[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124159-en":3,"doc-seo-124159-105":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},124159,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Estimation of the Soil Unit Weight of Mining Tailings through the Application of Machine Learning Techniques - Research paper","Several literature correlations estimate soil bulk unit weight for natural soils, but mining tailings present solid specific gravity values outside the ranges used to develop those correlations, creating uncertainty in interpreting field testing. This paper evaluates a previously developed machine-learning approach for estimating soil specific weights of mining tailings, using CPTu-based databases from Brazilian tailings deposits and comparing predicted values with published literature data. Results show a suitable fit and support the use of artificial intelligence to improve reliability of geotechnical design parameters and enhance security in tailings containment structure design.","Estimation of the soil unit weight of mining tailings through the application of machine learning techniques  \nHelena Paula Nierwinski1\\#, Talita Menegaz2, Ricardo José Pfitscher¹, Edgar Odebrecht ³, Fernando Schnaid4  \nand Fernando Mantaras5  \n1Federal University of Santa Catarina, PPGEC, R. Dona Francisca, 8300 – Bloco U Zona Industrial Norte Joinville –  \nSC – Brazil  \n²University of São Paulo, IGc, R. do Lago, 562-Butantã, São Paulo – SP-Brazil 3 University of Santa Catarina State, PPGEC, R. Paulo Malschitzki, 200-Zona Industrial Norte, Joinville – SC  \nBrazil  \n4Federal University of Rio Grande do Sul, PPGEC, Av. Paulo Gama, 110-Bairro Farroupilha-Porto Alegre-Rio  \nGrande do Sul  \n5Geotechnical Consultant, Geoforma, R. Ten. Antônio João, 2195-Bom Retiro, Joinville – SC-Brazil  \n\\#Corresponding author: [helena.paula@ufsc.br](helena.paula@ufsc.br)  \nABSTRACT  \nThere are several correlations in the literature that allow an estimate of the soil unit weight for natural soils, but when dealing with materials whose actual specific gravity of solids is outside the range of natural soils for which the correlations were developed, doubts arise, as occurs in the interpretation of tests on mining tailings. Therefore, the present paper aims to evaluate the application of a previously developed approach supported by machine learning techniques for estimating soil specific weights for mining tailings. This approach was developed considering a more comprehensive range of the specific gravity of solids. So, this work relies on a database with results of CPTu tests carried out in different mining tailings deposits from Brazil to estimate specific weights. The values of the specific weights obtained from the machine learning model were compared with literature data, presenting a suitable fit. The research demonstrates that artificial intelligence can contribute positively to the estimation of reliable design parameters and add security to the development of designs of mining tailings containment structures.  \nKeywords: Soil unit weight; CPTu tests; Multiple linear regression; Artificial neural networks.  \n1. Introduction  \nAn essential geotechnical parameter for the proper interpretation of field tests, understanding the soil behavior, and developing geotechnical designs is the natural unit weight of the soil (􀁊􀯧), also known as Bulk unit weight. The soil natural unit weight is defined as the ratio between the total weight of the soil and the total volume of the soil mass. The Bulk unit weight is distinguished from the dry unit weight by considering the amount of natural moisture in the soil. In designs, for example, the natural unit weight value is necessary for the designer to predict the level of geostatic stresses, which is directly related to the interpretation of the test results and the evaluation of material strength parameters, offering more security for design development. A more accurate methodology for determining the 􀁊􀯧 value is characterizing quality undisturbed samples in laboratory tests. In these cases, also some factors influence the reliability of the results. The first, according to Coile (1936) and Stewart (1943), is to guarantee the collection of undisturbed samples, preserving the structure of the material in the field. The others consist of having advanced and up-to-date technology equipment and having trained staff. Investments are necessary to guarantee the development  \nof geotechnical research and a culture of broad geotechnical-geological research; however, in South America, especially in Brazil, these resources are scarce. This deficit makes the accurate measuring of the unit weight hard, forcing most designs to use standard values adopted from the literature for these parameters.  \nFurthermore, like most mining tailings, cohesionless soils have a particular characteristic that makes it impossible to collect undisturbed samples using traditional methods, requiring technologies that are not widely used in South","cbCaibn5vQsNX9vk","https://ap.wps.com/l/cbCaibn5vQsNX9vk","pdf",603777,1,5,"English","en",105,"# Abstract\n# Introduction\n## Background: natural unit weight and design needs\n## Limitations of standard correlations for mining tailings\n## CPTu testing and estimation of unit weight\n## Prior statistical and machine-learning approaches","[{\"question\":\"Why do existing correlations often fail for mining tailings unit weight estimation?\",\"answer\":\"Those correlations are built from natural-soil databases with specific gravity ranges that mining tailings may fall outside, reducing prediction precision and increasing uncertainty.\"},{\"question\":\"What data and tests support the machine learning approach in this study?\",\"answer\":\"The approach uses a database of CPTu test results from different mining tailings deposits in Brazil to estimate soil specific weights.\"},{\"question\":\"How were the machine learning predictions validated?\",\"answer\":\"Predicted specific weight values from the machine learning model were compared with literature data, showing a suitable fit.\"}]","Estimation of the Soil Unit Weight of Mining Tailings through the Application of Machine Learning Techniques - Research paper | PDF",1785820789,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"estimation-of-the-soil-unit-weight-of-mining-tailings-through-the-application-of-machine-learning-techniques-research-paper","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/estimation-of-the-soil-unit-weight-of-mining-tailings-through-the-application-of-machine-learning-techniques-research-paper/124159/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why do existing correlations often fail for mining tailings unit weight estimation?","Question",{"text":75,"@type":76},"Those correlations are built from natural-soil databases with specific gravity ranges that mining tailings may fall outside, reducing prediction precision and increasing uncertainty.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data and tests support the machine learning approach in this study?",{"text":80,"@type":76},"The approach uses a database of CPTu test results from different mining tailings deposits in Brazil to estimate soil specific weights.",{"name":82,"@type":73,"acceptedAnswer":83},"How were the machine learning predictions validated?",{"text":84,"@type":76},"Predicted specific weight values from the machine learning model were compared with literature data, showing a suitable fit.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":21,"slug":137},19,"General","general"]