Simulating Hydraulic Fracture Stimulations at the EGS Collab: Model Validation from Experiments 1 and Design-Phase Simulation for Experiment 2
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Geosciences↗
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Results for “model validation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Testing and Model Validation of a Prototype Moving Packed-Bed Particle-to-sCO2 Heat Exchanger.
Abstract not provided.
Albrecht, Kevin↗
Processing Random and Systematic Experimental Uncertainties in Replicate Tests of Stochastic Phenomena for Real-Space Model Validation.
Abstract not provided.
Romero, Vicente J.↗
Relationships between ASME VV 10 & 20 AIAA CFD and Real Space Model Validation Frameworks.
Abstract not provided.
Romero, Vicente J.↗
Instrumented Modules for Mechanical Environment Characterization and Simulation Model Validation.
Abstract not provided.
Maes, Ashley↗
Instrumented Modules for Mechanical Environment Characterization and Simulation Model Validation.
Abstract not provided.
Maes, Ashley↗
Cyber Threat Modeling & Validation: Port Scanning & Detection.
Abstract not provided.
Vugrin, Eric D.↗
mystic: tools for AI, UQ, ML, model validation, and robust design under uncertainty
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McKerns, Michael↗
Model Validation of Falling Particle Receivers with On-sun Experiments.
Abstract not provided.
Mills, Brantley↗
Finite element model validation of transverse strain sensing Fiber Bragg Gratings.
Abstract not provided.
Gouws, Andre↗
Introduction to the Real Space Model Validation Approach and Its Advantages vs. the ASME VV10 and VV20 Validation Approaches.
Abstract not provided.
Romero, Vicente↗
Modeling and Simulation of TREAT with Thermal Graphite Model Validation
MOCkingbird LDRD final poster.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Confined circular arc geometry tests for high explosive model validation
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42 ENGINEERING↗
In-situ Measurements of Hydrogen-Titanium Plasma-Material Interactions for Model Validation
Final performance report for our DOE grant
Sankaran, Mohan [University of Illinois Urbana-Cha↗
Learning the Task Management Space of an Aircraft Approach Model
Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.
Validation↗