{"id":"W4399759776","doi":"10.1016/j.compstruc.2024.107453","title":"A thermal model for topology optimization in additive manufacturing: Design of support structures and geometry orientation","year":2024,"lang":"en","type":"article","venue":"Computers & Structures","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Engineering Link (Canada)","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Topology optimization; Orientation (vector space); Geometry; Thermal; Topology (electrical circuits); Mechanical engineering; Mathematics; Computer science; Engineering; Finite element method; Structural engineering; Physics; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003172945,0.0008173138,0.001160792,0.0005152551,0.0004651605,0.0009729007,0.001588554,0.00199289,0.004067263],"category_scores_gemma":[0.0009412021,0.0007050729,0.001023755,0.0008653554,0.0006339469,0.001070305,0.0005443466,0.0008779537,0.001040328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005582383,"about_ca_system_score_gemma":0.0009559449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002755768,"about_ca_topic_score_gemma":0.003456635,"domain_scores_codex":[0.9998127,0.00004712261,0.000007599418,0.00003085246,0.0000818992,0.00001990097],"domain_scores_gemma":[0.999786,0.00009471922,0.00002461594,0.00002829362,0.00005273527,0.00001371385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004295353,0.000009568872,0.00003063435,0.00001331822,0.000002654393,0.000008948,0.000005650326,0.9930247,0.0006978177,0.003941678,0.0001519193,0.002108843],"study_design_scores_gemma":[0.000002257184,0.000004609945,0.00001585199,0.000001597533,0.000002164449,0.000004541349,0.000001914975,0.9982675,0.0001657092,0.001220726,0.0003112939,0.000001693909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01479635,0.0003115381,0.9687371,0.0002249665,0.00007015569,0.00005692521,0.0001569167,0.0002519378,0.01539418],"genre_scores_gemma":[0.7556717,0.001028349,0.2200817,0.0002282285,0.0001025134,0.0004442722,0.0003948448,0.0004831994,0.02156506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004067263,"threshold_uncertainty_score":0.01360637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035599432416865,"score_gpt":0.2339399350386618,"score_spread":0.2235839407144932,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}