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At least 1,045 records · Page 58

Motivation for Using Generalized Geometry in the Time Dependent Transport Code TDKENO

We are proposing to use the code, TDKENO, to model TREAT. TDKENO solves the time dependent, three dimensional Boltzmann transport equation with explicit representation of delayed neutrons. Instead of directly integrating this equation, the neutron flux is factored into two components – a rapidly varying amplitude equation and a slowly varying shape equation and each is solved separately on different time scales. The shape equation is solved using the 3D Monte Carlo transport code KENO, from Oak Ridge National Laboratory’s SCALE code package. Using the Monte Carlo method to solve the shape equation is still computationally intensive, but the operation is only performed when needed. The amplitude equation is solved deterministically and frequently, so the solution gives an accurate time-dependent solution without having to repeatedly We have modified TDKENO to incorporate KENO-VI so that we may accurately represent the geometries within TREAT. This paper explains the motivation behind using generalized geometry, and provides the results of our modifications. TDKENO uses the Improved Quasi-Static method to accomplish this. In this method, the neutron flux is factored into two components. One component is a purely time-dependent and rapidly varying amplitude function, which is solved deterministically and very frequently (small time steps). The other is a slowly varying flux shape function that weakly depends on time and is only solved when needed (significantly larger time steps).

IQS↗

Investigation of Heterogeneity Effects on Calculated Sensitivities of the ZPPR-15B Assemblies

In past years, sensitivity studies of ZPR and ZPPR assemblies were carried out with deterministic codes for several purposes, such as uncertainty estimation of calculated parameter values, cross section adjustment, representativity analysis. etc. However, these sensitivity studies used simplified R-Z models of ZPR/ZPPR assemblies where the multi-group cross section data was obtained from the homogenized material compositions of each reactor zone. The main reason for this simplification was the lack of a deterministic path able to compute sensitivity coefficients for complicated 3D geometries in transport theory. Also, each ZPR and ZPPR assembly consists of several different drawers each containing different plate types and plate arrangements and it was felt that performing sensitivity calculations with an equivalent R-Z reactor model would capture most of the feedback while the heterogeneity effects were believed to be of second order. Recently a new code, BuildZPRModel, was developed at ANL that automatically generates the inputs for cross section processing and core calculation of heterogeneous ZPR and ZPPR assemblies for 3D transport calculations. Additionally, the PERSENT code (recently developed at ANL as well) is able to carry out sensitivity calculations in transport theory on 3D geometries. With the benefit of the newly developed codes, a sensitivity study was performed for the heterogeneous model of ZPPR-15B assemblies 96 and 102 generated by BuildZPRModel. The results were compared with the sensitivities computed with the use of fully homogenized R-Z reactor models, in order to quantify the impact of heterogeneity effects neglected in the analysis performed in past years.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluating software defined networking solutions to reduce the digital attack surface of nuclear security systems

Most nuclear security systems used today were not designed for today’s threat environment. Systems that were intended to be stand alone are now interconnected. Devices that have a single purpose are built on multi-purpose platforms and communication protocols that, while effective, have no ability to authenticate authorized versus unauthorized commands. These attributes provide an attacker significant ability to affect the system, pivot throughout the interconnected networks, and remain undetected if he/she is able to compromise a single node. Software defined networking (SDN) has been used for years by information technology (IT) cloud service providers to quickly provision or remove servers or other systems to meet changing demand. The same concept has recently been applied to operational technology (OT) systems to enable very fast failover on critical systems that have stringent and deterministic (<5ms) transmit/receive times. By carefully engineering the communication flows through a network using preplanned routes and specific pathways it is possible to achieve deterministic and extremely reliable message delivery even when components fail. This engineering approach to network design has added security benefits including securing the networking control plane, eliminating network scanning and mapping, inhibiting ARP spoofing and host masquerading, eliminating unauthorized network pivoting and enabling greater situational awareness on the network. SDN in OT environments is new but early testing in electrical power and other critical infrastructure has shown it to be a very powerful tool for building reliable networks and reducing the digital attack surface of the network. The authors tested a software defined network switch on a simple physical protection system with components commonly found in nuclear security systems and found improved mitigations to denial of service attacks, lateral movement and network reconnaissance. The paper details the tests and their results.

