FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2799685922> ?p ?o ?g. }

• W2799685922 endingPage "119" @default.
• W2799685922 startingPage "108" @default.
• W2799685922 abstract "The transport of solids in multiphase flows is common practice in energy industries due to the unavoidable extraction of solids from oil and gas bearing reservoirs. The persistent collision of solids to the pipeline can lead to erosion, i.e., the removal of internal surface of the pipeline. Reliable estimates of erosion rates are essential for designing and safely operating pipelines that transport solids. Prediction of erosion rates in multiphase flow is a complex problem due to the lack of accurate models for predicting particle movements in the flow and their impact velocities to the wall. The erosion-rate calculations also depend on the accuracy of the flow regime predictions in the pipeline. The comparisons of existing model predictions to experimental data revealed that the predictions might differ by several orders of magnitude for some operating conditions. The goal of this paper is to introduce a computational framework that estimates the model-prediction uncertainty of erosion-rate models. The inputs are a model predicting erosion rates and a database containing erosion-rate measurements at various operating conditions. The framework utilizes a non-parametric regression analysis, Gaussian Process Modeling (GPM), for estimating the model-prediction uncertainty. We compare two approaches for clustering the data prior to training GPMs: (1) a flow regime based clustering, and (2) a new clustering approach introduced in this paper. The results reveal that the new data clustering approach significantly shrinks the confidence intervals of the uncertainty estimates." @default.
• W2799685922 created "2018-05-17" @default.
• W2799685922 creator A5029733263 @default.
• W2799685922 creator A5031711223 @default.
• W2799685922 creator A5049704651 @default.
• W2799685922 creator A5056715372 @default.
• W2799685922 date "2018-08-01" @default.
• W2799685922 modified "2023-09-26" @default.
• W2799685922 title "Uncertainty quantification in erosion predictions using data mining methods" @default.
• W2799685922 cites W1970492033 @default.
• W2799685922 cites W1972883047 @default.
• W2799685922 cites W1973333099 @default.
• W2799685922 cites W1982048477 @default.
• W2799685922 cites W1988426958 @default.
• W2799685922 cites W1996422736 @default.
• W2799685922 cites W1999498580 @default.
• W2799685922 cites W2000469174 @default.
• W2799685922 cites W2007310394 @default.
• W2799685922 cites W2007928766 @default.
• W2799685922 cites W2022658703 @default.
• W2799685922 cites W2022970865 @default.
• W2799685922 cites W2026163264 @default.
• W2799685922 cites W2028216354 @default.
• W2799685922 cites W2033131661 @default.
• W2799685922 cites W2034468879 @default.
• W2799685922 cites W2036729857 @default.
• W2799685922 cites W2043433893 @default.
• W2799685922 cites W2043505214 @default.
• W2799685922 cites W2078335606 @default.
• W2799685922 cites W2081856556 @default.
• W2799685922 cites W2083862709 @default.
• W2799685922 cites W2088589160 @default.
• W2799685922 cites W2089247505 @default.
• W2799685922 cites W2092631686 @default.
• W2799685922 cites W2096045991 @default.
• W2799685922 cites W2120282157 @default.
• W2799685922 cites W2145475762 @default.
• W2799685922 cites W2147726312 @default.
• W2799685922 cites W2148425841 @default.
• W2799685922 cites W2163918679 @default.
• W2799685922 cites W2165835468 @default.
• W2799685922 cites W2174610466 @default.
• W2799685922 cites W2312997725 @default.
• W2799685922 cites W2331866400 @default.
• W2799685922 cites W2344757480 @default.
• W2799685922 cites W2548571075 @default.
• W2799685922 cites W2741397920 @default.
• W2799685922 cites W587438532 @default.
• W2799685922 cites W841998344 @default.
• W2799685922 doi "https://doi.org/10.1016/j.wear.2018.05.009" @default.
• W2799685922 hasPublicationYear "2018" @default.
• W2799685922 type Work @default.
• W2799685922 sameAs 2799685922 @default.
• W2799685922 citedByCount "13" @default.
• W2799685922 countsByYear W27996859222019 @default.
• W2799685922 countsByYear W27996859222020 @default.
• W2799685922 countsByYear W27996859222021 @default.
• W2799685922 countsByYear W27996859222022 @default.
• W2799685922 countsByYear W27996859222023 @default.
• W2799685922 crossrefType "journal-article" @default.
• W2799685922 hasAuthorship W2799685922A5029733263 @default.
• W2799685922 hasAuthorship W2799685922A5031711223 @default.
• W2799685922 hasAuthorship W2799685922A5049704651 @default.
• W2799685922 hasAuthorship W2799685922A5056715372 @default.
• W2799685922 hasConcept C105795698 @default.
• W2799685922 hasConcept C117251300 @default.
• W2799685922 hasConcept C119857082 @default.
• W2799685922 hasConcept C121332964 @default.
• W2799685922 hasConcept C123157820 @default.
• W2799685922 hasConcept C124101348 @default.
• W2799685922 hasConcept C127313418 @default.
• W2799685922 hasConcept C151730666 @default.
• W2799685922 hasConcept C175309249 @default.
• W2799685922 hasConcept C199360897 @default.
• W2799685922 hasConcept C2779379648 @default.
• W2799685922 hasConcept C33923547 @default.
• W2799685922 hasConcept C38349280 @default.
• W2799685922 hasConcept C39432304 @default.
• W2799685922 hasConcept C41008148 @default.
• W2799685922 hasConcept C43521106 @default.
• W2799685922 hasConcept C57879066 @default.
• W2799685922 hasConcept C73555534 @default.
• W2799685922 hasConcept C87717796 @default.
• W2799685922 hasConceptScore W2799685922C105795698 @default.
• W2799685922 hasConceptScore W2799685922C117251300 @default.
• W2799685922 hasConceptScore W2799685922C119857082 @default.
• W2799685922 hasConceptScore W2799685922C121332964 @default.
• W2799685922 hasConceptScore W2799685922C123157820 @default.
• W2799685922 hasConceptScore W2799685922C124101348 @default.
• W2799685922 hasConceptScore W2799685922C127313418 @default.
• W2799685922 hasConceptScore W2799685922C151730666 @default.
• W2799685922 hasConceptScore W2799685922C175309249 @default.
• W2799685922 hasConceptScore W2799685922C199360897 @default.
• W2799685922 hasConceptScore W2799685922C2779379648 @default.
• W2799685922 hasConceptScore W2799685922C33923547 @default.
• W2799685922 hasConceptScore W2799685922C38349280 @default.
• W2799685922 hasConceptScore W2799685922C39432304 @default.
• W2799685922 hasConceptScore W2799685922C41008148 @default.

• next