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John Eddy

Researcher at Sandia National Laboratories

Publications -  20
Citations -  1618

John Eddy is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Engineering optimization & Uncertainty quantification. The author has an hindex of 11, co-authored 20 publications receiving 1552 citations. Previous affiliations of John Eddy include University at Buffalo.

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Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

TL;DR: This manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota’s iterative analysis capabilities.
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DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis.

TL;DR: The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides aible and extensible interface between simulation codes and iterative analysis methods.
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Visualization of Multidimensional Design and Optimization Data Using Cloud Visualization

TL;DR: The new technique, Cloud Visualization, is based upon representing sets of points as clouds in both the design and performance spaces and is applicable to both single and multiobjective optimization problems.