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What can simulation test beds teach us about social science? Results of the ground truth program

Computational and Mathematical Organization Theory

Naugle, Asmeret B.; Krofcheck, Daniel J.; Warrender, Christina E.; Lakkaraju, Kiran L.; Swiler, Laura P.; Verzi, Stephen J.; Emery, Benjamin F.; Murdock, Jaimie; Bernard, Michael L.; Romero, Vicente J.

The ground truth program used simulations as test beds for social science research methods. The simulations had known ground truth and were capable of producing large amounts of data. This allowed research teams to run experiments and ask questions of these simulations similar to social scientists studying real-world systems, and enabled robust evaluation of their causal inference, prediction, and prescription capabilities. We tested three hypotheses about research effectiveness using data from the ground truth program, specifically looking at the influence of complexity, causal understanding, and data collection on performance. We found some evidence that system complexity and causal understanding influenced research performance, but no evidence that data availability contributed. The ground truth program may be the first robust coupling of simulation test beds with an experimental framework capable of teasing out factors that determine the success of social science research.

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Sensitivity and Uncertainty Analysis of Generator Failures under Extreme Temperature Scenarios in Power Systems

Emery, Benjamin F.; Staid, Andrea S.; Swiler, Laura P.

This report summarizes work done under the Verification, Validation, and Uncertainty Quantification (VVUQ) thrust area of the North American Energy Resilience Model (NAERM) Program. The specific task of interest described in this report is focused on sensitivity analysis of scenarios involving failures of both wind turbines and thermal generators under extreme cold-weather temperature conditions as would be observed in a Polar Vortex event.

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2 Results
2 Results