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Building energy codes have a 40-year history of reducing consumer energy bills. Today’s energy codes provide more than 30% savings compared to those of less than a decade ago, which translates to over $60 billion saved by U.S. homes and businesses. Learn more about DOE's Building Energy Codes program in this fact sheet.
Examples disclosed herein relate to path-synchronous performance monitoring of an interconnection network based on source code attribution. A processing node in the interconnection network has a profiler module to select a network transaction to be monitored, determine a source code attribution associated with the network transaction to be monitored, and issue a network command to execute the network transaction to be monitored. A logger module creates, in a buffer, a node temporal log associated with the network transaction and the network command. A drainer module periodically captures the node temporal log. The processing node has a network interface controller to receive the network command and mark a packet generated for the network command to be temporally tracked and attributed back to the source code attribution at each hop of the interconnection network traversed by the marked packet.
This fact sheet describes what Automatic Receptacle Controls (ARCs) are, how they work, ARC benefits and savings, and last, how they are being incorporated into energy codes. This fact sheet is meant to be a resource for energy codes adopters and influencers to help encourage them to adopt ARC provisions in their energy code.
Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.
Accurate cross sections are of great importance to Monte Carlo particle transport calculation codes which use pointwise cross sections. It is well known that cross sections have much dependence on temperature on account of Doppler effect which is particularly vital for resonance absorption cross sections. In general, pre-prepared continuous-energy libraries are used in Monte Carlo codes, which is feasible in many applications. However, in multi-physics calculations where neutronics and thermal hydraulics are coupled, cross sections at a fine interval of temperatures are desired, which brings a great challenge to computer memory. Consequently, different methods about on the fly Doppler broadening for cross sections are proposed, which can generate cross sections at the specific temperature points during neutron simulations. These methods can be roughly classified into two categories: one is to calculate the required cross sections by different algorithms, such as interpolation using a high order function expansion, multipole representation, and different integration algorithms based on Doppler broadening equation. The other, for instance, target motion sampling (TMS), does not calculate the Doppler broadening cross sections but takes into account Doppler effect by rejection technique. In this paper, several on the fly Doppler broadening algorithms based on Doppler broadening equation are implemented in the Reactor Monte Carlo code RMC, and then the accuracy and efficiency are discussed and compared. In this paper, several algorithms for on the fly Doppler broadening based on Doppler broadening equation have been implemented in RMC and the focus falls on the comparison of the Gauss Legendre quadrature and Gauss Hermite quadrature. Gauss Legendre quadrature is more accurate than Gauss Hermite quadrature but also more time consuming. Base temperature has a significant impact on Gauss Hermite quadrature while increasing base temperature to room temperature (300 K) can give satisfactory results. In addition, the proportion of overhead of Doppler broadening treatment in total computational time tends to decrease with an increase number of nuclides in fuel. For depletion calculation, both algorithms are in good agreement with reference and the relative errors of K{sub inf} are within 5 times of standard deviation. As for total computational time, the ratio between Gauss Legendre quadrature or Gauss Hermite quadrature and reference decreases and reaches 9.6 or 3.4 at last, respectively. Four important isotopes are chosen to compare the atom density and all relative errors are within 0.25%. After comparisons of different algorithms and different base temperatures, it can be found that Gauss Hermite quadrature broadening from 300 K can perform on the fly cross section Doppler broadening with least total computational time and acceptable precision. (authors)
