{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T02:06:55Z","timestamp":1768097215400,"version":"3.49.0"},"reference-count":32,"publisher":"IOP Publishing","issue":"1","license":[{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["IOP Conf. Ser.: Mater. Sci. Eng."],"published-print":{"date-parts":[[2022,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The simulation of deep drawing processes and its quality is intrinsically dependent on the accuracy of the constitutive model in reproducing the mechanical behaviour of the sheet metal material. Today, the calibration of elastoplastic models \u2013 correspondent to the inverse identification of the material parameters \u2013 often uses full-field measurements, through Digital Image Correlation (DIC) techniques, to capture non-homogeneous strain fields and states, coupled with non-straightforward numerical inverse methodologies. In the last decade, new parameter identification methodologies, such as the Finite Element Model Updating (FEMU), the Constitutive Equation Gap (CEG) method, the Equilibrium Gap Method (EGM) and the Virtual Fields Method (VFM) have been developed and have proven to be effective for non-linear plasticity models. Nonetheless, the FEMU and the VFM have distinguished themselves from the others. More recently, supervised Machine Learning (ML) techniques have been also used as an inverse identification method. These artificial intelligence-based methods use large datasets of numerical tests to train an inverse model in which the input is the history of the strain field and loads during the test, and the output are directly the material parameters.<\/jats:p>\n               <jats:p>The goal of this paper is to analyse, compare and discuss these inverse identification methods, with particular focus on the FEMU, VFM, and ML methodologies. A heterogeneous tensile-load test is considered to compare in detail the FEMU, VFM, and ML strategies.<\/jats:p>","DOI":"10.1088\/1757-899x\/1238\/1\/012059","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T07:16:27Z","timestamp":1653981387000},"page":"012059","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["On the inverse identification methods for forming plasticity models using full-field measurements"],"prefix":"10.1088","volume":"1238","author":[{"given":"A","family":"Andrade-Campos","sequence":"first","affiliation":[]},{"given":"N","family":"Bastos","sequence":"additional","affiliation":[]},{"given":"M","family":"Conde","sequence":"additional","affiliation":[]},{"given":"M","family":"Gon\u00e7alves","sequence":"additional","affiliation":[]},{"given":"J","family":"Henriques","sequence":"additional","affiliation":[]},{"given":"R","family":"Louren\u00e7o","sequence":"additional","affiliation":[]},{"given":"J M P","family":"Martins","sequence":"additional","affiliation":[]},{"given":"M G","family":"Oliveira","sequence":"additional","affiliation":[]},{"given":"P","family":"Prates","sequence":"additional","affiliation":[]},{"given":"L","family":"Rumor","sequence":"additional","affiliation":[]}],"member":"266","reference":[{"key":"MSE_1238_1_012059bib1","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1007\/s00466-004-0589-6","article-title":"Sensitivity of the virtual fields method to noisy data","volume":"34","author":"Avril","year":"2004","journal-title":"Computational Mechanics"},{"key":"MSE_1238_1_012059bib2","first-page":"1","article-title":"Material parameter identification of elastoplastic constitutive models using machine learning approach","author":"Bastos","year":"2022"},{"key":"MSE_1238_1_012059bib3","author":"Baudin","year":"2015"},{"key":"MSE_1238_1_012059bib4","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1002\/nme.4287","article-title":"A dissipation gap method for full-field measurement-based identification of elasto-plastic material parameters","volume":"91","author":"Blaysat","year":"2012","journal-title":"International journal for numerical methods in engineering"},{"key":"MSE_1238_1_012059bib5","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s00170-008-1809-6","article-title":"Inverse technique identification of material parameters using finite element and neural network computation","volume":"44","author":"Chamekh","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"MSE_1238_1_012059bib6","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.jmatprotec.2006.03.214","article-title":"Inverse identification using the bulge test and artificial neural networks","volume":"177","author":"Chamekh","year":"2006","journal-title":"Journal of Materials Processing Technology"},{"key":"MSE_1238_1_012059bib7","first-page":"785","author":"Chen","year":"2016"},{"key":"MSE_1238_1_012059bib8","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/S1631-0721(02)01524-3","article-title":"Identification of damage fields using kinematic measurements","volume":"330","author":"Claire","year":"2002","journal-title":"Comptes Rendus M\u00e9canique"},{"key":"MSE_1238_1_012059bib9","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1002\/nme.1057","article-title":"A finite element formulation to identify damage fields: the equilibrium gap method","volume":"61","author":"Claire","year":"2004","journal-title":"International Journal for Numerical Methods in Engineering"},{"key":"MSE_1238_1_012059bib10","first-page":"1","article-title":"Principe des travaux virtuels et identification","volume":"309","author":"Gr\u00e9diac","year":"1989","journal-title":"Comptes rendus de l\u2019Acad\u00e9mie des sciences. S\u00e9rie 2, Mecanique, Physique, Chimie, Sciences de l\u2019univers, Sciences de la Terre"},{"key":"MSE_1238_1_012059bib11","author":"Gr\u00e9diac","year":"2012"},{"key":"MSE_1238_1_012059bib12","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1111\/j.1475-1305.2006.00283.x","article-title":"The virtual fields method for extracting constitutive parameters from full-field measurements: a review","volume":"42","author":"Grediac","year":"2006","journal-title":"Strain"},{"key":"MSE_1238_1_012059bib13","first-page":"1","article-title":"Identification