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A processor emulator and a suite of benchmark applications have been developed to assist in characterizing the performance of data-centric workloads on current and future computer architectures. Some of the applications have been collected from other open source projects. For more details on the emulator and an example of its usage, see reference [1].
The Consortium for Advanced Simulation of Light Water Reactors, the first US DOE Energy Innovation Hub, is developing and deploying a suite of directly coupled, high-fidelity physics methods known as VERA for performing engineering analyses of operating commercial nuclear power reactors. The centerpiece of VERA is the reactor core simulator, which employs the direct coupling of a 3D neutron transport code, a two-phase sub-channel thermal-hydraulic code, and a well-known isotopic depletion and decay code. Together these tools represent the most rigorous reactor simulator available today. Recently added capabilities include the depletion, shuffling, and discharge of fuel assemblies, enabling VERA to simulate multiple fuel cycles of operation. To demonstrate this capability, VERA has been used to simulate over 18 years of operation of TVA’s Watts Bar Nuclear Unit 1, and the results of these calculations have been used to quantify its performance in an industry-grade benchmarking activity. Comparisons are made with measured critical boron concentrations, control bank reactivity worths, isothermal temperature coefficients, and in-core neutron flux distributions. These results demonstrate that the advanced tools in VERA are capable for application to practical and common industrial problems.
An advanced system analysis tool SAM is being developed for fast-running, improved-fidelity, and whole-plant transient analyses at Argonne National Laboratory under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As an important part of code development, companion validation activities are being conducted to ensure the performance and validity of the SAM code. This paper presents the benchmark simulations of two EBR-II tests, SHRT-45R and BOP-302R, whose data are available through the support of DOE-NE’s Advanced Reactor Technology (ART) program. The code predictions of major primary coolant system parameter are compared with the test results. Additionally, the SAS4A/SASSYS-1 code simulation results are also included for a code-to-code comparison.
NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2016 (Q1 2016). Our methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems, and it models the capital costs for such systems.
The Benchmarks of Global Clean Energy Manufacturing will help policymakers and industry gain deeper understanding of global manufacturing of clean energy technologies. Increased knowledge of the product supply chains can inform decisions related to manufacturing facilities for extracting and processing raw materials, making the array of required subcomponents, and assembling and shipping the final product. This brochure summarized key findings from the analysis and includes important figures from the report. The report was prepared by the Clean Energy Manufacturing Analysis Center (CEMAC) analysts at the U.S. Department of Energy's National Renewable Energy Laboratory.
Liquid Metal Reactors (LMRs) continue to be considered as an attractive concept for advanced reactor design. Software packages such as SASSYS are being used to im-prove new LMR designs and operating characteristics. Significant cost and safety im-provements can be realized in advanced liquid metal reactor designs by emphasizing inherent or passive safety through crediting the beneficial reactivity feedbacks associ-ated with core and structural movement. This passive safety approach was adopted for the Fast Flux Test Facility (FFTF), and an experimental program was conducted to characterize the structural reactivity feedback. The FFTF passive safety testing pro-gram was developed to examine how specific design elements influenced dynamic re-activity feedback in response to a reactivity input and to demonstrate the scalability of reactivity feedback results to reactors of current interest. The U.S. Department of En-ergy, Office of Nuclear Energy Advanced Reactor Technology program is in the pro-cess of preserving, protecting, securing, and placing in electronic format information and data from the FFTF, including the core configurations and data collected during the passive safety tests. Benchmarks based on empirical data gathered during operation of the Fast Flux Test Facility (FFTF) as well as design documents and post-irradiation examination will aid in the validation of these software packages and the models and calculations they produce. Evaluation of these actual test data could provide insight to improve analytical methods which may be used to support future licensing applications for LMRs
This project is a benchmark suite of Open-MP parallel codes that have been checked for data races. The programs are marked to show which do and do not have races. This allows them to be leveraged while testing and developing race detection tools.
Efforts are underway at the Y-12 National Security Complex (Y-12) to modernize the recovery, purification, and consolidation of un-irradiated, highly enriched uranium metal. Successful integration of advanced technology such as Electrorefining (ER) eliminates many of the intermediate chemistry systems and processes that are the current and historical basis of the nuclear fuel cycle at Y-12. The cost of operations, the inventory of hazardous chemicals, and the volume of waste are significantly reduced by ER. It also introduces unique material forms and compositions related to the chemistry of chloride salts for further consideration in safety analysis and engineering. The work herein briefly describes recent investigations of nuclear criticality for 235UO2Cl2 (uranyl chloride) and 6LiCl (lithium chloride) in aqueous solution. Of particular interest is the minimum critical mass of highly enriched uranium as a function of the molar ratio of 6Li to 235U. The work herein also briefly describes recent investigations of nuclear criticality for 235U metal reflected by salt mixtures of 6LiCl or 7LiCl (lithium chloride), KCl (potassium chloride), and 235UCl3 or 238UCl3 (uranium tri-chloride). Computational methods for analysis of nuclear criticality safety and published nuclear data are employed in the absence of directly relevant experimental criticality benchmarks.