The in-pile behavior of light-water-reactor (LWR) fuels is governed by the physics from various time and spatial scales. Accordingly, multi-scale modeling and simulation are needed to accurately predict the fuel performance at the engineering scale. To improve the traditional fuel performance modeling, the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program targets at developing multi-scale, multiphysics modeling tools for in-pile fuel behavior prediction under various operating or accident scenarios. In traditional fuel performance modeling, the history of fuel is represented by a single parameter, fuel burn-up. Burn-up measures the energy that has been extracted from fuels. However, it is not an adequate measure of fuel history as it ignores the flux effect, which is critical for the irradiation-induced microstructural evolution in fuels. Moreover, the traditional fuel performance models are usually fitted to experimental data. Their capabilities of being extrapolated to new operating conditions and being extended to new types of fuels are strongly limited by the empirical or semi-empirical nature. To improve the burn-up based models, a microstructure based fuel approach, the MOOSE-BISON-MARMOT (MBM) tool-kit, is being developed under the fuel product line (FPL) of the NEAMS program for predictive fuel performance modeling. In the MBM approach, the evolution of fuel microstructure and changes in fuel properties are described by the MARMOT code. The transient fuel properties obtained from MARMOT are then fed into the BISON code for engineering scale fuel performance modeling. Both BISON and MARMOT are developed within the MOOSE framework, which was developed at Idaho National Laboratory. In this summary, the development and the capabilities of the MARMOT code will be introduced. In the past few years, several materials models have been developed including: (1) a grain growth model that describes the grain size evolution as a function of time, temperature and fuel porosity, considering the effects of impurity and porosity dragging and anisotropic grain boundary energy, (2) a fission gas release model that describes the fission gas diffusion in grain interior, fission gas bubble formation in grain interior and at grain boundaries, and fission gas release to the fuel-cladding gap, (3) a fracture model that describes the fracture initiation and propagation in grain interior and along grain boundaries, and (4) a thermal conductivity model that describes the change in thermal conductivity due to grain growth, gas bubble formation, fracture and radiation damage. Several other models are also being developed in MARMOT for hydride formation in Zr-based cladding, radiation damage and grain size subdivision. In most cases, these materials models are coupled with each other. For instance, to accurate predict the transient thermal conductivity, information on grain size, fission gas density, porosity and fracture is required. Further development is on going to improve all these models. These models are developed primarily for UO{sub 2} fuels used in LWRs. They can be extended to other fuels with possibly new development. All models in MARMOT will be rigorously verified and validated before being applied for fuel performance modeling. A version of MARMOT was recently released in September 2015 with an assessment report. (authors)
In this study, a preliminary structural assessment on a graphite component of a VHTR was done in accordance with the semi-probabilistic assessment procedures of the latest 2015 edition of the ASME Boiler and Pressure Vessel Code, Section III, Div. 5, Subpart HHA-Graphite Materials. Establishment of the Weibull distribution for the tensile strength is essential to set up the stress limits based on the probability of failure of the graphite materials. All parameters required in the ASME code were identified and evaluated for a nuclear graphite material, IG-110. The assessment of design level was done on one of fuel elements in a Korean VHTR design by two methodologies in the ASME code: (1) Simplified assessment and (2) Full assessment. The structural integrity of the fuel element was assured by both assessment methods. Also, the effect of the number of integration volume groups on the probability of failure in the full assessment was investigated and a recommendation for the conservative results was suggested. (authors)
A new neutron transport lattice physics code, cosLATC, which is an essential part in COSINE (Core and System Integrated Engine) code package, has been developed by SPICRI. It is mainly used for 2-D transport calculations on Pressurized Water Reactor (PWR) assemblies or pin cells. cosLATC generates few group constants for the core physics code cosCORE in COSINE package. With regards to cross-section data, WIMS-D 69 and 281 energy groups library is employed currently. cosLATC also has capability of resonance treatment, depletion and fuel temperature calculation. cosLATC uses modular tracking and parallelization technique in MOC transport calculation, which can save lots of memory and running time. In this paper, MOC module in cosLATC are introduced, the accuracy and efficiency of the module are verified by C5G7 benchmark and a PWR typical assembly. (authors)
