DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, developers 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 developers manual for the DAKOTA software and describes the DAKOTA class hierarchies and their interrelationships. It derives directly from annotation of the actual source code and provides detailed class documentation, including all member functions and attributes.4

Computational thermal, chemical, fluid, and solid mechanics for geosystems management.

“…In our simplified RF analysis framework, depicted graphically in Figure 7.3-2, we used the SNL software package Dakota (Eldred et al 2007a(Eldred et al , 2007b(Eldred et al , 2007c as a driver and other user tools developed at SNL for constructing the discretized ̃ (ComputeKL), for taking the input RV realizations passed from Dakota via plain-text files and using them to generate realizations for ̃ (RealizeRF), and for passing this information to the given Sierra analysis codes. The mechanism we used was via entity identifiers, such as material blocks or element side sets, with the realization values embedded as variables into ExodusII databases.…”

Combining Simulation and Emulation for Calibrating Sequentially Reactive Transport Systems

“…More robust, automated approaches are needed to bring advanced theories in uncertainty quantification (UQ) to real-world applications. UQ tools, such as DAKOTA (Eldred et al 2002), NESSUS (Southwest Research Institute 2004), and iSIGHT (Engineous Software, Inc. 1998) have been used to model engineered systems. PSUADE (Tong 2005), which stands for Problem Solving environment for Uncertainty Analysis and Design Exploration, developed at Lawrence Livermore National Laboratory, was selected as the UQ and optimization tool of choice by the Department of Energy Advanced Simulation Capability for Environmental Management (ASCEM) program.…”

Optimal design of flexible pavements using a framework of DAKOTA and MEPDG

“…Such a platform was developed by intertwining MEPDG with Design Analysis Kit for Optimisation and Terascale Applications (DAKOTA). DAKOTA (Eldred et al 2006b) is a computational framework developed to facilitate rapid and systematic design studies using studyspecific simulator models. It allows analysts to efficiently execute iterative analyses of a simulator model including parametric studies, design of computer experiments, uncertainty quantification and optimisation.…”