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At least 1,477 records · Page 82

Alternative Method for Performing As-Built, As-Irradiated Neutronics Analyses

Neutronics analyses have been used to assist in the design, development, and qualification of miniature fuel (MiniFuel) experiments irradiated in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) since their conception almost a decade ago. In recent years, upon completion of a MiniFuel target’s irradiation, neutronics analyses that reflect the as-built, as-irradiated conditions of an experiment have also been performed to validate postirradiation examination (PIE) efforts. Several radiation transport and depletion/activation software wrapper programs have been developed to increase the fidelity of these calculations; at ORNL, a program called HFIRCON is the primary software method employed. However, the utilization of these wrapper programs comes at a cost. To produce accurate results, the radiation transport portion of these analyses requires significant time and resources to execute. Therefore, this report discusses an alternative methodology for calculating some of the desired output for PIE validation—specifically, the output used in evaluating the experiment’s fuel burnup—without complete reliance on ORNL’s wrapper program. The alternative method is not a new software but rather a procedure for utilizing the depletion/activation software, SCALE, in conjunction with limited input data and reasonable assumptions to bypass most of the radiation transport calculations and thereby reduce the time required for the completion of a standard analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development and formulation of physics based metallic fuel models and comparison to integral irradiation data

Metallic fuel has an important historical significance in the development of nuclear reactors and continues to be relevant to the progression of advanced test and power reactors. A number of models, ranging from empirical to mechanistic, have been developed and implemented in various fuel performance codes to describe U-Zr and U-Pu-Zr fuel and typical fast reactor cladding materials. One challenge of using these models to simulate fuel performance is the inevitable tangling of coupled phenomena that can cloud proper implementation, calibration, and eventual utilization of new models. Here in an effort to provide a baseline capability that will facilitate the use of advanced models, new capabilities have been implemented into the fuel performance code BISON specific to metallic fuel simulations, ranging from materials properties, fission gas release and swelling calculations, coolant channel models, and cladding correlations. These models have been applied to the X441/X441A EBR-II experimental assembly data, a set of irradiated metallic UPuZr fuel rods of varying pin designs. The models implemented in BISON are able to capture the general trend of the expected response of the fuel and cladding to irradiation in EBR-II, especially when considering the spread in experimental measurements and the uncertainties inherited from the historical material models. Ultimately, the models outlined here provide the baseline capabilities on which new models can build upon in order to improve the prediction of metallic fuel performance simulations in off-normal designs or operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigating Fission Reaction Rate Ratio Sensitivities [Abstract]

Reaction rate ratios are a measurable parameter for reactor and criticality applications. A number of foil irradiations and fission chamber measurements have been performed for critical assemblies at Los Alamos National Laboratory starting in the 1950’s including (i) Godiva, a bare HEU spherical assembly; (ii) Flattop-25, a spherical assembly consisting of an HEU core and a natural uranium reflector; (iii) Jezebel, a bare 239 Pu assembly; and (iv) Flattop-Pu, a spherical assembly consisting of a 239Pu core and a natural uranium reflector. Fission ratio data for 238 U(n,f)/ 235 U(n,f), 237 Np(n,f)/ 235 U(n,f), 233 U(n,f)/ 235 U(n,f) and 239 Pu(n,f)/ 235 U(n,f) were obtained and reported. The EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) project at Los Alamos National Laboratory (LANL) aims to constrain nuclear data by using a suite of measurement types beyond k-effective. Recent investigations include the use of pulsed spheres for nuclear data validation and other measurement methods of interest. One focus of the work is to determine if other methods are complimentary to the critical experiments utilized for nuclear data validation. It is anticipated the investigations will help inform methods that may be utilized in machine learning algorithms for nuclear validation. In order to use a measurement type for nuclear validation, it is necessary to obtain cross-section sensitivities for parameters. This work looks at reaction rate ratio sensitivities with SENSMG and Monte Carlo N-Particle R Code Version 6.21.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

