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Ivanov, Kostadin

Publications and source records attributed to Ivanov, Kostadin.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fuel performance uncertainty quantification and sensitivity analysis in the presence of epistemic and aleatoric sources of uncertainties

Fuel performance modeling and simulation includes many uncertain parameters from models to boundary conditions, manufacturing parameters and material properties. These parameters exhibit large uncertainties and can have an epistemic or aleatoric nature, something that renders fuel performance code-to-code and code-to-measurements comparisons for complex phenomena such as the pellet cladding mechanical interaction (PCMI) very challenging. Additionally, PCMI and other complex phenomena found in fuel performance modeling and simulation induce strong discontinuities and non-linearities that can render difficult to extract meaningful conclusions form uncertainty quantification (UQ) and sensitivity analysis (SA) studies. In this work, we develop and apply a consistent treatment of epistemic and aleatoric uncertainties for both UQ and SA in fuel performance calculations and use historical benchmark-quality measurement data to demonstrate it. More specifically, the developed methodology is applied to the OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation benchmark. A cold ramp test leading to PCMI is modeled. Two measured quantities of interest are considered: the cladding axial elongation during the irradiations and the cladding outer diameter after the cold ramp. The fuel performance code used to perform the simulation is FAST. The developed methodology involves various steps including a Morris screening to decrease the number of uncertain inputs, a nested loop approach for propagating the epistemic and aleatoric sources of uncertainties, and a global SA using Sobol indices. The obtained results indicate that the fuel and cladding thermal conductivities as well as the cladding outer diameter uncertainties are the three inputs having the largest impact on the measured quantities. More importantly, it was found that the epistemic uncertainties can have a significant impact on the measured quantities and can affect the outcome of the global sensitivity analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Preservation of kinetics parameters generated by Monte Carlo calculations in two-step deterministic calculations

The generation of accurate kinetic parameters such as mean generation time Λ and effective delayed neutron fraction β eff via Monte Carlo codes is established. Employing these in downstream deterministic codes warrants another step to ensure no additional error is introduced by the low-order transport operator when computing forward and adjoint fluxes for bilinear weighting of these parameters. Another complexity stems from applying superhomogenization (SPH) equivalence in non-fundamental mode approximations, where reference and low-order calculations rely on a 3D full core model. In these cases, SPH factors can optionally be computed for only part of the geometry while preserving reaction rates and K-effective, but the impact of such approximations on kinetics parameters has not been thoroughly studied. This paper aims at studying the preservation of bilinearly-weighted quantities in the Serpent–Griffin calculation procedure. Diffusion and transport evaluations of IPEN/MB-01, Godiva, and Flattop were carried out with the Griffin reactor physics code, testing available modeling options using Serpent-generated multigroup cross sections and equivalence data. Verifying Griffin against Serpent indicates sensitivities to multigroup energy grid selection and regional application of SPH equivalence, introducing significant errors; these were demonstrated to be reduced through the use of a transport method together with a finer energy grid.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

IAEA CRP on HTGR UAM: Propagation of Phase I cross section uncertainties to Phase II neutronics steady state using SCALE/SAMPLER and PHISICS/RELAP5-3D

The IAEA Coordinated Research Project (CRP) on High Temperature Gas Cooled Reactor (HTGR) Uncertainties in Modeling (UAM) has been actively supported by the HTGR Methods group at Idaho National Laboratory since 2013. The INL team is responsible for the development of the prismatic reactor design exercises, based on the 350 MW General Atomics Modular HTGR (MHTGR). The focus of this paper is the reporting of the INL results obtained for the propagation of the lattice cross section uncertainties to the stand-alone neutronics simulation of the full MHTGR-350 core. For the nominal (i.e. best-estimate) model, a series of fresh and depleted single block and super cell SCALE/KENO and SCALE/NEWT models were developed at INL to assess spectral effects in the MHTGR-350, and a combination of these lattice cells were used to construct 8-group cross section libraries for use in the INL-developed PHISICS/RELAP5-3D code suite. The block-level homogenized libraries were assigned to the 220 fuel zones utilized in the MHTGR-350 PHISICS core model, according to the fresh and mixed fresh/depleted core loading pattern. A set of 1,000 perturbed NEWT lattice and PHISICS/RELAP5-3D core calculations were performed using the stochastic sampling module SAMPLER in SCALE 6.2. The paper discusses the mean and standard deviation values obtained for the eigenvalue, power offset and peak axial power density uncertainty results for this sequence of 1,000 lattice-to-core MHTGR-350 simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Three-dimensional fuel pin model validation by prediction of hydrogen distribution in cladding and comparison with experiment