of swift law parameters using femu by a synthetic image dic-based approach","author":"Henriques","year":"2022"},{"key":"MSE_1238_1_012059bib14","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/0020-7683(71)90015-1","article-title":"Finite element applications in the characterization of elastic solids","volume":"7","author":"Kavanagh","year":"1971","journal-title":"International Journal of Solids and Structures"},{"key":"MSE_1238_1_012059bib15","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.proeng.2017.10.769","article-title":"Characterization of dynamic hardening behavior using acceleration information","volume":"207","author":"Kim","year":"2017","journal-title":"Procedia Engineering"},{"key":"MSE_1238_1_012059bib16","author":"Kingma","year":"2017"},{"key":"MSE_1238_1_012059bib17","first-page":"153","article-title":"Mechanical design of ring tensile specimen via surrogate modelling for inverse material parameter identification","author":"Ktari","year":"2021"},{"key":"MSE_1238_1_012059bib18","doi-asserted-by":"publisher","DOI":"10.1111\/str.12350","article-title":"Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine","volume":"56","author":"Pascal","year":"2020","journal-title":"Strain"},{"key":"MSE_1238_1_012059bib19","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1137\/0720033","article-title":"Error estimate procedure in the finite element method and applications","volume":"20","author":"Ladeveze","year":"1983","journal-title":"SIAM Journal on Numerical Analysis"},{"key":"MSE_1238_1_012059bib20","doi-asserted-by":"crossref","DOI":"10.1007\/s00466-017-1411-6","article-title":"Sensitivity-based virtual fields for the non-linear virtual fields method","author":"Marek","year":"2017"},{"key":"MSE_1238_1_012059bib21","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1137\/0111030","article-title":"An algorithm for least-squares estimation of nonlinear parameters","volume":"11","author":"Marquardt","year":"1963","journal-title":"Journal of the society for Industrial and Applied Mathematics"},{"key":"MSE_1238_1_012059bib22","doi-asserted-by":"crossref","DOI":"10.1063\/1.5034964","article-title":"Identification of material parameters for plasticity models A comparative study on the finite element model updating and the virtual fields method","volume":"1960","author":"Martins","year":"2018","journal-title":"AIP Conference Proceedings"},{"key":"MSE_1238_1_012059bib23","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.ijmecsci.2018.07.013","article-title":"Comparison of inverse identification strategies for constitutive mechanical models using full-field measurements","volume":"145","author":"Martins","year":"2018","journal-title":"International Journal of Mechanical Sciences"},{"key":"MSE_1238_1_012059bib24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cma.2013.06.003","article-title":"The constitutive compatibility method for identification of material parameters based on full-field measurements","volume":"265","author":"Moussawi","year":"2013","journal-title":"Computer methods in applied mechanics and engineering"},{"key":"MSE_1238_1_012059bib25","first-page":"1","article-title":"On the optimisation efficiency for the inverse identification of constitutive model parameters","volume":"1","author":"Oliveira","year":"2021","journal-title":"ESAFORM 2021 [Online]"},{"key":"MSE_1238_1_012059bib26","doi-asserted-by":"crossref","first-page":"2993","DOI":"10.1016\/j.ijsolstr.2010.06.022","article-title":"Extension of the virtual fields method to elasto-plastic material identification with cyclic loads and kinematic hardening","volume":"47","author":"Pierron","year":"2010","journal-title":"International Journal of Solids and Structures"},{"key":"MSE_1238_1_012059bib27","author":"Pierron","year":"2012"},{"key":"MSE_1238_1_012059bib28","author":"Pierron","year":"2012"},{"key":"MSE_1238_1_012059bib29","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1002\/nme.2908","article-title":"A fully integrated noise robust strategy for the identification of constitutive laws from digital images","volume":"84","author":"R\u00e9thor\u00e9","year":"2010","journal-title":"International Journal for Numerical Methods in Engineering"},{"key":"MSE_1238_1_012059bib30","article-title":"Tabular data","author":"Shwartz-Ziv","year":"2021"},{"key":"MSE_1238_1_012059bib31","author":"Wirgin","year":"2004"},{"key":"MSE_1238_1_012059bib32","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.ijplas.2010.08.003","article-title":"A self-optimizing inverse analysis method for estimation of cyclic elasto-plasticity model parameters","volume":"27","author":"Yun","year":"2011","journal-title":"International Journal of Plasticity"}],"container-title":["IOP Conference Series: Materials Science and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1757-899X\/1238\/1\/012059","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1757-899X\/1238\/1\/012059\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1757-899X\/1238\/1\/012059\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1757-899X\/1238\/1\/012059\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T07:16:49Z","timestamp":1653981409000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1757-899X\/1238\/1\/012059"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,1]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,5,1]]}},"URL":"https:\/\/doi.org\/10.1088\/1757-899x\/1238\/1\/012059","relation":{},"ISSN":["1757-8981","1757-899X"],"issn-type":[{"value":"1757-8981","type":"print"},{"value":"1757-899X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,1]]},"assertion":[{"value":"On the inverse identification methods for forming plasticity models using full-field measurements","name":"article_title","label":"Article Title"},{"value":"IOP Conference Series: Materials Science and Engineering","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"Published under licence by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}