“Virtual IED sensor” at an rf-biased electrode in low-pressure plasma

Energy distribution and the flux of the ions coming on a surface are considered as the key-parameters in anisotropic plasma etching. Since direct ion energy distribution (IED) measurements at the treated surface during plasma processing are often hardly possible, there is an opportunity for virtual ones. This work is devoted to the possibility of such indirect IED and ion flux measurements at an rf-biased electrode in low-pressure rf plasma by using a “virtual IED sensor” which represents “in-situ” IED calculations on the absolute scale in accordance with a plasma sheath model containing a set of measurable external parameters. The “virtual IED sensor” should also involve some external calibration procedure. Applicability and accuracy of the “virtual IED sensor” are validated for a dual-frequency reactive ion etching (RIE) inductively coupled plasma (ICP) reactor with a capacitively coupled rf-biased electrode. The validation is carried out for heavy (Ar) and light (H{sub 2}) gases under different discharge conditions (different ICP powers, rf-bias frequencies, and voltages). An EQP mass-spectrometer and an rf-compensated Langmuir probe (LP) are used to characterize plasma, while an rf-compensated retarded field energy analyzer (RFEA) is applied to measure IED and ion flux at the rf-biased electrode. Besides, the pulsed selfbias method is used as an external calibration procedure for ion flux estimating at the rf-biased electrode. It is shown that pulsed selfbias method allows calibrating the IED absolute scale quite accurately. It is also shown that the “virtual IED sensor” based on the simplest collisionless sheath model allows reproducing well enough the experimental IEDs at the pressures when the sheath thickness s is less than the ion mean free path λ{sub i} (s < λ{sub i}). At higher pressure (when s > λ{sub i}), the difference between calculated and experimental IEDs due to ion collisions in the sheath is observed in the low energy range. The effect of electron impact ionization in the sheath on the origin and intensity of low-energy peaks in IED is discussed compared to ion charge-exchange collisions. Obviously, the extrapolation of the “virtual IED sensor” approach to higher pressures requires developing some other sheath models, taking into account both ion and electron collisions and probably including even a model of the whole plasma volume instead of plasma sheath one.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measurements of multiple heat flux components at the divertor target by using surface eroding thermocouples (invited)

The Surface Eroding Thermocouple (SETC) is a robust diagnostic utilized in DIII-D to provide fast, edge-localized modes (ELMs) resolved heat flux measurements, in particular in geometric regions that are too shadowed for traditional infrared thermography. In order to further investigate the power dissipation in the divertor region, a combination of flush-mounted and recessed SETCs was developed to assess the effect on surface heating from non-charged particles at the divertor target. Utilizing the Divertor Materials Evaluation System sample exposure platform, the first demonstration of the feasibility of using this new method to distinguish between the heat flux from charged particles and that from neutrals and radiative heating was achieved. This paper details the process of using the combination of flush SETCs and recessed SETCs to measure the multiple heat flux components at the divertor target and further discusses how to determine two important ratios, α (ratio of heat flux from charged particles deposit on recessed SETC to that deposit on flush SETC) and β (ratio of heat flux from non-charged particles deposit on recessed SETC to that deposit on flush SETC), in the estimation of the heat flux from non-charged particle sources. Using a time dependent ratio α, it was found that ~50% of the total incident heat flux is attributable to the non-charged particles in the fully detached open divertor in DIII-D. Finally, the new application of similar SETC diagnostics in the Small Angle Slot divertor with a V-like configuration and partial tungsten coated surface (SAS-VW) is also introduced.

47 OTHER INSTRUMENTATION↗

Characterization of the liquid Li-solid Mo (1 1 0) interface from classical molecular dynamics for plasma-facing applications

An understanding of the wetting properties and a characterization of theinterface between liquid lithium (Li) and solid molybdenum (Mo) are relevant to assessing the efficacy of Li as a plasma-facing component in fusion reactors. Here, a new second-nearest neighbor modified embedded-atom method (2NN MEAM) force eld is parameterized to describe the interactions between Li and Mo. The new force eld reproduces several benchmark properties obtained from first-principles quantum mechanics simulations, including binding curves for Li at three different adsorption sites and the corresponding forces on Li atoms adsorbed on the Mo (110) surface. This force field is then used to study the wetting of liquid Li on the (110) surface of Mo and to examine the Li-Mo interface using molecular dynamics simulations. From droplet simulations, we nd that liquid Li tends to completely wet the perfect Mo (110) surface, in contradiction with previous experimental measurements that found non-zero contact angles for liquid Li on a Mo substrate. However, these experiments were not carried out under ultra-high vacuum conditions or with a perfect (110) Mo surface, suggesting that the presence of impurities, such as oxygen, and surface structure play a crucial role in this wetting process. From thin- lm simulations, it is observed that the first layer of Li on the Mo (110) surface has many solid-like properties such as a low mobility and a larger degree of ordering when compared to layers further away from the surface, even at temperatures well above the bulk melting temperature of Li. Our findings are consistent with temperature-programmed desorption experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nuclear fuel irradiation testbed for nuclear security applications