To correctly describe and predict this hydrogen distribution there is a need for multi-physics coupling to provide accurate three-dimensional azimuthal, radial, and axial temperature distributions in the cladding. Coupled high-fidelity reactor-physics codes with a sub-channel code as well as with a computational fluid dynamics (CFD) tool have been used to calculate detailed temperature distributions. These high-fidelity coupled neutronics/thermal-hydraulics code systems are coupled further with the fuel-performance BISON code with a kernel (module) for hydrogen. Both hydrogen migration and precipitation/dissolution are included in the model. Results from this multi-physics analysis is validated utilizing calculations of hydrogen distribution using models informed by data from hydrogen experiments and PIE data.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The IAEA coordinated research programme on HTGR uncertainty analysis: Phase I status and Ex. I-1 prismatic reference results

The quantification of uncertainties in design and safety analysis of reactors is today not only broadly accepted, but in many cases became the preferred way to replace traditional conservative analysis for safety and licensing analysis. The use of a more fundamental methodology is also consistent with the reliable high fidelity physics models and robust, efficient, and accurate codes available today. To facilitate uncertainty analysis applications a comprehensive approach and methodology must be developed and applied, in contrast to the historical approach where sensitivity analysis were performed and uncertainties then determined by a simplified statistical combination of a few important input parameters. New methodologies are currently under development in the OECD/NEA Light Water Reactor (LWR) Uncertainty Analysis in Best-Estimate Modelling (UAM) benchmark activity. High Temperature Gas-cooled Reactor (HTGR) designs require specific treatment of the double heterogeneous fuel design and large graphite quantities at high temperatures. The IAEA has therefore launched a Coordinated Research Project (CRP) on HTGR Uncertainty Analysis in Modelling (UAM) in 2013 to study uncertainty propagation specifically in the HTGR analysis chain. Two benchmark problems are defined, with the prismatic design represented by the General Atomics (GA) MHTGR-350 and a 250 MW modular pebble bed design similar to the Chinese HTR-PM. Work has started on the first phase and the current CRP status is reported in the paper. A comparison of the Serpent and SCALE/KENO-VI reference Monte Carlo results for Ex. I-1 of the MHTGR-350 design is also included. It was observed that the SCALE/KENO-VI Continuous Energy (CE) k ∞ values were 395 pcm (Ex. I-1a) to 803 pcm (Ex. I-1b) higher than the respective Serpent lattice calculations, and that within the set of the SCALE results, the KENO-VI 238 Multi-Group (MG) k ∞ values were up to 800 pcm lower than the KENO-VI CE values. The use of the latest ENDF-B-VII.1 cross section library in Serpent lead to ~180 pcm lower k ∞ values compared to the older ENDF-B-VII.0 dataset, caused by the modified graphite neutron capture cross section. Furthermore, the fourth beta release of SCALE 6.2 likewise produced lower CE k∞ values when compared to SCALE 6.1, and the improved performance of the new 252-group library available in SCALE 6.2 is especially noteworthy. A SCALE/TSUNAMI uncertainty analysis of the Hot Full Power variant for Ex. I-1a furthermore concluded that the 238 U(n,γ) (capture) and 235 U(View the MathML source) cross-section covariance matrices contributed the most to the total k ∞ uncertainty of 0.58%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

ROD INTERNAL PRESSURE QUANTIFICATION AND DISTRIBUTION ANALYSIS USING FRAPCON

The discharge rod internal pressure (RIP) and cladding hoop stress (CHS) distributions are quantified forWatts BarNuclearUnit 1 (WBN1) fuel rods by modeling core cycle design data, intercycle assembly movements, operation data (including modeling significant trips and downpowers), and as-built fuel enrichments and densities of each fuel rod in FRAPCON-3.5. An alternate model for the amount of helium released from zirconium diboride (ZrB2) integral fuel burnable absorber (IFBA) layers is derived and applied to FRAPCON output data to quantify the RIP and CHS for these fuel rods. SCALE/Polaris is used to quantify fuel rod-specific spectral quantities and the amount of gaseous fission products produced in the fuel for use in FRAPCON inputs. Fuel rods with ZrB2 IFBA layers (i.e., IFBA rods) are determined to have RIP predictions that are elevated when compared to fuel rod without IFBA layers (i.e., standard rods) despite the fact that IFBA rods often have reduced fill pressures and annular fuel blankets. Cumulative distribution functions (CDFs) are prepared from the distribution of RIP predictions for all standard and IFBA rods. The provided CDFs allow for the determination of the portion of WBN1 fuel rods that exceed a specified RIP limit. Lastly, improvements to the computational methodology of FRAPCON are proposed.

