{"id":"W4367048646","doi":"10.1007/s40571-023-00586-x","title":"Coupled elasto-softening contact models in DEM to predict the in-plane response of masonry walls","year":2023,"lang":"en","type":"article","venue":"Computational Particle Mechanics","topic":"Masonry and Concrete Structural Analysis","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Masonry; Unreinforced masonry building; Structural engineering; Softening; Brittleness; Discrete element method; Contact force; Shear (geology); Materials science; Unilateral contact; Geology; Geotechnical engineering; Finite element method; Mechanics; Composite material; Engineering; Physics; Classical mechanics","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":[0.0002526926,0.0004427292,0.000637214,0.0004702157,0.000427983,0.0005918908,0.00107146,0.00184424,0.003208963],"category_scores_gemma":[0.00129889,0.0005177231,0.0005564608,0.0005263436,0.0006049965,0.0006884388,0.0008342723,0.0008816082,0.0004570453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006389917,"about_ca_system_score_gemma":0.0005292809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01156631,"about_ca_topic_score_gemma":0.009491723,"domain_scores_codex":[0.9998627,0.00003321561,0.000007339338,0.00002347294,0.00004600536,0.00002724561],"domain_scores_gemma":[0.999493,0.0002606039,0.00004232558,0.00006515259,0.00009253835,0.00004632823],"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":[0.00001478929,0.00002799072,0.0004079555,0.00001165138,0.000008458194,0.00004343631,0.0000215251,0.9955699,0.0009531504,0.0009888613,0.0001320378,0.001820297],"study_design_scores_gemma":[0.000001434383,0.000001778333,0.00007693221,9.200041e-7,5.816687e-7,0.000002403544,0.000002346429,0.9996719,0.0001056747,0.0001034661,0.00003158039,9.712194e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6311415,0.0005078609,0.339572,0.00035402,0.0001369683,0.0001301548,0.0005140878,0.001101056,0.02654244],"genre_scores_gemma":[0.9880265,0.00008267788,0.008350044,0.00003613704,0.00001460808,0.00003742743,0.0001116591,0.00007407813,0.003266945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01156631,"threshold_uncertainty_score":0.02299798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0157890085759883,"score_gpt":0.2273070579306238,"score_spread":0.2115180493546355,"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."}}