The nuclear security community has long been interested in the identification and quantification of nuclear material signatures to understand a material’s provenance, use, and ultimate application. New forensics signatures and methods intended for non-traditional or advanced nuclear fuel applications require fuel irradiation experiments to demonstrate viability and validity. Integral fuel irradiations have historically required significant costs and long timelines to design, irradiate, and characterize. This paper describes how a recently developed nuclear fuel irradiation testbed can be used to provide a low cost, rapid turnaround, modular test environment for irradiation and evaluation of nuclear fuel specimens for nuclear security applications. The irradiation testbed houses six small ‘MiniFuel’ samples within hermetically sealed capsules inside targets that can be removed in between each ∼25-day operating cycle of the High Flux Isotope Reactor (HFIR). As many as nine targets can be irradiated using a single irradiation position (reflector region) in HFIR, allowing for varying irradiation temperatures and burnups. A suite of hot cell capabilities have been established to perform post-irradiation examination for measuring performance (e.g., fuel swelling, fission gas release) and facilitating experiment disassembly for subsequent property measurements, microstructural analysis, or chemical assay. This new testbed allows fuel irradiations to be conducted on an accelerated timeframe to enable rapid proof of concept testing and to provide reference material for nuclear fuel security applications. Recent applications using this testbed include the testing of isotopic taggants in UO 2 fuel (intentional forensics), testing of U-10Mo fuel for down-conversion of highly enriched uranium–fueled reactors, and the production of irradiated UO 2 fuel material for signature analysis of its isotopic composition (plutonium, fission gases, etc.).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Thermal conductivity modeling of monodispersed microspheres using discrete element method

Particle beds are widely used in various systems and processes, such as particle heat exchangers, granular flow reactors, and additive manufacturing. Accurate modeling of the thermal conductivity of particle beds and understanding of their heat transfer mechanisms are important. However, previous models were based on simple cubic packing of particles, which could not accurately represent the actual heat transfer processes under certain conditions. Here, we examine the effect of the packing structure on the thermal conductivity of particle beds. We use monodispersed silica microspheres with average particle sizes ranging from 23 to 330 μm as a model material. We employ a transient hot-wire technique to measure the thermal conductivity of the particle beds with packing density of 43%–57% within a temperature range of room temperature to 500 °C and under N2 gaseous pressures of 20–760 Torr. We then use a discrete element method (DEM) to obtain the realistic packing structure of the particles, which is then fed into a finite-element model (FEM) to calculate the thermal conductivity, with the consideration of solid conduction, gas conduction, and radiation heat transfer. Our results show that the thermal conductivity model based on the more realistic random packing structure derived from the DEM shows better agreement with the experimental data compared to that based on the simple cubic-packing structure. The combined DEM and FEM methodology can serve as a useful tool to predict the effective thermal conductivity of particle beds and to quantify different heat transfer mechanisms under various conditions.

14 SOLAR ENERGY↗

Integrated Energy System Investigation for the Eastman Chemical Company, Kingsport, Tennessee Facility

The industrial manufacturing industry is looking to implement new methods of energy production to ensure a consistent energy supply while reducing economic costs and environmental impacts. Much of the manufacturing industry relies on fossil fuels—primarily coal and natural gas—of which there are finite resources subject to price volatility due to an inelastic demand. These resources also come with significant negative environmental impacts related to emissions. While complete independence from fossil fuels is not immediately realistic, options are available to significantly reduce dependency on fossil fuel supplies, including integrated energy systems (IESs) which tightly couple nuclear energy source generators with energy consumers (i.e., industrial factories) to fulfill power and energy requirements. Once realized, optimized IESs may yield significant economic and environmental benefits over traditionally isolated generator and consumer facilities. This report presents a feasibility study for siting an IES to meet the steam and electricity needs of Eastman Chemical Company’s facility in Kingsport, Tennessee. This study explored reactor technology options, evaluation, and optimization, with a focus on meeting the facility’s operational and reliability requirements. This work is part of an ongoing effort by Eastman to be good environmental stewards and meet the demands of their customers by shifting to more environmentally sustainable solutions for their energy needs. Outcomes of this report are also of general interest and value to any design or development team seeking to deploy an IES, as many topics described herein are generally applicable to any nuclear power facility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

