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Abstract: Keywords: [\/et_pb_text][et_pb_button button_url=”https:\/\/revija-ventil.si\/wp-content\/uploads\/arctur_2023_12.pdf” url_new_window=”on” button_text=”Download PDF” admin_label=”Gumb Prenesi PDF” _builder_version=”4.23.4″ custom_button=”on” button_text_size=”15px” button_text_color=”#00868a” button_bg_color=”rgba(0,0,0,0)” button_border_color=”#00868a” button_icon=”||divi||400″ custom_margin=”||0px||false|false” custom_margin_tablet=”||20px||false|false” custom_margin_phone=”” custom_margin_last_edited=”on|desktop” custom_padding=”||||false|false” locked=”off” global_colors_info=”{}” button_border_color__hover_enabled=”on|hover” button_border_color__hover=”#00868a”][\/et_pb_button][et_pb_post_nav in_same_term=”on” prev_text=”Older entries” next_text=”Newer entries” admin_label=”Navigacija po objavah” _builder_version=”4.3.3″ custom_margin=”||||false|false” custom_margin_phone=”||||false|false” custom_margin_last_edited=”off|desktop” custom_padding=”20px||||false|false” custom_padding_tablet=”0px||0px||false|false” custom_padding_phone=”0px||0px||false|false” custom_padding_last_edited=”on|tablet” title_text_color_last_edited=”off|desktop” global_module=”11763″ locked=”off” global_colors_info=”{}” title_text_color__hover_enabled=”on|desktop” title_text_color__hover=”#212b31″][\/et_pb_post_nav][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”]<\/p>\n [et_pb_sidebar orientation=”right” area=”et_pb_widget_area_4″ disabled_on=”on|on|off” _builder_version=”4.3.3″ global_module=”11764″ global_colors_info=”{}”][\/et_pb_sidebar]<\/p>\n [\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" The success story presented in this article was developed during the first tranche of the R&D H2020 FF4EuroHPC Project. Partners Optimad, Aidro and CINECA teamed up to address specific business challenge in the manufacturing sector and overcome it with the help of High Performance Computing.<\/p>\n","protected":false},"author":5,"featured_media":15072,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[153,154],"tags":[],"class_list":["post-15079","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-exposed-articles","category-science-and-expert-articles"],"_links":{"self":[{"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/posts\/15079","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/comments?post=15079"}],"version-history":[{"count":2,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/posts\/15079\/revisions"}],"predecessor-version":[{"id":15081,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/posts\/15079\/revisions\/15081"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/media\/15072"}],"wp:attachment":[{"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/media?parent=15079"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/categories?post=15079"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/revija-ventil.si\/en\/wp-json\/wp\/v2\/tags?post=15079"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
<\/strong>The success story presented in this article was developed during the first tranche of the R&D H2020 FF4EuroHPC Project. Partners Optimad, Aidro and CINECA teamed up to address specific business challenge in the manufacturing sector and overcome it with the help of High Performance Computing. Micro Channel Heat Exchanger (MCHE) are heat exchangers in which the fluid flows in lateral confinements with dimensions of millimeters. Thanks to the high volumetric heat flux, compactness, and efficient flow distribution, they offer several advantages over standard exchangers. The traditional design approach for MCHE requires several iterations before the final configuration is established, leading to significant R&D costs, long time-to-market, and expensive experimental campaigns. In practice, due to budget constraints, only a few configurations are assessed, resulting in sub-optimal design which negatively impacts the competitiveness of the final product. An innovative solution was developed as a SaaS platform, which integrates a set of computational tools for topology optimization of MCHX in an HPC-centric framework. TOLOMHE represents the first step towards cloud services for topology optimization and generative design offered to SMEs specialized in manufacturing for MCHX. <\/p>\n
<\/strong>FF4EuroHPC, Micro Channel Heat Exchanger, optimization, CFD simulation, machine learning, innovation<\/p>\n