Cyber security, Nuclear security, software defined↗

Phase 2: Updated Geothermal Play Fairway Analysis of the Tularosa Basin, New Mexico

Play fairway analysis (PFA) methodologies, both deterministic and stochastic, are being applied for medium to low enthalpy geothermal resources in the Tularosa Basin, in south-central New Mexico. These PFA methods use datasets representative of heat, groundwater and fault-fracture related permeability to locate areas with the lowest risk of geothermal energy development. Our Phase 1 PFAs predicted several plays throughout the study area, with a range of certainty and risk, based upon legacy data. In Phase 2, new data were collected for high priority plays and integrated into the PFAs to enhance certainty and further reduce risk. Field geology, gravity surveys and alluvial fan geomorphology supplemented the understanding of geologic structure and potential permeability, while additional well sampling, geothermometry and temperature logging provided valuable information about heat in the subsurface. In order to statistically compare and contrast the layers of evidence in the Tularosa Basin with the broader Great Basin, a probabilistic Weights of Evidence analysis was conducted in parallel with the inclusive and deterministic petroleum industry logic PFA. Both methods yielded 3 similar plays, while Weights of Evidence identified 2 additional plays. A sixth play was inferred around the NASA-Aerospace Data Facility Southwest site, north-east of Las Cruces, based on a promising shallow temperature survey, geothermometers, and structural interpretations of geophysical data. Here, the White Sands Missile Range main cantonment (headquarters) play is now given high priority, along with McGregor Range, Fort Bliss, due to the discovery of relatively high geothermometer values.

15 GEOTHERMAL ENERGY↗

Evaluating Safeguards Statistical Assumptions via Stochastic Simulation

Herein, the authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 SQ, using typical IAEA inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗

Occlusion-Perturbed Deep Learning for Probabilistic Solar Forecasting via Sky Images: Preprint

Solar forecasting is shifting to the probabilistic paradigm due to the inherent uncertainty within the solar resource. Input uncertainty quantification is one of the widely used and best-performing ways to model solar uncertainty. However, compared to other sources of inputs, such as numerical weather prediction models, pure sky image-based probabilistic solar forecasting lags behind. In this research, an occlusion-perturbed convolutional neural network, named the PSolarNet, is developed. The PSolarNet provides very short-term deterministic forecasts, forecast scenarios, and probabilistic forecasts of the global horizontal irradiance from sky image sequences. Case studies based on 6 years of open-source data show that the developed PSolarNet is able to generate accurate 10-minute ahead deterministic forecasts with a 5.62% normalized root mean square error, realistic and diverse forecast scenarios with a 0.966 average correlation with the actual time series, and reliable and sharp probabilistic forecasts with a 2.77% normalized continuous ranked probability score.

Bayesian model averaging↗

Learning Stochastic Parametric Differentiable Predictive Control Policies

We present a scalable unsupervised learning-based method for obtaining explicit control policies for model predictive control problems for stochastic linear systems with additive uncertainties subject to nonlinear chance constraints. We call the proposed method stochastic parametric differentiable predictive control (SP-DPC), which extends the recently proposed deterministic DPC policy optimization algorithm. We formulate the SP-DPC as a deterministic approximation to the stochastic parametric constrained optimal control problem via independent sampling of the problem's parameters and uncertainties. This formulation allows us to directly compute the policy gradients via automatic differentiation of the problem's value function, evaluated over sampled parameters and uncertainties. In particular, the computed expectation of the problem's value function is backpropagated through the finite-time closed-loop system rollouts parametrized by a known nominal system dynamics model and neural control policy. We also provide theoretical probabilistic guarantees on closed-loop stability and chance constraints satisfaction for systems controlled by learned neural policies. We demonstrate the computational efficiency and scalability of the proposed policy optimization algorithm in three numerical examples, including systems with a large number of states or subject to nonlinear constraints.

Drgona, Jan↗

Performance of the block-Krylov energy group solvers in Jaguar

A new method of coupling the inner and outer iterations for deterministic transport problems is proposed. This method is termed the Multigroup Energy Blocking Method (MEBM) and has been implemented in the deterministic transport solver Jaguar, which is currently under development at KAPL. The method is derived for both fixed-source and eigenvalue problems. The method is then applied to a PWR pin cell model, both in fixed-source mode and eigenvalue mode. The results show that the MEBM improves the convergence of both types of problems when applied to the thermal (up-scattering) groups. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Safety design approach for external events in Japan sodium-cooled fast reactor

