{"id":"W2513859524","doi":"10.1080/1573062x.2016.1223323","title":"A practical overview of unsteady pipe flow modeling: from physics to numerical solutions","year":2016,"lang":"en","type":"article","venue":"Urban Water Journal","topic":"Water Systems and Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Water hammer; Transient (computer programming); Confusion; Stability (learning theory); Computer science; Flow (mathematics); Unsteady flow; Numerical analysis; Applied mathematics; Engineering; Mechanics; Mechanical engineering; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001038671,0.001403108,0.0008323491,0.001710771,0.0006386884,0.002401033,0.001887532,0.002104463,0.004783342],"category_scores_gemma":[0.001812485,0.0008600172,0.0008476626,0.002390936,0.001970006,0.003436378,0.001506511,0.002538968,0.002994091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008813799,"about_ca_system_score_gemma":0.001084342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00193831,"about_ca_topic_score_gemma":0.001353143,"domain_scores_codex":[0.9993477,0.0002323291,0.0000621498,0.00007710187,0.0002503839,0.00003016515],"domain_scores_gemma":[0.9995284,0.0002225003,0.00005444103,0.0000628156,0.0001111422,0.00002066336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002789523,0.0001146619,0.0004877965,0.001387559,0.00002933032,0.0002277698,0.0003390378,0.1288132,0.005031265,0.6714708,0.02175509,0.1703157],"study_design_scores_gemma":[0.00001067565,0.000169007,0.0006315766,0.0007623043,0.00001834311,0.0004399576,0.0001469821,0.2587195,0.002383386,0.3869286,0.3497066,0.00008300916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001189485,0.03683983,0.9395849,0.002378775,0.0006487683,0.00006944765,0.0001258906,0.0004867944,0.01867608],"genre_scores_gemma":[0.07043323,0.2171156,0.6742793,0.001901408,0.003309113,0.000706434,0.0004960899,0.0006010498,0.03115781],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004783342,"threshold_uncertainty_score":0.01600182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06791399298666562,"score_gpt":0.2561112467963144,"score_spread":0.1881972538096488,"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."}}