Predictive modeling and simulation of the performance of a nuclear reactor and its fuel is a challenging task because of the large number of coupled physical phenomena that must be addressed. In addition to this intrinsic complexity, model uncertainty must be accounted for in any analysis if the model will be used to facilitate design or operational decisions which may impact safety and performance. Rigorous, structured uncertainty analyses are performed by first characterizing the model's input uncertainties and, by propagating the uncertainty through the model in order to estimate the output's uncertainty. This paper presents the state of advancement of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) project to characterize the uncertainty of the CFD code Nek5000 using the Dakota package. Nek5000 is a high order spectral element computational fluid dynamics (CFD) code developed at Argonne National Laboratory for high resolution spectral-filtered large eddy simulations (LESs) and unsteady Reynolds averaged Navier-Stokes (RANS) simulations. The Dakota package developed at Sandia National Laboratory can be integrated with many scientific and engineering codes to facilitate efficient, effective uncertainty quantification (UQ) and sensitivity analyses. Dakota is designed to interface with external packages/codes such as Nek5000 through a script-driven interface called fork. Such interface provides maximum flexibility to the users for pre- and post-processing tasks preceding and following each function evaluation. (authors)
System codes such as TRACE and RELAP5 have the option of adding boron to be dissolved in the water. In principle, the density and the viscosity of the water are not affected when the amounts of dissolved boron are very small. However, if the boron concentration is significant, water density and viscosity will be affected. Version 5.890 of the TRACE code has a new boron model with the option of modifying the water density and viscosity to account for the presence of dissolved boron. The input variable ISOLUT is used for this purpose. If ISOLUT=0, no boron is dissolved in the water. If ISOLUT=1, boron is dissolved in the water, and the liquid water density and viscosity are not modified by the dissolved boron. If ISOLUT=2, boron is dissolved in the water, and the liquid water density and viscosity are modified by the dissolved boron. This paper evaluates some features of this new boron model in the TRACE code.
The MSRs is a liquid-fuel reactor in which uranium, fission products and actinides are dissolved in the molten salt. The molten salt reactors are featured by circulating fuel, low pressure and high temperature. The MSRs meets many of the future goals of nuclear technology, in particular for what concerns as improved sustainability and unique characteristics in terms of actinide burning. The fluid nature of fuel in MSRs gives extra flexibility in reactor design, fuel fabrication and recycling. But because of the application of fluid fuel, MSRs have several special characteristics compared with the traditional solid-fuel reactors. Firstly, the transport of the delayed neutron precursors by the fluid flow reduces the contribution of delayed neutrons to the chain reaction.. Secondly, the fact that the fuel is dissolved in the coolant rather than separated from the coolant by the claddings results in a much stronger coupling phenomenon between the neutronics and thermal-hydraulics. Thirdly, the shape of the fuel is determined by the container because of the characteristics of fluid, the unstructured meshes are required to model the complex geometry accurately. However most of the conventional reactor codes were developed for solid-fuel reactor and therefore not capable of taking liquid fuel flow into account. To address all these particular modeling issues of MSRs, a multi-physics code named TANSY has been developed in our laboratory. In this paper, the benchmark problem based on the MSFR design was calculated to verify the code.
This paper presents a joint work conducted at CEA Saclay and JAEA Tokai aimed at comparing the Monte Carlo codes TRIPOLI-4{sup R} and MVP on a selection of ICSBEP benchmarks. Our goal is to establish a common set of Monte Carlo input decks, as a basis for rigorous inter-code comparison in criticality-safety. As a reference, we will use the MCNP Criticality Validation Suite: other Monte Carlo developers might easily join this effort in the future. For the purpose of inter-code comparison, the TRIPOLI-4{sup R} and MVP input decks have been exactly translated from those of MCNP, without any further assumptions. Both TRIPOLI-4{sup R} and MVP have been run with the same ENDF/B-VII.0 evaluated nuclear data and, as far as possible, the same simulation options as in the original LANL work (same initial source, same number of active and discarded cycles and neutrons per cycle). (authors)
