![]() By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. ![]() These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Dakota contains algorithms for optimization with gradient and nongradient-based methods uncertainty quantification with sampling, reliability, and stochastic expansion methods parameter estimation with nonlinear least squares methods and sensitivity/variance analysis with design of experiments and parameter study methods. ![]() ![]() The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. ![]()
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