{"id":"W4410084235","doi":"10.1016/j.applthermaleng.2025.126564","title":"Heat transfer enhancement in shell and tube Latent Heat Thermal Energy Storage units for waste heat recovery applications: A 3D numerical study on melting–solidification kinetics","year":2025,"lang":"en","type":"article","venue":"Applied Thermal Engineering","topic":"Phase Change Materials Research","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Région Hauts-de-France; GDF Suez","keywords":"Materials science; Thermal energy storage; Heat transfer; Latent heat; Tube (container); Thermodynamics; Kinetics; Waste heat; Waste heat recovery unit; Thermal; Nuclear engineering; Shell and tube heat exchanger; Waste management; Composite material; Heat exchanger; Engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002480129,0.0003437531,0.0003702165,0.0003048487,0.00006103257,0.00006945631,0.000206769,0.0001210362,0.00001779637],"category_scores_gemma":[0.00001098427,0.0003581211,0.00003416461,0.0005080122,0.00001800622,0.00007310503,0.00005589083,0.0002028355,0.000004746135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002571618,"about_ca_system_score_gemma":0.00001961637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003494188,"about_ca_topic_score_gemma":0.000004952145,"domain_scores_codex":[0.9984095,0.00003147102,0.0004285056,0.0004071503,0.0002148085,0.0005085628],"domain_scores_gemma":[0.9993382,0.0001628281,0.000004835587,0.0003547666,0.00004285744,0.00009654972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009853548,0.0001449019,0.000006247744,0.0001483277,0.00005568501,0.000001728231,0.000294498,0.3682762,0.6269805,0.0002483334,0.000004574754,0.003740432],"study_design_scores_gemma":[0.001629776,0.0002187726,0.00042559,0.00009957326,0.00003376166,0.000001003966,0.0001504586,0.3277034,0.6682895,0.0000103605,0.001044572,0.0003932046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7991465,0.0003849503,0.1980288,0.00004078474,0.0001703191,0.001578432,0.00002673614,0.0001901772,0.0004332792],"genre_scores_gemma":[0.9961718,0.0000900919,0.0002600834,0.00004584543,0.000133181,0.003133299,0.00005475155,0.000089476,0.00002148595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1977687,"threshold_uncertainty_score":0.999887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157425742256232,"score_gpt":0.2442558064203476,"score_spread":0.2226815489977853,"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."}}