For application in criticality safety, numerical code systems require profound validation against experimental data. In terms of burn-up credit, this refers to the inventory determination as well as the subsequent criticality calculation. Within this framework, a dedicated, conservative estimation of uncertainties, bias and bias uncertainties for the resulting calculated multiplication factor k{sub eff} is indispensable. However, measures to reduce excess conservatism may become desirable, depending on the application case. For this reason GRS implemented a methodology to validate a calculation code system for criticality safety analyses for systems with irradiated nuclear fuel. The work at hand demonstrates this methodology by means of the GRS home-built inventory determination system KENOREST and ORNL's well-known SCALE 6 CSASS criticality safety calculation sequence. A number of 40 radiochemical analysis samples taken from SFCOMPO and elsewhere have been calculated to derive isotopic correction factors in different ways, depending on the required level of conservatism and the calculational efforts to be carried out. This includes bounding methods as well as different Monte Carlo sampling approaches. Furthermore, from the ICSBEP a number of 515 critical benchmark experiment configurations comprising water moderated low enriched UO{sub 2} fuel rods and water moderated mixed oxide (MOX) fuel rods have been selected and evaluated. Important absorber and structure materials are also covered. Various trending and sensitivity and uncertainty analysis methods have been applied, again to derive conservative estimates on the various contributions to k{sub eff} uncertainties. The overall methodology is applicable to low enriched, water moderated PWR uranium dioxide fuels in a burn-up range of about 10 to 60 GWd/tHM, and validates the reactivity contributions of the major uranium and plutonium isotopes. The methodology itself has no limitation which requires the exclusion of further isotopes as e.g. fission products. However, its application is constrained by the experimental database being publicly available. After the potential provision of an extended database in the future, the range of applicability can easily be extended to more nuclides. In addition, it is not limited to the code systems being used here but can also be applied using different numerical tools. For a generic PWR spent fuel pool rack and different enrichment and burn-up combinations, the impact of the current level of validation on k{sub eff} is demonstrated and quantified. (authors)
The Bison fuel performance code has been under development at Idaho National Laboratory by various programs within the U.S. Department of Energy since 2009. As part of any fuel performance code development, validation is necessary. To this end, several Halden experiments have been used. Early on, the focus was on validating the thermal mechanical behaviour, including pellet cladding mechanical interaction and fission gas release models implemented in Bison. Support for design-basis accident capabilities began in approximately 2014. Also in 2014, the development of models for accident tolerant fuel (ATF) concepts also began. This includes dopedUO2 fuel for which Halden has some experiments with temperature and fission gas release measurements. The Bison team has been fortunate to have two senior developers be secondees to Halden for a year: the late Dr. Giovanni Pastore from May 2015 to April 2016 and the now retired Dr. Richard Williamson in 2018. The paper will provide examples of Bison validation using Halden data for standard UO2 fuel under normal operation and loss-of-coolant accident condition, and ATF concepts. A tribute to the legacy that both the late Giovanni and retired Richard left on the Bison code is provided.
This report describes major features of the most recent version of the MARS code as well as ongoing developments. The list of features includes various options for geometry models, a beam line builder based on MADX code, import of geometry models in GDML format, use of structured and unstructured meshes for scoring purposes, an update to the recent TENDL library for a number of projectiles at low energies (up to 250 MeV), and a recently implemented method to calculate spatial distribution of residual dose in a single computer run without an intermediate source. Examples of the code application to various projects are presented as well.
The AMPX nuclear data processing code reads evaluated nuclear data files and prepares libraries in continuous energy (CE) and multigroup (MG) formats. These libraries are used by the transport and depletion codes in the SCALE code system.
Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.
This is code associated with the publication “Nonparametric Multi-shape Modeling with Uncertainty Quantification,” authored by Hengrui Luo (Lawrence Berkeley National Laboratory) and Justin Strait (Los Alamos National Laboratory). The code is used to fit multiple-output Gaussian process (GP) models of planar closed curves to collections of ordered point sets, allowing for flexible nonlinear prediction of the underlying curve under dense or sparse point set samplings and with or without noise, as well as tractable uncertainty quantification. To do this, we employ use of a periodic kernel to account for the nonlinear input space of closed curves, and combine with coregionalization models to account for dependence both (i) between curve coordinates, and (ii) between pairs of curves. Functions in the code are capable of fitting these models, as well as performing additional tasks with the fitted curves such as (a) shape registration and alignment, (b) shape averaging, and (c) fitting for curve sub-populations / clusters.