Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.16 Theory Manual

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

doi:10.2172/1868423

Cited by 11 publications

(5 citation statements)

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“…The four output parameters that would be observed included: total bundle pressure drop, peak cladding temperature at the 19g2 thermocouple location, quench time at the 19g2 thermocouple location (defined as the time when temperature drops below 200 C), and droplet carryover at the bundle exit. Dakota (Dalbey, 2022) was used to drive the sensitivity analysis. A Latin hypercube sampling method was used to generate the combinations of input parameters.…”

Section: Sensitivity Studymentioning

confidence: 99%

Comparison Between Pin-by-Pin Subchannel and System Level Thermal Hydraulic Results for High Burnup Loss-of-Coolant Applications

Salko Jr.,

Wysocki,

Hizoum

et al. 2023

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This milestone report summarizes recent work to investigate higher fidelity modeling and simulation practices for large-break loss-of-coolant accident (LBLOCA) analysis in high-burnup pressurized water reactor (PWR) cores. Because of current industry interest in extending fuel cycle lengths ranging from 18 to 24-months, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been investigating the susceptibility of high-burnup core designs to fuel fragmentation, release, and dispersal (FFRD) during accident conditions such as LBLOCA. This work has prioritized developing and demonstrating a methodology for calculating core-wide susceptibility to FFRD and addressing uncertainties identified in the analysis and the US Nuclear Regulatory Commission (NRC) Research Information Letter on FFRD. Part of this investigation seeks to quantify differences between system-level thermal hydraulic behavior and higher fidelity subchannel modeling methods to identify potential safety concerns or opportunities to minimize FFRD susceptibility.To this end, the NEAMS subchannel code, CTF, is being used, along with the NRC system analysis code TRACE, for analysis of LBLOCA in a core containing high-burnup fuel. This project includes two thrusts: (1) improving on the existing TRACE model for a 4-loop PWR for LBLOCA so that the model is higher fidelity and consistent with current USNRC best practices, and (2) using CTF to perform pinresolved modeling of the core region of the reflood phase of a LBLOCA in a high-burnup PWR.Although CTF includes a wide range of closure models for modeling LOCA conditions, these models have not been assessed during recent CTF development activities, so the first step is to validate CTF using loss-of-coolant accident (LOCA) reflood experiments. A sensitivity study was also performed to identify high-impact models, which were then reviewed and corrected as needed. To strengthen the assessment, a code-to-code benchmark was performed against TRACE for these conditions. Both highand low-flooding rate tests from the FEBA reflood experiments were modeled using lumped and pinresolved CTF models, and the models were compared against lumped pin TRACE results. The lumped CTF and TRACE models demonstrated good agreement with experimental peak cladding temperatures (PCT) for all axial levels except near the top of the bundle. CTF pin-resolved PCT predictions were good for all thermocouple locations except for those facing the center subchannel, which were predicted to be about 40 K too low. A study on radial effects on the pin-resolved model was performed, and advanced CTF spacer grid droplet breakup and quenching models were tested to demonstrate the impact on better cooling the top of the bundle for better agreement with experimental data.Several modifications and improvements were made to the full-system TRACE model in this work, to better align the model with industry and NRC best practices and improve the accuracy of the LBLOCA predictions. This included converting to the best-practice 3D vessel comp...

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Section: Sensitivity Studymentioning

confidence: 99%

Comparison Between Pin-by-Pin Subchannel and System Level Thermal Hydraulic Results for High Burnup Loss-of-Coolant Applications

Salko Jr.,

Wysocki,

Hizoum

et al. 2023

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“…To assess the impact of the experimental uncertainties on SAM predictions, a forward propagation UQ study was done using Dakota 6.16 [48]. Latin hypercube sampling (LHS) was used to perform the analysis with three uncertain parameters, which are summarized in Table 5-2.…”

Section: 𝑣 = 𝐶 𝑗 + 𝑣 (12)mentioning

confidence: 99%

Development of Integrated Thermal Fluids Modeling Capability for MSRs

Fang

Nunez

et al. 2022

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The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad class of light-water and advanced reactor concepts. The research and development approach under thermal fluids technical area synergistically combines three length and time scales in a hierarchal multi-scale approach. To demonstrate the feasibility and capabilities of a multi-scale thermal fluids capability using these codes, a key joint effort has been pursued to develop an integrated systemand engineering-scale thermal fluids analysis capability with the MOOSE-based codes, through integration of SAM and Pronghorn, both based on the MOOSE framework.

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“…In the past decades, multiple general purpose MDAO platforms with different focuses, like DAKOTA [4] and OpenMDAO [5], have been developed from different engineering backgrounds. They can also be used to solve MDAO problems in the wind energy field.…”

Section: Introductionmentioning

confidence: 99%

Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy

Feng,

Sørensen

2024

J. Phys.: Conf. Ser.

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To enable easier uptake and flexible usage for the wind energy community, a general tool chain integration platform for multi-disciplinary analysis and optimization, TopDesign, is proposed and developed. This work describes its concept and the initial implementation. The platform is written in Python and provided as an open source framework. The design of this platform puts emphasis on flexibility, usability and extensibility. General model classes with standard interfaces, which can wrap custom tools/models in different formats based on different programming languages, will be provided together with examples that are easy to understand and modify. Coupling tools/models into a system thus becomes an easy task of connecting models by inputs and outputs and defining workflow with a directed graph. To demonstrate the usage of the proposed platform, we implement a wind farm evaluation system by coupling the PyWake model, the FLORIS model and self-written constraint models in the platform and apply it in solving wind farm layout optimization problems with two algorithms, as implemented in an in-house optimization Python library. A case study for a wind farm composed of 9 turbines shows the potential of the proposed platform and methodology.

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Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.16 Theory Manual

Cited by 11 publications

References 0 publications

Comparison Between Pin-by-Pin Subchannel and System Level Thermal Hydraulic Results for High Burnup Loss-of-Coolant Applications

Comparison Between Pin-by-Pin Subchannel and System Level Thermal Hydraulic Results for High Burnup Loss-of-Coolant Applications

Development of Integrated Thermal Fluids Modeling Capability for MSRs

Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy

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