This paper describes a safety design approach for external events in the design study of Japan sodium-cooled fast reactor. An emphasis is introduction of a design extension external condition (DEEC). In addition to seismic design, other external events such as tsunami, strong wind, abnormal temperature, etc. were addressed in this study. From a wide variety of external events consisting of natural hazards and human-induced ones, a screening method was developed in terms of siting, consequence, frequency to select representative events. Design approaches for these events were categorized on the probabilistic, statistical and deterministic basis. External hazard conditions were considered mainly for DEECs. In the probabilistic approach, the DEECs of earthquake, tsunami and strong wind were defined as 1/10 of exceedance probability of the external design bases. The other representative DEECs were also defined based on statistical or deterministic approaches. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Uncertainty analysis on reactivity and discharged inventory for a pressurized water reactor fuel assembly due to {sup 235,238}U nuclear data uncertainties

This paper discusses the uncertainty analysis on reactivity and inventory for a typical PWR fuel element as a result of uncertainties in {sup 235,238}U nuclear data. A typical Westinghouse 3-loop fuel assembly fuelled with UO{sub 2} fuel with 4.8% enrichment has been selected. The Total Monte-Carlo method has been applied using the deterministic transport code DRAGON. This code allows the generation of the few-groups nuclear data libraries by directly using data contained in the nuclear data evaluation files. The nuclear data used in this study is from the JEFF3.1 evaluation, and the nuclear data files for {sup 238}U and {sup 235}U (randomized for the generation of the various DRAGON libraries) are taken from the nuclear data library TENDL. The total uncertainty (obtained by randomizing all {sup 238}U and {sup 235}U nuclear data in the ENDF files) on the reactor parameters has been split into different components (different nuclear reaction channels). Results show that the TMC method in combination with a deterministic transport code constitutes a powerful tool for performing uncertainty and sensitivity analysis of reactor physics parameters. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of 3D full-core ERANOS-2.2/MCNPX-2.7.0 models and neutronic analysis of the BFS-2 zero-power facility

The present paper is addressing the development and validation against experimental data of 3D full-core models of the BFS-2 zero-power fast-reactor using both the deterministic system code ERANOS-2.2 and the stochastic code MCNPX-2.7.0. The model configuration of BFS considered for analysis is the BFS-62-3A benchmark. To extend the - deterministic/stochastic - code-to-code comparison, neutronic parameters, i.e. reactivity, neutron spectrum and reaction rates, were also simulated at the cell level with the Monte Carlo code SERPENT-1.1.7 with two modern data libraries, ENDF-B/VII and JEFF-3.1.1. The BFS-2 critical zero-power facility at the Inst. of Physics and Power Engineering (IPPE) was designed for simulations of the core and shielding of sodium-cooled, fast reactors, for neutron data validation and comparison with experimental results. At the BFS-2 facility, the BFS-62-3A critical benchmark experiment was set-up as a mock-up of the BN-600 reactor, with hybrid MOX fuel and stainless steel reflectors. A UO{sub 2} blanket and a large non-homogeneous stainless-steel reflector surround the core. The lattice is hexagonal of pitch 5.1 cm and metallic dowels are used to keep in central position cylindrical rods made of different types of material (fissile, fertile, blanket, plenum, shielding and absorber). A typical subassembly is formed in piling up various pellets of about 1 cm in height and 4.6 cm in diameter, conferring large heterogeneity in the axial direction. The full-core model development was a complex task due to the large number of subassemblies and the axial subassembly heterogeneity. In ERANOS-2.2, it was necessary to homogenize axially per region the pellets used to form the subassembly. The self-shielded macroscopic cross-sections were calculated using the cell code ECCO in association with JEFF-3.1 and ENDF/B-VI.8 data libraries. The core calculations were performed with broad cross-sections data in 33 neutron energy groups with the solver AVNM in the diffusion approximation, mostly. In MCNPX-2.7.0, a step-by-step approach was used, starting with a model in which the fissile rods were simulated on a homogeneous level, to finally integrate the actual heterogeneous description of the subassemblies. The code-to-code cell analysis performed between ECCO, SERPENT and MCNPX with different modern nuclear data library revealed that the results for the infinite multiplication factor between Monte Carlo and deterministic analysis are in good agreement ({Delta}p < 100 pcm). The differences between the results were observed to be larger for the neutron data libraries, with reactivity differences up to 350 pcm. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A modified Monte Carlo 'local importance function transform' method

