FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4312443079> ?p ?o ?g. }

• W4312443079 abstract "This article presents the application of machine learning (ML) algorithms in modeling the heat transfer correlations (e.g., Nusselt number and friction factor) for a heat exchanger with twisted tape inserts. The experimental data for the heat exchanger at different Reynolds numbers (Re), twist ratio (t), percentage of perforation (p), and a varied number of twisted tapes (n) were used for the correlation modeling. Three ML algorithms: polynomial regression (PR), random forest (RF), and artificial neural network (ANN) were used in the data-driven surrogate modeling. The hyperparameters of the ML models were carefully optimized to ensure generalizability. The performance parameters (e.g., R2 and mean absolute error (MAE)) of different ML algorithms were analyzed. It was observed that the ANN predictions of heat transfer coefficients outperform the predictions of PR and RF across different test datasets. Based on our analysis we make recommendations for future data-driven modeling efforts of heat transfer correlations and similar studies." @default.
• W4312443079 created "2023-01-04" @default.
• W4312443079 creator A5011144922 @default.
• W4312443079 creator A5047094130 @default.
• W4312443079 creator A5047401890 @default.
• W4312443079 creator A5054289982 @default.
• W4312443079 creator A5061116800 @default.
• W4312443079 date "2022-08-30" @default.
• W4312443079 modified "2023-09-28" @default.
• W4312443079 title "Machine learning assisted modeling of thermohydraulic correlations for heat exchangers with twisted tape inserts" @default.
• W4312443079 cites W1994848651 @default.
• W4312443079 cites W2002664102 @default.
• W4312443079 cites W2044350125 @default.
• W4312443079 cites W2046018838 @default.
• W4312443079 cites W2185727379 @default.
• W4312443079 cites W2771510793 @default.
• W4312443079 cites W2889821621 @default.
• W4312443079 cites W2901800918 @default.
• W4312443079 cites W2947859013 @default.
• W4312443079 cites W2970469194 @default.
• W4312443079 cites W2971252478 @default.
• W4312443079 cites W2981173151 @default.
• W4312443079 cites W2993639813 @default.
• W4312443079 cites W3000063884 @default.
• W4312443079 cites W3037409910 @default.
• W4312443079 cites W3042596241 @default.
• W4312443079 cites W3083856780 @default.
• W4312443079 cites W3100799996 @default.
• W4312443079 cites W3112215575 @default.
• W4312443079 cites W3114167306 @default.
• W4312443079 cites W3116478298 @default.
• W4312443079 cites W3133874009 @default.
• W4312443079 cites W3158247802 @default.
• W4312443079 cites W3159141515 @default.
• W4312443079 cites W3166130151 @default.
• W4312443079 cites W3167839193 @default.
• W4312443079 cites W3184945419 @default.
• W4312443079 cites W3185896196 @default.
• W4312443079 cites W3203999462 @default.
• W4312443079 cites W3204822876 @default.
• W4312443079 cites W4205478561 @default.
• W4312443079 cites W4205878948 @default.
• W4312443079 cites W4205924843 @default.
• W4312443079 cites W4210377122 @default.
• W4312443079 doi "https://doi.org/10.1007/s10409-022-22036-x" @default.
• W4312443079 hasPublicationYear "2022" @default.
• W4312443079 type Work @default.
• W4312443079 citedByCount "1" @default.
• W4312443079 countsByYear W43124430792023 @default.
• W4312443079 crossrefType "journal-article" @default.
• W4312443079 hasAuthorship W4312443079A5011144922 @default.
• W4312443079 hasAuthorship W4312443079A5047094130 @default.
• W4312443079 hasAuthorship W4312443079A5047401890 @default.
• W4312443079 hasAuthorship W4312443079A5054289982 @default.
• W4312443079 hasAuthorship W4312443079A5061116800 @default.
• W4312443079 hasBestOaLocation W43124430792 @default.
• W4312443079 hasConcept C105795698 @default.
• W4312443079 hasConcept C107706546 @default.
• W4312443079 hasConcept C119857082 @default.
• W4312443079 hasConcept C121332964 @default.
• W4312443079 hasConcept C130230704 @default.
• W4312443079 hasConcept C159985019 @default.
• W4312443079 hasConcept C182748727 @default.
• W4312443079 hasConcept C192562407 @default.
• W4312443079 hasConcept C196558001 @default.
• W4312443079 hasConcept C27158222 @default.
• W4312443079 hasConcept C2778456384 @default.
• W4312443079 hasConcept C2778527123 @default.
• W4312443079 hasConcept C33923547 @default.
• W4312443079 hasConcept C41008148 @default.
• W4312443079 hasConcept C50517652 @default.
• W4312443079 hasConcept C50644808 @default.
• W4312443079 hasConcept C97355855 @default.
• W4312443079 hasConceptScore W4312443079C105795698 @default.
• W4312443079 hasConceptScore W4312443079C107706546 @default.
• W4312443079 hasConceptScore W4312443079C119857082 @default.
• W4312443079 hasConceptScore W4312443079C121332964 @default.
• W4312443079 hasConceptScore W4312443079C130230704 @default.
• W4312443079 hasConceptScore W4312443079C159985019 @default.
• W4312443079 hasConceptScore W4312443079C182748727 @default.
• W4312443079 hasConceptScore W4312443079C192562407 @default.
• W4312443079 hasConceptScore W4312443079C196558001 @default.
• W4312443079 hasConceptScore W4312443079C27158222 @default.
• W4312443079 hasConceptScore W4312443079C2778456384 @default.
• W4312443079 hasConceptScore W4312443079C2778527123 @default.
• W4312443079 hasConceptScore W4312443079C33923547 @default.
• W4312443079 hasConceptScore W4312443079C41008148 @default.
• W4312443079 hasConceptScore W4312443079C50517652 @default.
• W4312443079 hasConceptScore W4312443079C50644808 @default.
• W4312443079 hasConceptScore W4312443079C97355855 @default.
• W4312443079 hasIssue "1" @default.
• W4312443079 hasLocation W43124430791 @default.
• W4312443079 hasLocation W43124430792 @default.
• W4312443079 hasOpenAccess W4312443079 @default.
• W4312443079 hasPrimaryLocation W43124430791 @default.
• W4312443079 hasRelatedWork W2017057604 @default.
• W4312443079 hasRelatedWork W2043942623 @default.
• W4312443079 hasRelatedWork W2067027371 @default.
• W4312443079 hasRelatedWork W2146407388 @default.
• W4312443079 hasRelatedWork W2484177594 @default.

• next