cladding hoop stress↗
DOE OSTI2014

Anisotropic Azimuthal Power and Temperature distribution on FuelRod: Impact on Hydride Distribution

The degradation of the zirconium cladding may limit nuclear fuel performance. In the high temperature environment of a reactor, the zirconium in the cladding corrodes, releasing hydrogen in the process. Some of this hydrogen is absorbed by the cladding in a highly inhomogeneous manner. The distribution of the absorbed hydrogen is extremely sensitive to temperature and stress concentration gradients. The absorbed hydrogen tends to concentrate near lower temperatures. This hydrogen absorption and hydride formation can cause cladding failure. This project set out to improve the hydrogen distribution prediction capabilities of the BISON fuel performance code. The project was split into two primary sections, first was the use of a high fidelity multi-physics coupling to accurately predict temperature gradients as a function of r, θ , and z, and the second was to use experimental data to create an analytical hydrogen precipitation model. The Penn State version of thermal hydraulics code COBRA-TF (CTF) was successfully coupled to the DeCART neutronics code. This coupled system was verified by testing and validated by comparison to FRAPCON data. The hydrogen diffusion and precipitation experiments successfully calculated the heat of transport and precipitation rate constant values to be used within the hydrogen model in BISON. These values can only be determined experimentally. These values were successfully implemented in precipitation, diffusion and dissolution kernels that were implemented in the BISON code. The coupled output was fed into BISON models and the hydrogen and hydride distributions behaved as expected. Simulations were conducted in the radial, axial and azimuthal directions to showcase the full capabilities of the hydrogen model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

The IAEA Coordinated Research Program on HTGR Uncertainty Analysis: Phase I Status and Initial Results

The continued development of High Temperature Gas Cooled Reactors (HTGRs) requires verification of HTGR design and safety features with reliable high fidelity physics models and robust, efficient, and accurate codes. One way to address the uncertainties in the HTGR analysis tools is to assess the sensitivity of critical parameters (such as the calculated maximum fuel temperature during loss of coolant accidents) to a few important input uncertainties. The input parameters were identified by engineering judgement in the past but are today typically based on a Phenomena Identification Ranking Table (PIRT) process. The input parameters can also be derived from sensitivity studies and are then varied in the analysis to find a spread in the parameter of importance. However, there is often no easy way to compensate for these uncertainties. In engineering system design, a common approach for addressing performance uncertainties is to add compensating margins to the system, but with passive properties credited it is not so clear how to apply it in the case of modular HTGR heat removal path. Other more sophisticated uncertainty modelling approaches, including Monte Carlo analysis, have also been proposed and applied. Ideally one wishes to apply a more fundamental approach to determine the predictive capability and accuracies of coupled neutronics/thermal-hydraulics and depletion simulations used for reactor design and safety assessment. Today there is a broader acceptance of the use of uncertainty analysis even in safety studies, and it has been accepted by regulators in some cases to replace the traditional conservative analysis. Therefore some safety analysis calculations may use a mixture of these approaches for different parameters depending upon the particular requirements of the analysis problem involved. Sensitivity analysis can for example be used to provide information as part of an uncertainty analysis to determine best estimate plus uncertainty results to the required confidence level. In order to address uncertainty propagation in analysis and methods in the HTGR community the IAEA initiated a Coordinated Research Project (CRP) on the HTGR Uncertainty Analysis in Modelling (UAM) that officially started in 2013. Although this project focuses specifically on the peculiarities of HTGR designs and its simulation requirements, many lessons can be learned from the LWR community and the significant progress already made towards a consistent methodology uncertainty analysis. In the case of LWRs the NRC has already in 1988 amended 10 CFR 50.46 to allow best-estimate (plus uncertainties) calculations of emergency core cooling system performance. The Nuclear Energy Agency (NEA) of the Organization for Economic Co-operation and Development (OECD) also established an Expert Group on "Uncertainty Analysis in Modelling" which finally led to the definition of the "Benchmark for Uncertainty Analysis in Modelling (UAM) for Design, Operation and Safety Analysis of LWRs". The CRP on HTGR UAM will follow as far as possible the on-going OECD Light Water Reactor UAM benchmark activity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Cobra-TF Parameter Exposure Work

The purpose of this work is to provide improved VUQ capability for CTF. We will initially focus on uncertainty quantification, but we will keep the larger scope of SQA, verification, validation, calibration, and optimization in mind while we work on uncertainty quantification. This is a living document that will be amended as the work is completed. Note that any reference to the CTF software is based on the code version of 12/17/13.

97 MATHEMATICS AND COMPUTING↗