Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

Dalbey, Keith; Eldred, Michael; Geraci, Gianluca; Jakeman, John Davis; Maupin, Kathryn; Monschke, Jason; Seidl, Daniel; Swiler, Laura Painton; Tran, Anh; Menhorn, Friedrich; Zeng, Xiaobo

doi:10.2172/1630693

Cited by 21 publications

(12 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Best fit metabolism values were determined using open-source non-gradient-based optimization methods, DAKOTA. 99…”

Section: Resultsmentioning

confidence: 99%

A physiologically based model to capture species-dependent differences in oxygen distribution in the posterior eye

German¹,

Boyer²,

Przekwas³

et al. 2021

MAIO

View full text Add to dashboard Cite

Ocular barriers to drug transport make delivery of effective doses to posterior targets exceptionally difficult. Animal models have commonly been used to evaluate drug distribution and penetrability, but translational tools to determine human dosing are lacking. Here we present a framework for modeling interspecies variation by simulating oxygen distribution in the posterior eye, from outer vitreous to the sclera. Posterior eye models of mouse, rabbit, and human are presented with modifications based solely on species-dependent anatomical and physiological differences. The model includes tissue and vascular contributions to transport. In addition to oxygen, nitric oxide and its impact on oxygen metabolism is simulated. Depth-dependent retinal oxygen partial pressure profiles are in good agreement with experimental data for all three species. The model can be further extended to evaluate the variations of retinal oxygenation in response to various drugs, formulations, administration protocols, and treatment plans. Further, this framework of ocular physiologically based pharmacokinetic/pharmacodynamic models could support animal to human translation, a critical step in the drug development process.

show abstract

“…Best fit metabolism values were determined using open-source non-gradient-based optimization methods, DAKOTA. 99…”

Section: Resultsmentioning

confidence: 99%

A physiologically based model to capture species-dependent differences in oxygen distribution in the posterior eye

German¹,

Boyer²,

Przekwas³

et al. 2021

MAIO

View full text Add to dashboard Cite

show abstract

“…BO is a flexible optimization framework that naturally lends itself to multi-fidelity [66,67], multi-objective [68,69] optimization problems with applications to computational solid mechanics [70,71,72] and fluid mechanics [73]. It is also worthy to mention that the asynchronous parallel feature for HPC is currently supported in DAKOTA [74].…”

Section: Discussionmentioning

confidence: 99%

Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers

Tran¹

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Bayesian optimization (BO) is a flexible and powerful framework that is suitable for computationally expensive simulation-based applications and guarantees statistical convergence to the global optimum. While remaining as one of the most popular optimization methods, its capability is hindered by the size of data, the dimensionality of the considered problem, and the nature of sequential optimization. These scalability issues are intertwined with each other and must be tackled simultaneously. In this work, we propose the Scalable 3 -BO framework, which employs sparse GP as the underlying surrogate model to scope with Big Data and is equipped with a random embedding to efficiently optimize high-dimensional problems with low effective dimensionality. The Scalable 3 -BO framework is further leveraged with asynchronous parallelization feature, which fully exploits the computational resource on HPC within a computational budget. As a result, the proposed Scalable 3 -BO framework is scalable in three independent perspectives: with respect to data size, dimensionality, and computational resource on HPC. The goal of this work is to push the frontiers of BO beyond its well-known scalability issues and minimize the wall-clock waiting time for optimizing high-dimensional computationally expensive applications. We demonstrate the capability of Scalable 3 -BO with 1 million data points, 10,000-dimensional problems, with 20 concurrent workers in an HPC environment.

show abstract

“…This approach gives fuel qualification efforts the advantage of taking previously established material behaviors and relationships from historical fuel designs and enabling rapid digital prototyping of new fuel designs by the use of HPC and sensitivity studies (e.g., Dakota 102 ). As a fuel design concept transitions into experimental reality, it can do so with a higher degree of confidence and with characterization plans derived from the physicsbased modeling results of different phenomena.…”

Section: Ivd Integrated Plan Reviewmentioning

confidence: 99%

Integrating Advanced Modeling and Accelerated Testing for a Modernized Fuel Qualification Paradigm

et al. 2021

View full text Add to dashboard Cite

With the increasing interest in sodium fast reactor technology, as seen by applications to the U.S. Nuclear Regulatory Commission for the OKLO Aurora plant, fuel testing for the TerraPower Traveling Wave Reactor, and the impending construction and startup of the versatile test reactor (VTR), a modernized, accelerated approach to fuel qualification is needed. To guide this effort, a Phenomena Identification Ranking Table-styled analysis was performed for a U-Pu-Zr sodium-free annular fuel system. This analysis evaluated a series of fuel design properties and parameters against their contributions to key fuel performance phenomena. The resulting priority parameters were then reviewed against existing modeling and experimental capabilities to support investigation of the highest-priority parameters. A pathway for qualification was then established using highthroughput, high-volume experiments from MiniFuel and FAST in parallel with advanced physics-based model development. This effort outlines how the first stages of qualification can be reduced from the typical 20+-year development cycle to 5 to 7 years by deploying accelerated irradiation testing platforms. As with any accelerated test, these methods are prototypic in some aspects and less so in others; however, by coupling with advanced fuel performance modeling and simulation capabilities, the larger space of irradiation parameters and material response provided offers advantages for the validation of physics-based models supporting the deployment of novel fuel designs. As a test case, this paper utilizes a proposed Mark II fuel system for the upcoming VTR. Thus, an accelerated qualification method can be tested for the development of MARK II driver fuel so that by the time of VTR startup, lead test assemblies for a Mark II fuel can be initiated.

show abstract

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

Cited by 21 publications

References 0 publications

A physiologically based model to capture species-dependent differences in oxygen distribution in the posterior eye

A physiologically based model to capture species-dependent differences in oxygen distribution in the posterior eye

Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers

Integrating Advanced Modeling and Accelerated Testing for a Modernized Fuel Qualification Paradigm

Contact Info

Product

Resources

About