[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127699-en":3,"doc-seo-127699-105":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},127699,962084928432,"Emma Wilson","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Bullet Ricochet Mark Plan-view Morphology in Concrete - An Experimental Assessment of Five Bullet Types and Two Distances","Bullet ricochets are frequent during shooting incidents and can support reconstruction by preserving measurable evidence at impact sites. Yet few studies have systematically quantified how ricochet impact-site morphology varies across bullet types. This experiment analyzed 297 concrete ricochet impact sites produced by five bullet types fired from two distances. A random forest model classified bullet types using ricochet-mark dimensions, achieving 62% accuracy and 66% when distance was included. Results indicate potential probabilistic identification but also substantial overlap that can mislead human assessments in real reconstructions.","Bullet ricochet mark plan-view morphology in concrete: an experimental assessment of five bullet types and two distances using machine learning  \nMetin I. Eren1 ,2 , * , Jay Romans3 , Robert S. Walker4 , Briggs Buchanan5 , Alastair Key6  \n1 Department of Anthropology, Kent State University, Lowry Hall, 750 Hilltop Drive, Kent, OH, USA  \n2 Department of Archaeology, Cleveland Museum of Natural History, 1 Wade Oval, University Circle, Cleveland, OH, USA  \n3 Pro Armament, 2427 Front Street, Suite B, Cuyahoga Falls, OH, USA  \n4 Department of Anthropology, University of Missouri, Swallow Hall, 112, 507 S 9th Street, Columbia, MO, USA  \n5 Department of Anthropology, University of Tulsa, Harwell Hall, Tulsa, OK, USA  \n6 Department of Archaeology, University of Cambridge, Downing Street, Cambridge, UK  \n*Corresponding [author. E-mail: meren@kent.edu](author. E-mail: meren@kent.edu)  \nAbstract  \nBullet ricochets are common occurrences during shooting incidents and can provide a wealth of information useful for shooting incident reconstruction. However, there have only been a small number of studies that have systematically investigated bullet ricochet impact site morphology. Here, this study reports on an experiment that examined the plan-view morphology of 297 ricochet impact sites in concrete that were produced by five different bullet types shot from two distances. This study used a random forest machine learning algorithm to classify bullet types with morphological dimensions of the ricochet mark (impact) with length and perimeter-to-area ratio emerging as the top predictor variables. The 0.22 LR leaves the most distinctive impact mark on the concrete, and overall, the classification accuracy using leave-one-out cross-validation is 62%, considerably higher than a random classification accuracy of 20% . Adding in distance to the model as a predictor increases the classification accuracy to 66% . These initial results are promising, in that they suggest that an unknown bullet type can potentially be determined, or at least probabilistically assessed, from the morphology of the ricochet impact site alone. However, the substantial amount of overlap this study documented among distinct bullet types’ ricochet mark morphologies under highly controlled conditions and with machine learning suggests that the human identification of ricochet marks in real-world shooting incident reconstructions may be on occasion, or perhaps regularly, in error.  \nKey points  \n• Bullet ricochet impact sites can help with shooting incident reconstruction.  \n• A random forest machine learning algorithm classified bullet type from ricochet morphology.  \n• Results suggest that unknown bullets can potentially be determined from ricochet impact site morphology.  \n• Human identification of bullet types from ricochet sites may be erroneous.  \nKeywords: bullet ricochet; machine learning; morphometrics; concrete; shooting incident reconstruction  \nIntroduction  \nBullet ricochet is a type of deflection that changes the initial bullet path and velocity by impact, but without perforation or penetration ([1]: p.263–264; [2–6]: p.605; [7]: p.21, 163) . Ricochets are common occurrences during shooting incidents, can occur accidentally or intentionally, and are affected by a wide range of factors [8, 9]. As such, the phenomenon of bullet ricochet has a rich and diverse research history [1, 10, 11] . Ricochet experiments and case studies include the investigation of wound production; bullet destabilization; bullet deformation and fragmentation; bullet path and velocity change; bullet fragment velocity, angle, and impact distribution; range danger area; shooter location and proximity to victim; travel distance and distribution of debris; and potential defensive considerations when ricochet is possible or likely [7, 12–28] .  \nOne topic that has received less attention is bullet ricochet  \nimpact site morphology, which is surprising given the widely held notion that “ricochet marks ... ","cbCaie51nJzTUfcx","https://ap.wps.com/l/cbCaie51nJzTUfcx","pdf",1466151,1,10,"English","en",105,"# Abstract\n# Key points\n# Keywords\n# Introduction","[{\"question\":\"What question does the study address about bullet ricochet marks?\",\"answer\":\"The study examines how bullet ricochet impact-site plan-view morphology in concrete varies across different bullet types and distances, using quantitative experimental comparisons and machine learning.\"},{\"question\":\"How is bullet type classification performed?\",\"answer\":\"A random forest machine learning algorithm classifies bullet types from morphological dimensions of the ricochet mark, with length and perimeter-to-area ratio among the top predictor variables.\"},{\"question\":\"What classification performance is reported, and how does adding distance change it?\",\"answer\":\"Leave-one-out cross-validation yields 62% accuracy; adding distance as a predictor increases accuracy to 66%.\"}]","Bullet Ricochet Mark Plan-view Morphology in Concrete - An Experimental Assessment of Five Bullet Types and Two Distances | PDF",1785940981,25,{"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},"bullet-ricochet-mark-plan-view-morphology-in-concrete-an-experimental-assessment-of-five-bullet-types-and-two-distances","",{"@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/bullet-ricochet-mark-plan-view-morphology-in-concrete-an-experimental-assessment-of-five-bullet-types-and-two-distances/127699/",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","2026-08-05",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},"What question does the study address about bullet ricochet marks?","Question",{"text":75,"@type":76},"The study examines how bullet ricochet impact-site plan-view morphology in concrete varies across different bullet types and distances, using quantitative experimental comparisons and machine learning.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is bullet type classification performed?",{"text":80,"@type":76},"A random forest machine learning algorithm classifies bullet types from morphological dimensions of the ricochet mark, with length and perimeter-to-area ratio among the top predictor variables.",{"name":82,"@type":73,"acceptedAnswer":83},"What classification performance is reported, and how does adding distance change it?",{"text":84,"@type":76},"Leave-one-out cross-validation yields 62% accuracy; adding distance as a predictor increases accuracy to 66%.","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},[93,97,101,105,110,115,120,123,128,131,134],{"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":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":21,"slug":133},"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]