The Local Importance Function Transform (LIFT) method uses an approximation of the contribution transport problem to bias a forward Monte-Carlo (MC) source-detector simulation [1-3]. Local (cell-based) biasing parameters are calculated from an inexpensive deterministic adjoint solution and used to modify the physics of the forward transport simulation. In this research, we have developed a new expression for the LIFT biasing parameter, which depends on a cell-average adjoint current to scalar flux (J{sup *}/{phi}{sup *}) ratio. This biasing parameter differs significantly from the original expression, which uses adjoint cell-edge scalar fluxes to construct a finite difference estimate of the flux derivative; the resulting biasing parameters exhibit spikes in magnitude at material discontinuities, causing the original LIFT method to lose efficiency in problems with high spatial heterogeneity. The new J{sup *}/{phi}{sup *} expression, while more expensive to obtain, generates biasing parameters that vary smoothly across the spatial domain. The result is an improvement in simulation efficiency. A representative test problem has been developed and analyzed to demonstrate the advantage of the updated biasing parameter expression with regards to solution figure of merit (FOM). For reference, the two variants of the LIFT method are compared to a similar variance reduction method developed by Depinay [4, 5], as well as MC with deterministic adjoint weight windows (WW). (authors)

97 MATHEMATICS AND COMPUTING↗

Comparison of Serpent and HELIOS-2 as applied for the PWR few-group cross section generation

This paper discusses recent modifications to the Serpent Monte Carlo code methodology and related to the calculation of few-group diffusion coefficients and reflector discontinuity factors The new methods were assessed in the following manner. First, few-group homogenized cross sections calculated by Serpent for a reference PWR core were compared with those generated 1 commercial deterministic lattice transport code HELIOS-2. Second, Serpent and HELIOS-2 fe group cross section sets were later employed by nodal diffusion code DYN3D for the modeling the reference PWR core. Finally, the nodal diffusion results obtained using the both cross section sets were compared with the full core Serpent Monte Carlo solution. The test calculations show that Serpent can calculate the parameters required for nodal analyses similar to conventional deterministic lattice codes. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Monte Carlo burnup code acceleration with the correlated sampling method. Preliminary test on an UOX cell with TRIPOLI-4{sup R}

For several years, Monte Carlo burnup/depletion codes have appeared, which couple a Monte Carlo code to simulate the neutron transport to a deterministic method that computes the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3 dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the time-expensive Monte Carlo solver called at each time step. Therefore, great improvements in term of calculation time could be expected if one could get rid of Monte Carlo transport sequences. For example, it may seem interesting to run an initial Monte Carlo simulation only once, for the first time/burnup step, and then to use the concentration perturbation capability of the Monte Carlo code to replace the other time/burnup steps (the different burnup steps are seen like perturbations of the concentrations of the initial burnup step). This paper presents some advantages and limitations of this technique and preliminary results in terms of speed up and figure of merit. Finally, we will detail different possible calculation scheme based on that method. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimization of multi-group cross sections for fast reactor analysis

The selection of the number of broad energy groups, collapsed broad energy group boundaries, and their associated evaluation into collapsed macroscopic cross sections from a general 238-group ENDF/B-VII library dramatically impacted the k eigenvalue for fast reactor analysis. An analysis was undertaken to assess the minimum number of energy groups that would preserve problem physics; this involved studies using the 3D deterministic transport parallel code PENTRAN, the 2D deterministic transport code SCALE6.1, the Monte Carlo based MCNP5 code, and the YGROUP cross section collapsing tool on a spatially discretized MOX fuel pin comprised of 21% PUO{sub 2}-UO{sub 2} with sodium coolant. The various cases resulted in a few hundred pcm difference between cross section libraries that included the 238 multi-group reference, and cross sections rendered using various reaction and adjoint weighted cross sections rendered by the YGROUP tool, and a reference continuous energy MCNP case. Particular emphasis was placed on the higher energies characteristic of fission neutrons in a fast spectrum; adjoint computations were performed to determine the average per-group adjoint fission importance for the MOX fuel pin. This study concluded that at least 10 energy groups for neutron transport calculations are required to accurately predict the eigenvalue for a fast reactor system to within 250 pcm of the 238 group case. In addition, the cross section collapsing/weighting schemes within YGROUP that provided a collapsed library rendering eigenvalues closest to the reference were the contribution collapsed, reaction rate weighted scheme. A brief analysis on homogenization of the MOX fuel pin is also provided, although more work is in progress in this area. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Probabilistic Modeling of Settlement Risk at Land Disposal Facilities - 12304

