DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's reference manual.

Abstract

The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. 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. 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.This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.4

A high heating rate pyrolysis model for the Phenolic Impregnated Carbon Ablator (PICA) based on mass spectroscopy experiments

“…In order to carry out the minimization process, PATO was interfaced with Dakota, an open source software developed by Sandia National Laboratories for optimization and uncertainty quantification [24]. Dakota provides several optimization algorithms, including gradient-based, genetic and surrogate-based methods.…”

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis (V.6.16 User's Manual)

“…Additional syntax features include use of the # symbol to indicate a comment, use of single or double quotes for string inputs (e.g., 'x1'), the use of commas and/or white space for separation of specifications, and the optional use of "=" symbols to indicate supplied data. See the DAKOTA Reference Manual [3] for additional details on this input file syntax.…”

VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations

“…Several other toolkits share a subset of the added values that VECMAtk provides. In the area of VVUQ, a well-known toolkit is Design Analysis for Optimization and Terascale Applications (DAKOTA) 1 [10], which provides a suite of algorithms for optimization, UQ, parameter studies, and model calibration. DAKOTA is a powerful tool, but has a relatively steep learning curve due to the large number of tools available [11] and offers no way to coordinate resources across concurrent runs [12,13].…”

“…All these components can be flexibly combined with other VECMAtk and third party components to create diverse application workflows. In addition, no single component is essential to all applications: for example FabSim3 and QCG-Client are to a limited degree interchangeable, and at least one application fully relies on a third party tool (the Mogp emulator 6 ) instead of EasyVVUQ.…”