One-Step Synthesis of Zeolite Membranes Containing Catalytic Metal Nanoclusters

Metal-loaded zeolitic membranes are promising candidates as catalytic membrane reactors. We report a one-step synthesis method to synthesize zeolite membranes containing metal nanoclusters, that has advantages in comparison to multistep methods such as impregnation and ion exchange. Pure-silica MFI zeolite-Pt hybrid membranes were prepared by hydrothermal synthesis with addition of 3-mercaptopropyl-trimethoxysilane (MPS) and a platinum precursor. Composition analysis and mapping by energy-dispersive X-ray spectroscopy (EDX) reveal that Pt ions/clusters are uniformly distributed along the membrane cross-section. High-magnification scanning transmission electron microscopy (STEM) analysis shows that Pt metal clusters in the hybrid zeolite membrane have a diameter distribution in the range of 0.5–2.0 nm. In contrast, a pure-silica MFI membrane synthesized from an MPS-free solution shows negligible incorporation of Pt metal clusters. To characterize the properties of the hybrid (zeolite/metal) membrane, it was used as a catalytic membrane reactor (CMR) for high-temperature propane dehydrogenation (PDH) at 600 °C and 1 atm. The results indicate that Pt metal clusters formed within the MFI zeolite membrane can serve as effective catalysts for high-temperature PDH reaction along with H 2 removal via membrane permeation, thereby increasing both conversion and selectivity in relation to a conventional membrane reactor containing an equivalent amount of packed Pt catalyst in contact with an MFI membrane. In conclusion, the hybrid zeolite-Pt CMR also showed stable conversion and selectivity upon extended high-temperature operation (12 h), indicating that encapsulation in the zeolite allowed thermal stabilization of the Pt nanoclusters and reduced catalyst deactivation.

36 MATERIALS SCIENCE↗

Human factors and modeling methods in the development of control room modernization concepts - 315

Control room modernization is one of the most challenging and complex upgrade projects that a nuclear power plant can undertake. It can even have a bigger impact on operations than, for example, turbine replacement. The challenges of migrating an analog control system to a distributed control system are already well known and a number of nuclear utilities have embarked upon various levels of effort to upgrade some of the systems in the control room. When planning for control room upgrades, plants have to deal with a multitude of engineering and operational impacts. This will inevitably include several human factors considerations, including physical ergonomics of workstations, viewing angles, lighting, seating, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the Idaho National Laboratory (INL) has developed human factors design and evaluation methods to be used in the development of an end-state control room concept and to manage the various phases of the upgrade life cycle. This included interactive sessions with operators in INL's Human System Simulation Laboratory, and three-dimensional modeling to visualize control board changes. To make the various upgrade phases as concrete and as visible as possible, the end-state concept includes a set of visual representations of the control room before and after various upgrade phases to provide the context and a framework within which to consider the various options in the upgrade. This includes the various control systems, human-system interfaces to be replaced, and possible changes to operator workstations. This paper describes how this framework helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and also provide substantial improvement in operator performance. The paper further describes the application of this integrated approach in the strategic modernization program at a nuclear power plant where legacy systems are upgraded to advanced digital technologies through a systematic process that links human factors principles to the systems engineering process. This approach results in an integrated control room architecture beyond what is possible for individual subsystem upgrades alone. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Error analysis of a hybrid control drum worth model

This paper presents a perturbation-based model for control drum worth prediction which employs both physics-based and statistics-based components. Control drums, or control shims, are cylindrical in shape and span the axial length of the core. A portion of the cylinder is coated in neutron absorbing material and the drum can rotate to introduce the absorbing material to the body of the core to reduce reactivity. The model can be expensive to create due to the requirement for full-core Monte Carlo eigenvalue calculations. Therefore, it is important to analyze how the errors in Monte Carlo calculated k{sub eff} used for model training affect model performance. It was found that the error in predicted criticalities could average to 70 pcm in the most complex form of the model and 215 pcm in the simplest form of the model. Furthermore, it was found that the Monte Carlo uncertainty in quantities calculated with Serpent used to train the models had minimal impact on the error observed from the model. Lastly, one of the forms of the hybrid model could be trained in considerably less computational time if the Monte Carlo calculations were run to higher uncertainty in k{sub eff} with a small penalty to model performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Extended-MHD simulations of disruption mitigation via massive gas injection in SPARC

