[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120062-en":3,"doc-seo-120062-105":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},120062,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","TRIBOINFORMATICS: MACHINE LEARNING METHODS FOR FRICTIONAL INSTABILITIES","Friction research is moving from purely data-driven experiments and phenomenological structure–property models toward triboinformatics, which integrates tribology with machine learning and artificial intelligence to uncover correlations in friction and wear data. The approach is aimed at frictional instabilities, where deterministic modeling is difficult, including instabilities triggered by velocity-dependent dry friction, coupling with wear and heat generation, elastic Adams instabilities, and the unstable onset of sliding. Topological data analysis and multiple ML algorithms are highlighted as applicable tools.","[https://doi.org/10.22190/FUME231208013N](https://doi.org/10.22190/FUME231208013N)  \nOriginal scientific paper  \nTRIBOINFORMATICS: MACHINE LEARNING METHODS FOR FRICTIONAL INSTABILITIES  \nMichael Nosonovsky1,2, Aleksandr S. Aglikov2  \n1University of Wisconsin-Milwaukee, Mechanical Engineering Department, USA 2ITMO University, Infochemistry Scientific Center, Russia  \nAbstract. The study of friction is traditionally a data-driven area with many experimental data and phenomenological models governing structure-property relationships. Triboinformatics is a new area combining Tribology with Machine Learning (ML) and Artificial Intelligence (AI) methods, which can help to establish correlations in data on friction and wear. This is particularly relevant to unstable motion, where deterministic models are difficult to build. There are several types of frictioninduced instabilities including those caused by the velocity dependency of dry friction, coupling of friction with another process (wear, heat generation, etc.), the elastic Adams instabilities, and others. The onset of sliding is also an unstable process. ML/AI methods, such as Topological Data Analysis and various ML algorithms, which have been already used for various aspects of data analysis on friction, can be applied also to the frictional instabilities.  \nKey words: Frictional instabilities, Painlevé paradoxes, Triboinformatics, Machine learning  \n1. INTRODUCTION  \nDue to the extremely interdisciplinary and multiscale character of tribological processes, new mathematical and computational methods rapidly evolve [1]. Many current problems of contact mechanics and tribology are complex dynamic problems, which often lead to instabilities and require new mathematical methods, models, and algorithms. Thus, Ostermeyer and co-workers proposed a boundary layer machine approach for the modeling of wear [2] . Popov and co-workers applied several new methods including non-linear Diffusion-Reaction models of cellular processes [3], the Burridge-Knopoff model combined with Voronoi tessellations to study the stick-slip instability for the state-and-rate  \nReceived: December 08, 2023 / Accepted March 09, 2024  \nCorresponding author: Michael Nosonovsky  \nUniversity of Wisconsin-Milwaukee, 3200 N Cramer St., Milwaukee WI 53217 USA ITMO University, 9 Lomonosova St., St. Petersburg, Russia [E-mail: nosonovs@uwm.edu](E-mail: nosonovs@uwm.edu)  \nfriction [4], the effects of dynamic menisci on adhesion [5], a method to solve viscoelastic contact problems with arbitrary loading histories [6], and an energetic criterion for adhesion in viscoelastic contacts with non-entropic surface interactions [7] . Forsbach and co-authors [8] investigated a two-scale FEM-BAM approach for fingerpad friction under electroadhesion. Many of new multi-scale and dynamic applications are related to biomimetic and biocompatible applications [3, 9-10] . Various Machine Learning (ML) algorithms have been used successfully for similar engineering problems including the kNearest Neighbor (kNN), Decision Trees (DT), and Random Forests (RF) [11, 12] .  \nStability analysis has been the subject of intensive studies in Mechanics and the theory of Dynamical Systems since at least the middle of the 19th century. The Theory of Stability addresses the stability of equilibria states and stability of solutions of differential equations of dynamical systems, under small perturbations of initial conditions [13] . Typically, a dynamical system is represented by a point in that system’s configuration space (x1, x2,… xn), where xi are coordinates and n is the total number of degrees of freedom, and by a governing differential equation which establishes the evolution of the system in the time domain.  \nDifferent approaches to the stability analysis have been developed to provide stability criteria: Lyapunov stability, algebraic stability (the Routh–Hurwitz stability criterion), frequency stability analysis (the Nyquist stability criterion","cbCaicmJCORMPPmp","https://ap.wps.com/l/cbCaicmJCORMPPmp","pdf",567671,1,12,"English","en",105,"# Introduction\n## Stability and dynamical systems\n## Unstable motion and statistical/ML approaches\n## Triboinformatics and frictional instabilities\n## Dry friction model and destabilization mechanisms","[{\"question\":\"What is triboinformatics and why is it relevant to friction studies?\",\"answer\":\"Triboinformatics combines tribology with machine learning and AI to discover correlations between friction and wear data. It is especially useful for unstable motion where deterministic models are difficult to build.\"},{\"question\":\"Which frictional instability mechanisms are discussed in the paper?\",\"answer\":\"The paper mentions instabilities caused by velocity dependence of dry friction, coupling of friction with other processes such as wear and heat generation, elastic Adams instabilities, and unstable onset of sliding.\"},{\"question\":\"How can ML methods be applied to analyze friction instabilities?\",\"answer\":\"The study points to methods such as topological data analysis and various ML algorithms previously used in friction-related data analysis, enabling statistical insights into unstable behavior.\"}]","TRIBOINFORMATICS: MACHINE LEARNING METHODS FOR FRICTIONAL INSTABILITIES | PDF",1785727947,30,{"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},"triboinformatics-machine-learning-methods-for-frictional-instabilities","",{"@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/triboinformatics-machine-learning-methods-for-frictional-instabilities/120062/",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","2026-08-03",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 is triboinformatics and why is it relevant to friction studies?","Question",{"text":75,"@type":76},"Triboinformatics combines tribology with machine learning and AI to discover correlations between friction and wear data. It is especially useful for unstable motion where deterministic models are difficult to build.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which frictional instability mechanisms are discussed in the paper?",{"text":80,"@type":76},"The paper mentions instabilities caused by velocity dependence of dry friction, coupling of friction with other processes such as wear and heat generation, elastic Adams instabilities, and unstable onset of sliding.",{"name":82,"@type":73,"acceptedAnswer":83},"How can ML methods be applied to analyze friction instabilities?",{"text":84,"@type":76},"The study points to methods such as topological data analysis and various ML algorithms previously used in friction-related data analysis, enabling statistical insights into unstable behavior.","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},[93,97,101,105,110,115,120,122,127,130,134],{"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":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":29,"slug":121},"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":106,"slug":137},19,"General","general"]