Professor Camila Caiado's Outputs (3)

Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques (2020)
Presentation / Conference Contribution
Formentin, H. N., Vernon, I., Goldstein, M., Caiado, C., Avansi, G., & Schiozer, D. (2020, September). Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques. Presented at ECMOR XVII

Model discrepancy specifies unavoidable differences between a physical system and its corresponding computer model. Incomplete information, simplifications and lack of knowledge about the physical state originate model discrepancy. Misevaluation of m... Read More about Accounting for Model Discrepancy in Uncertainty Analysis by Combining Numerical Simulation and Bayesian Emulation Techniques.

Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis (2020)
Journal Article
Ferreira, C., Vernon, I., Caiado, C., Formentin, H., Avansi, G., Goldstein, M., & Schiozer, D. (2020). Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis. SPE Journal, 25(4), 2119-2142. https://doi.org/10.4043/29801-ms

When performing classic uncertainty reduction based on dynamic data, a large number of reservoir simulations need to be evaluated at high computational cost. As an alternative, we construct Bayesian emulators that mimic the dominant behaviour of the... Read More about Efficient Selection of Reservoir Model Outputs within an Emulation-Based Bayesian History Matching Uncertainty Analysis.

A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification (2020)
Journal Article
Howitt, S. H., Oakley, J., Caiado, C., Goldstein, M., Malagon, I., McCollum, C., & Grant, S. W. (2020). A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification. Critical Care Medicine, 48(1), e18-e25. https://doi.org/10.1097/ccm.0000000000004074

Objectives: The Kidney Disease: Improving Global Outcomes urine output criteria for acute kidney injury lack specificity for identifying patients at risk of adverse renal outcomes. The objective was to develop a model that analyses hourly urine outpu... Read More about A Novel Patient-Specific Model for Predicting Severe Oliguria; Development and Comparison With Kidney Disease: Improving Global Outcomes Acute Kidney Injury Classification.