The long-term reliability of land disposal facility final cover systems - and therefore the overall waste containment - depends on the distortions imposed on these systems by differential settlement/subsidence. The evaluation of differential settlement is challenging because of the heterogeneity of the waste mass (caused by inconsistent compaction, void space distribution, debris-soil mix ratio, waste material stiffness, time-dependent primary compression of the fine-grained soil matrix, long-term creep settlement of the soil matrix and the debris, etc.) at most land disposal facilities. Deterministic approaches to long-term final cover settlement prediction are not able to capture the spatial variability in the waste mass and sub-grade properties which control differential settlement. An alternative, probabilistic solution is to use random fields to model the waste and sub-grade properties. The modeling effort informs the design, construction, operation, and maintenance of land disposal facilities. A probabilistic method to establish design criteria for waste placement and compaction is introduced using the model. Random fields are ideally suited to problems of differential settlement modeling of highly heterogeneous foundations, such as waste. Random fields model the seemingly random spatial distribution of a design parameter, such as compressibility. When used for design, the use of these models prompts the need for probabilistic design criteria. It also allows for a statistical approach to waste placement acceptance criteria. An example design evaluation was performed, illustrating the use of the probabilistic differential settlement simulation methodology to assemble a design guidance chart. The purpose of this design evaluation is to enable the designer to select optimal initial combinations of design slopes and quality control acceptance criteria that yield an acceptable proportion of post-settlement slopes meeting some design minimum. For this specific example, relative density, which can be determined through field measurements, was selected as the field quality control parameter for waste placement. This technique can be extended to include a rigorous performance-based methodology using other parameters (void space criteria, debris-soil mix ratio, pre-loading, etc.). As shown in this example, each parameter range, or sets of parameter ranges can be selected such that they can result in an acceptable, long-term differential settlement according to the probabilistic model. The methodology can also be used to re-evaluate the long-term differential settlement behavior at closed land disposal facilities to identify, if any, problematic facilities so that remedial action (e.g., reinforcement of upper and intermediate waste layers) can be implemented. Considering the inherent spatial variability in waste and earth materials and the need for engineers to apply sound quantitative practices to engineering analysis, it is important to apply the available probabilistic techniques to problems of differential settlement. One such method to implement probability-based differential settlement analyses for the design of landfill final covers has been presented. The design evaluation technique presented is one tool to bridge the gap from deterministic practice to probabilistic practice. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Transuranic Transmutation and Criticality Calculation Sensitivity to Heterogeneous Lattice Effects - 12391

Using Mixed Oxide (MOX) fuel in traditional Pressurized Water Reactor (PWR) assemblies has been researched at length and has shown to provide the benefit of transmutation and targets the amount and toxicity of high level waste needed to be managed. Advanced MOX concepts using enriched Uranium Dioxide (UO{sub 2}) are required for multiple recycling of plutonium. The use of MOX and ordinary UO{sub 2} fuel in the same assembly as well as unfueled rods and assembly edge effects contrasts with the unit cell computational assumption of a uniform infinite array of rods. While a deterministic method of calculating the Dancoff factor has traditionally been employed in fuel assembly analysis due to the lighter computational and modeling requirements, this research seeks to determine the validity of the uniform, infinite lattice assumption with respect to Dancoff factor and determine the magnitude of the impact of nonuniform lattice effects on fuel assembly criticality calculations as well as transuranic isotope production and transmutation. This research explored the pin-to-pin interaction in a non-uniform lattice of MOX fuel rods and UO{sub 2} fuel rods through the impact of the calculated Dancoff factors from the deterministic method used in SCALE versus the Monte Carlo method used in the code DANCOFF-MC. Using the Monte Carlo method takes into account the non-uniform lattice effects of having neighboring fuel rods with different cross-sectional spectra whereas the Dancoff factor calculated by SCALE assumes a uniform, infinite lattice of one fuel rod type. Differences in eigenvalue calculations as a function of burnup are present between the two methods of Dancoff factor calculation. The percent difference is greatest at low burnup and then becomes smaller throughout the cycle. Differences in the transmutation rate of transuranic isotopes in the MOX fuel are also present between the Dancoff factor calculation methods. The largest difference is in Pu-239, Pu-242, and Am-241 composition whereas U-238, Pu-242, and Pu-238 composition was not changed by taking into account the non-homogenous lattice effects. Heterogeneous lattice effects do change the calculated eigenvalue and transmutation rate in a non-uniform lattice of MOX fuel rods and UO{sub 2} fuel. However, the uncertainty in the ENDF data used by SCALE in these calculations is large enough that the infinite lattice assumption remains valid. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