Recent developments to the M3D-C1 code enable higher fidelity modeling of disruptions, and can be applied in the design verification of reactor-scale tokamaks. Among these new capabilities is a method to mesh conducting vessel structures such as coils and passive plates, packing of the toroidal mesh around gas injectors, as well as anisotropic resistivity inside the vessel structures. We present extended-magnetohydrodynamic (MHD) simulations of disruption mitigation via massive gas injection (MGI) in SPARC. The goal of this study is to inform the disruption mitigation layout of SPARC and aid in the design of an effective gas injector configuration. Fully three-dimensional simulations with M3D-C1 are carried out for various injector configurations with the primary goal of determining the effect of different MGI parameters on heat loads and vessel forces. The simulations include a model for impurity ionization, recombination, advection and radiation, as well as spatially resolved conducting structures around the plasma. A localized mixture of deuterium and neon with a small toroidal and poloidal width is injected in up to six locations. We demonstrate that M3D-C1 can model a rapid shutdown via MGI using narrow and more realistic gas plumes than in previous simulations. As a result of the q = 1 surface in the SPARC baseline case a sawtooth is observed early in the simulations. Despite the sawtooth and the onset of edge MHD instabilities, the impurity distribution remains localized around the injector locations, but enables a radiative shutdown of the plasma. We find that using the maximum of six gas injectors results in a lower peaking factor and leads to a more even distribution of radiation toroidally than using two injectors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Kriging-Based Inverse Uncertainty Quantification of BISON Fission Gas Release Model

Nuclear reactor fuel performance analysis studies the thermo-mechanical behavior of fuel rods and verify their compliance with safety criteria under both normal operation and accidental conditions. One of the major concerns in fuel performance analysis is the behavior of the fission gases xenon and krypton in uranium dioxide fuel, which significantly affect the thermo-mechanical performance of the nuclear fuel rods employed in current LWRs. Previously, the modeling of fission gas release (FGR) in nuclear fuel performance codes have been relying on empirical models which are not applicable beyond their range of calibration. Recently a more efficient and flexible physics-based FGR and swelling model that can describe a wider range of reactor operation conditions have been implemented in fuel performance code BISON. In this work, we performed Bayesian calibration to inversely quantify the uncertainties associated with the 5 tuning parameters in BISON FGR model, based on the time-dependent FGR measurement data from Riso-AN3 benchmark. It takes around 1 hour and 40 minutes for BISON to simulate the Riso-AN3 benchmark with a moderate mesh size using 32 processors. As hundreds of thousands of BISON simulations are needed during Markov Chain Monte Carlo (MCMC) sampling, running BISON directly is not a viable solution. Therefore we propose to use Kriging-based metamodels to replace BISON during MCMC sampling. Surrogate model is an approximation of the input/output relation of a computer code/model. It is also called metamodel, response surface, emulator. Surrogate models usually take much less computational time than the original model (like BISON) while maintaining the input/output relation of the original model to a desirable accuracy. Constructing the metamodels normally requires small number of executions of the original model. Once validated, metamodels can be used to perform uncertainty and sensitivity analysis, Bayesian calibration, optimization, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Flow field characteristics of a 127-pin rod bundle with hexagonal spacer grids

A determination of nominal flow phenomena in liquid metal fast reactor (LMFR) fuel assemblies is critical toward generation-IV reactor development. Axially positioned spacer grids are used to maintain the geometry of hexagonal rod bundles and simultaneously introduce perturbations in the flow. Three-dimensional (3D) printed asymmetric honeycomb spacer grids were installed in a prototypical 127-pin LMFR fuel assembly model to study complex fluid dynamics interactions induced by the spacer grid and rods. To characterize flow dynamics in this intricate geometry, time-resolved particle image velocimetry (TR-PIV) using the matched-index-of-refraction method was employed to obtain non-intrusive velocity measurements for three axial planes (one near-wall and two interior planes) at a Reynolds number of 6000. The statistical TR-PIV results compared sub-channel-dependent normalized time-averaged velocity, velocity fluctuations, Reynolds stress, vorticity, and turbulence kinetic energy distributions. TR-PIV line profiles characterized downstream spacer grid flow dynamics. Two-point spatial and spatial–temporal cross-correlation fields revealed local coherent structures and quantified convection velocities of traveling vortices. Spatial–temporal decomposition using dynamic mode decomposition (DMD) applied to the near-wall vorticity fields extracted turbulent structures and flow instabilities in the wake region of the spacer grid, along with their decay and frequency rates. Reduced-order velocity fields from DMD reconstructions identified the most energy-containing coherent structures persistent in the near-wall region. This research provides experimental data sets and analyses of flow behavior in rod bundles with hexagonal spacer grids. In conclusion, the results are critical toward LMFR design and geometry optimization, crucial for the validation of computational fluid dynamics and reduced-order flow models.

