alongside automated models created via Plaxis and Python integration. This approach facilitated the evaluation of trench effectiveness in both active and passive design scenarios. Our findings suggest that optimal trench dimensions for effective vibration reduction in active designs are a depth and width of approximately 1λr and 0.2λr, respectively. In passive designs, while trench depth becomes less significant, width plays a crucial role in both single and double‐wall systems. Additionally, a support vector machine algorithm was developed to forecast the performance of single‐wall trenches, showing a high correlation with numerical model outcomes. This underscores the algorithm's utility in predicting trench efficiency, highlighting the practical application of machine learning in geotechnical engineering.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"15 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/eng2.12960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates the effect of Leca‐filled barriers, both single and double‐walled trenches, on mitigating ground vibrations due to harmonic loads. A three‐dimensional finite element program, validated in comparison by aforementioned studies, was used alongside automated models created via Plaxis and Python integration. This approach facilitated the evaluation of trench effectiveness in both active and passive design scenarios. Our findings suggest that optimal trench dimensions for effective vibration reduction in active designs are a depth and width of approximately 1λr and 0.2λr, respectively. In passive designs, while trench depth becomes less significant, width plays a crucial role in both single and double‐wall systems. Additionally, a support vector machine algorithm was developed to forecast the performance of single‐wall trenches, showing a high correlation with numerical model outcomes. This underscores the algorithm's utility in predicting trench efficiency, highlighting the practical application of machine learning in geotechnical engineering.