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Full-Text Articles in Engineering
A Data-Driven Approach For Predicting Nepheline Crystallization In High-Level Waste Glasses, Irmak Sargin, Charmayne E. Lonergan, John D. Vienna, John S. Mccloy, Scott P. Beckman
A Data-Driven Approach For Predicting Nepheline Crystallization In High-Level Waste Glasses, Irmak Sargin, Charmayne E. Lonergan, John D. Vienna, John S. Mccloy, Scott P. Beckman
Materials Science and Engineering Faculty Research & Creative Works
High-level waste (HLW) glasses with high alumina content are prone to nepheline crystallization during the slow canister cooling that is experienced during large-scale production. Because of its detrimental effects on glass durability, nepheline (NaAlSiO4) precipitation must be avoided; however, developing robust, predictive models for nepheline crystallization behavior in compositionally complex HLW glasses is difficult. Using overly conservative constraints to predict nepheline formation can limit the waste loading to lower than the achievable capacity. In this study, a robust data-driven model using five compositional features has been developed to predict nepheline formation. A new descriptor is introduced called the …
A Data-Driven Approach For Winter Precipitation Classification Using Weather Radar And Nwp Data, Bong Chul Seo
A Data-Driven Approach For Winter Precipitation Classification Using Weather Radar And Nwp Data, Bong Chul Seo
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study describes a framework that provides qualitative weather information on winter precipitation types using a data-driven approach. The framework incorporates the data retrieved from weather radars and the numerical weather prediction (NWP) model to account for relevant precipitation microphysics. To enable multimodel-based ensemble classification, we selected six supervised machine learning models: k-nearest neighbors, logistic regression, support vector machine, decision tree, random forest, and multi-layer perceptron. Our model training and cross-validation results based on Monte Carlo Simulation (MCS) showed that all the models performed better than our baseline method, which applies two thresholds (surface temperature and atmospheric layer thickness) for …
Utility Of Vertically Integrated Liquid Water Content For Radar-Rainfall Estimation: Quality Control And Precipitation Type Classification, Bong Chul Seo, Witold F. Krajewski, Youcun Qi
Utility Of Vertically Integrated Liquid Water Content For Radar-Rainfall Estimation: Quality Control And Precipitation Type Classification, Bong Chul Seo, Witold F. Krajewski, Youcun Qi
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study proposes a new estimation method for vertically integrated liquid water content (VIL) using radar reflectivity volume data and temperature sounding retrieved from the numerical weather model analysis. This method addresses uncertainty factors in conventional VIL estimation associated with the effects from the bright band (BB) and radar beam geometry near the radar site. The new VIL is then used for precipitation classification (convective/stratiform) and wind turbine clutter detection in the hope that the estimated VIL indicating vertical activities or development of precipitation systems will account for the two independent subjects together, in opposite ways. The non-precipitation radar echoes …