42 ENGINEERING↗

The 2019 Edition of the ICSBEP Handbook

Over the past several decades, innumerable experiments have been performed worldwide to support criticality safety. These experiments represent significant investment in infrastructure, expertise, and cost, and are valuable resources of data for present and future research. These valuable assets provide the basis for recording, development, and validation of methods and nuclear data [1]. If the experimental data are lost, the high cost to repeat many of these measurements would likely be prohibitive. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) was established to: 1. Identify a comprehensive set of critical benchmark data and, to the extent possible, verify the data; 2. Evaluate the data and quantify overall uncertainties through various types of sensitivity analyses; 3. Compile the data into a standardized format; 4. Perform calculations of each experiment with standard criticality safety codes; and 5. Formally document the work into a single source of verified benchmark critical data. Annually, contributors from around the world continue to collaborate in the evaluation and review of select benchmark experiments for inclusion in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) [2]. Further information regarding the ICSBEP, including highlighted criticality safety benchmark evaluations, can be found in the September and October 2003 editions of Nuclear Science and Engineering [3]. New and recently revised evaluations have been prepared for inclusion in the 2019 edition of the ICSBEP Handbook.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Generation of Low Fidelity Experimental Covariance Matrices for ICSBEP Cases

In validation, statistical methods routinely incorporate information from integral experiments to improve estimations of code biases and uncertainties. One source of high quality integral experiments is the ICSBEP Handbook. While uncertainties for criticality benchmarks are well characterized in the Handbook, information pertaining to the shared uncertainty/covariance between the cases is sparse, yet required for the aforementioned methods; correlations can result from using the same fuel for example. To remedy the lack of available covariance data in the Handbook, recent efforts have been undertaken, notably, within the framework of the NEA Expert Group on Uncertainty Analysis in Criticality Safety Assessment (UACSA) under the Working Party on Nuclear Criticality Safety (WPNCS) . The UACSA activities have focused primarily on comparing methods used to generate high quality covariance matrices for a small number of evaluations. Despite these efforts, within the Database for ICSBEP DICE only about 2% of the nearly 5000 experiments in the ICSBEP Handbook have correlation coefficients, so the amount of work required to generate the missing data appears daunting. And so, to fill in the gaps where no correlations are available, it is proposed to generate low fidelity correlations by isolating the largest components of uncertainty and determining the fraction shared between cases within an evaluation. Uncertainties can be shared when they are not independently measured, or the source of uncertainty is unchanged between cases. The degree to which an uncertainty is shared is linked to the experimental procedure; an approximation is made that in the absence of additional information, similar experimental procedures will lead to a similar fraction of shared uncertainty. Between experimental procedures there is some commonality. One method, proposed here, to help elucidate similar procedures is to encode each procedure into a decision tree grouped by uncertainty type. End nodes of the tree require judgment to assign the fraction of shared uncertainty between cases associated with the node. This can also be thought of as a set of rules, such that if experimental procedures and conditions occurred, then assign the shared uncertainty as some number between 0.0 and 1.0. One advantage of such a procedure is the formation of a transparent logical link between the judgment applied and the amount of shared uncertainty. This makes the results both more reproducible and easy to update. Generating correlation coefficients is reduced to developing decision trees that categorize how the experiments were done, and apply judgment of the degree of shared uncertainty for the end node of the tree. Trees need to be constructed after reading section 1 and 2 of the evaluation and some evaluations certainly do not contain enough information to create informative decision trees nor to assign an amount of shared uncertainty. These evaluations will not be considered here. (authors)

42 ENGINEERING↗