Matches in SemOpenAlex for { <https://semopenalex.org/work/W2915755087> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2915755087 endingPage "35" @default.
- W2915755087 startingPage "21" @default.
- W2915755087 abstract "Aquifer recharge and recovery systems (ARRS), which can broadly be analysed as seepage depth filters, in natural or engineered aquifers are gaining attention worldwide. Engineering predictions of their complex physical clogging behavior, however, continue to be challenging which has hindered the predictive maintenance of these systems for energy and materials savings. To address this problem statement, we leverage the homogenization theory with the multiscale perturbation analysis as the feature engineering step to reduce the complexity of the physical clogging behavior in ARRS. The analytical approach systematically derives a unique homogenized representation which quantifies the clogging condition at the macroscale. A series of physical parameters are identified from the derived homogenized representation to build a pre-processed input layer into our own multi-layered neural network (NN) architecture for predictive analysis. Measured data extracted from the literature is then used to train and verify the NN model. The trained model yields an average error deviation of 20% between the model's predictions and the respective measurements for an optimized set of hyperparameters tested. We then discuss quantitatively how the model can be adhered to predict the timing for a concerned ARRS to reach its breakthrough stage for a range of operational conditions. Finally, we also demonstrate how the homogenized representation can be useful to determine an arbitrary filter's critical reaction rate and diffusion coefficient responsible for its breakthrough stage." @default.
- W2915755087 created "2019-03-02" @default.
- W2915755087 creator A5071006586 @default.
- W2915755087 creator A5072808223 @default.
- W2915755087 date "2019-03-01" @default.
- W2915755087 modified "2023-10-16" @default.
- W2915755087 title "Feature engineering using homogenization theory with multiscale perturbation analysis for supervised model-based learning of physical clogging condition in seepage filters" @default.
- W2915755087 cites W1990749943 @default.
- W2915755087 cites W1993559969 @default.
- W2915755087 cites W2017146434 @default.
- W2915755087 cites W2020113935 @default.
- W2915755087 cites W2020691379 @default.
- W2915755087 cites W2024579509 @default.
- W2915755087 cites W2033008599 @default.
- W2915755087 cites W2033535792 @default.
- W2915755087 cites W2050572222 @default.
- W2915755087 cites W2060680089 @default.
- W2915755087 cites W2063766578 @default.
- W2915755087 cites W2077527063 @default.
- W2915755087 cites W2081171198 @default.
- W2915755087 cites W2081383799 @default.
- W2915755087 cites W2084709939 @default.
- W2915755087 cites W2100407778 @default.
- W2915755087 cites W2100667239 @default.
- W2915755087 cites W2104871393 @default.
- W2915755087 cites W2164175962 @default.
- W2915755087 cites W2426617844 @default.
- W2915755087 cites W2531004967 @default.
- W2915755087 cites W2600399923 @default.
- W2915755087 cites W2621806032 @default.
- W2915755087 cites W2789573576 @default.
- W2915755087 cites W3098140287 @default.
- W2915755087 cites W3099137143 @default.
- W2915755087 cites W3099996442 @default.
- W2915755087 cites W41744896 @default.
- W2915755087 doi "https://doi.org/10.1016/j.jocs.2019.02.003" @default.
- W2915755087 hasPublicationYear "2019" @default.
- W2915755087 type Work @default.
- W2915755087 sameAs 2915755087 @default.
- W2915755087 citedByCount "8" @default.
- W2915755087 countsByYear W29157550872019 @default.
- W2915755087 countsByYear W29157550872020 @default.
- W2915755087 countsByYear W29157550872021 @default.
- W2915755087 countsByYear W29157550872022 @default.
- W2915755087 countsByYear W29157550872023 @default.
- W2915755087 crossrefType "journal-article" @default.
- W2915755087 hasAuthorship W2915755087A5071006586 @default.
- W2915755087 hasAuthorship W2915755087A5072808223 @default.
- W2915755087 hasBestOaLocation W29157550872 @default.
- W2915755087 hasConcept C11413529 @default.
- W2915755087 hasConcept C130217890 @default.
- W2915755087 hasConcept C154945302 @default.
- W2915755087 hasConcept C155512373 @default.
- W2915755087 hasConcept C166957645 @default.
- W2915755087 hasConcept C18903297 @default.
- W2915755087 hasConcept C2778152828 @default.
- W2915755087 hasConcept C2778722038 @default.
- W2915755087 hasConcept C41008148 @default.
- W2915755087 hasConcept C50644808 @default.
- W2915755087 hasConcept C60908668 @default.
- W2915755087 hasConcept C86803240 @default.
- W2915755087 hasConcept C95457728 @default.
- W2915755087 hasConceptScore W2915755087C11413529 @default.
- W2915755087 hasConceptScore W2915755087C130217890 @default.
- W2915755087 hasConceptScore W2915755087C154945302 @default.
- W2915755087 hasConceptScore W2915755087C155512373 @default.
- W2915755087 hasConceptScore W2915755087C166957645 @default.
- W2915755087 hasConceptScore W2915755087C18903297 @default.
- W2915755087 hasConceptScore W2915755087C2778152828 @default.
- W2915755087 hasConceptScore W2915755087C2778722038 @default.
- W2915755087 hasConceptScore W2915755087C41008148 @default.
- W2915755087 hasConceptScore W2915755087C50644808 @default.
- W2915755087 hasConceptScore W2915755087C60908668 @default.
- W2915755087 hasConceptScore W2915755087C86803240 @default.
- W2915755087 hasConceptScore W2915755087C95457728 @default.
- W2915755087 hasLocation W29157550871 @default.
- W2915755087 hasLocation W29157550872 @default.
- W2915755087 hasOpenAccess W2915755087 @default.
- W2915755087 hasPrimaryLocation W29157550871 @default.
- W2915755087 hasRelatedWork W2099435776 @default.
- W2915755087 hasRelatedWork W2146632973 @default.
- W2915755087 hasRelatedWork W2620155290 @default.
- W2915755087 hasRelatedWork W2624354332 @default.
- W2915755087 hasRelatedWork W2915755087 @default.
- W2915755087 hasRelatedWork W2946835660 @default.
- W2915755087 hasRelatedWork W2951964800 @default.
- W2915755087 hasRelatedWork W2973451922 @default.
- W2915755087 hasRelatedWork W3094412894 @default.
- W2915755087 hasRelatedWork W4225307033 @default.
- W2915755087 hasVolume "32" @default.
- W2915755087 isParatext "false" @default.
- W2915755087 isRetracted "false" @default.
- W2915755087 magId "2915755087" @default.
- W2915755087 workType "article" @default.