{"id":32176,"date":"2026-04-08T14:12:57","date_gmt":"2026-04-08T12:12:57","guid":{"rendered":"https:\/\/www.dica.polimi.it\/?page_id=32176"},"modified":"2026-04-27T11:03:22","modified_gmt":"2026-04-27T09:03:22","slug":"ai3dcp","status":"publish","type":"page","link":"https:\/\/www.dica.polimi.it\/en\/ai3dcp\/","title":{"rendered":"Machine learning for 3D printing"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"32176\" class=\"elementor elementor-32176\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-924854b e-flex e-con-boxed e-con e-parent\" data-id=\"924854b\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5178144 elementor-widget elementor-widget-text-editor\" data-id=\"5178144\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>This page provides open-source machine learning codes and tools for 3D printing applications, developed by members of the Department of Civil and Environmental Engineering (DICA) at Politecnico di Milano, including Prof. Massimiliano Cremonesi, Giacomo Rizzieri and Federico Lanteri.<br \/><br \/><\/p><div class=\"et_pb_row et_pb_row_1\"><div class=\"et_pb_column et_pb_column_4_4 et_pb_column_1 et_pb_css_mix_blend_mode_passthrough et-last-child\"><div class=\"et_pb_module et_pb_text et_pb_text_1 et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><h4><strong>ShapeGen3DCP<\/strong><\/h4><\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-883f83c elementor-widget elementor-widget-spacer\" data-id=\"883f83c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1d031b0 e-flex e-con-boxed e-con e-parent\" data-id=\"1d031b0\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-0ae2ed9 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"0ae2ed9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><em><strong>ShapeGen3DCP<\/strong><\/em>\u202f is a fast and user-friendly open-source tool to predict the cross-sectional geometry of the printed layers in 3D Concrete Printing (3DCP) based on material and process parameters. The tool uses machine learning models trained on computational fluid dynamics simulations to provide rapid predictions, enabling optimization of printing parameters for desired outcomes.<br \/><span data-teams=\"true\">The dataset used for training and validation is available at <a id=\"menur4ln\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/doi.org\/10.5281\/zenodo.19473878\" href=\"https:\/\/doi.org\/10.5281\/zenodo.19473878\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Collegamento Zenodo DOI\">Zenodo DOI<\/a>. The pre-trained model and the Python implementation required to run it are publicly available on <a id=\"menur4lp\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/github.com\/polimi-3d-printing-ai\/shapegen3dcp\" href=\"https:\/\/github.com\/PoliMi-3D-Printing-AI\/ShapeGen3DCP\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Collegamento GitHub\">GitHub<\/a>.<\/span>\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a8c9c3 elementor-widget elementor-widget-image\" data-id=\"8a8c9c3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/shapegen3dcp.streamlit.app\/\">\n\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"120\" src=\"https:\/\/www.dica.polimi.it\/wp-content\/uploads\/2026\/04\/shapegen3dcp-300x120-1.png\" class=\"attachment-large size-large wp-image-32185\" alt=\"\" srcset=\"https:\/\/www.dica.polimi.it\/wp-content\/uploads\/2026\/04\/shapegen3dcp-300x120-1.png 300w, https:\/\/www.dica.polimi.it\/wp-content\/uploads\/2026\/04\/shapegen3dcp-300x120-1-18x7.png 18w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5787fe7 e-flex e-con-boxed e-con e-parent\" data-id=\"5787fe7\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-77b6f6f elementor-widget elementor-widget-spacer\" data-id=\"77b6f6f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-83ed6a1 elementor-widget elementor-widget-text-editor\" data-id=\"83ed6a1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>If you use ShapeGen3DCP in your work (e.g., books, articles, reports), please cite:<br \/><span data-teams=\"true\"><i>G. Rizzieri, F. Lanteri, L. Ferrara, M. Cremonesi, \u201cShapeGen3DCP: A deep learning framework for layer shape prediction in 3D concrete printing\u201d, Computers &amp; Structures 323 (2026) 108142. doi:<\/i><a id=\"menur2j8\" class=\"fui-Link ___1q1shib f2hkw1w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1s184ao f1mk8lai fnbmjn9 f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\/\/doi.org\/10.1016\/j.compstruc.2026.108142\" href=\"https:\/\/doi.org\/10.1016\/j.compstruc.2026.108142\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Collegamento 10.1016\/j.compstruc.2026.108142\"><i>10.1016\/j.compstruc.2026.108142<\/i><\/a><\/span><\/p><p>Click here to access the tool:\u00a0<strong><a href=\"https:\/\/shapegen3dcp.streamlit.app\/\" target=\"_blank\" rel=\"noopener\">ShapeGen3DCP \u2013 predict your 3D concrete printing cross-section \u00b7 Streamlit<\/a><\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9eaa7e8 elementor-widget elementor-widget-spacer\" data-id=\"9eaa7e8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>This page provides open-source machine learning codes and tools for 3D printing applications, developed by members of the Department of Civil and Environmental Engineering (DICA) at Politecnico di Milano, including&#8230;<\/p>","protected":false},"author":11,"featured_media":813,"parent":0,"menu_order":10,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"footnotes":""},"class_list":["post-32176","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/pages\/32176","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/comments?post=32176"}],"version-history":[{"count":23,"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/pages\/32176\/revisions"}],"predecessor-version":[{"id":32591,"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/pages\/32176\/revisions\/32591"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/media\/813"}],"wp:attachment":[{"href":"https:\/\/www.dica.polimi.it\/en\/wp-json\/wp\/v2\/media?parent=32176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}