Liquid salt-cooled reactors, such as the Fluoride Salt-Cooled High-Temperature Reactor (FHR), offer passive decay heat removal through natural circulation using Direct Reactor Auxiliary Cooling System (DRACS) loops. The behavior of such systems should be well-understood through performance analysis. The advanced system thermal-hydraulics tool System Analysis Module (SAM) from Argonne National Laboratory has been selected for this purpose. The work presented here is part of a larger study in which SAM modeling capabilities are being enhanced for the system analyses of FHR or Molten Salt Reactors (MSR). Liquid salt thermophysical properties have been implemented in SAM, as well as properties of Dowtherm A, which is used as a simulant fluid for scaled experiments, for future code validation studies. Additional physics modules to represent phenomena specific to salt-cooled reactors, such as freezing of coolant, are being implemented in SAM. This study presents a useful first benchmark for the applicability of SAM to liquid salt-cooled reactors: it provides steady-state and transient comparisons for a salt reactor system. A RELAP5-3D model of the Mark-1 Pebble-Bed FHR (Mk1 PB-FHR), and in particular its DRACS loop for emergency heat removal, provides steady state and transient results for flow rates and temperatures in the system that are used here for code-to-code comparison with SAM. The transient studied is a loss of forced circulation with SCRAM event. To the knowledge of the authors, this is the first application of SAM to FHR or any other molten salt reactors. While building these models in SAM, any gaps in the code’s capability to simulate such systems are identified and addressed immediately, or listed as future improvements to the code.
High-fidelity, multi-physics modeling and simulation (M&S) tools are being developed and utilized for a variety of applications in nuclear science and technology and show great promise in their abilities to reproduce observed phenomena for many applications. Even with the increasing fidelity and sophistication of coupled multi-physics M&S tools, the underpinning models and data still need to be validated against experiments that may require a more complex array of validation data because of the great breadth of the time, energy and spatial domains of the physical phenomena that are being simulated. The Expert Group on Multi-Physics Experimental Data, Benchmarks and Validation (MPEBV) of the Nuclear Energy Agency (NEA) of the Organization for Economic Cooperation and Development (OECD) was formed to address the challenges with the validation of such tools. The work of the MPEBV expert group is shared among three task forces to fulfill its mandate and specific exercises are being developed to demonstrate validation principles for common industrial challenges. This paper describes the overall mission of the group, the specific objectives of the task forces, the linkages among the task forces, and the development of a validation exercise that focuses on a specific reactor challenge problem.
The burnup of an HEU fueled dynamically operated research reactor, the Oak Ridge Research Reactor, was experimentally reconstructed using two different analytic methodologies and a suite of signature isotopes to evaluate techniques for estimating burnup for research reactor fuel. The methods studied include using individual signature isotopes and the complete mass spectrometry spectrum to recover the sample’s burnup. The individual, or sets of, isotopes include 148 Nd, 137 Cs+ 137 Ba, 139 La, and 145 Nd+ 146 Nd. The storage documentation from the analyzed fuel material provided two different measures of burnup: burnup percentage and the total power generated from the assembly in MWd. When normalized to conventional units, these two references differed by 7.8% (395.42GWd/MTHM and 426.27GWd/MTHM) in the resulting burnup for the spent fuel element used in the benchmark. Among all methods being evaluated, the results were within 11.3% of either reference burnup. The results were mixed in closeness to both reference burnups; however, consistent results were achieved from all three experimental samples.
As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the subchannel code CTF is being used for single- and two-phase flow analysis under light water reactor operating conditions. Accurate determination of flow distribution, pressure drop, and void content is crucial for prediction of margins to thermal crisis and neutronic feedback, and therefore more efficient plant performance. In preparation for the intended applications, CTF has been validated against experimental facilities comprising the General Electric (GE) 3×3 bundle, the BWR Full-size Fine-mesh Bundle Tests (BFBT), the RISO tube, and the PWR Subchannel and Bundle Tests (PSBT). Meanwhile, the licensed and industrially well-recognized subchannel code VIPRE-01 is used to generate a baseline set of simulations for the targeted tests, and solution parameters are compared to CTF results. The flow split verification problem and single-phase GE 3×3 result in essentially perfect agreement between CTF and VIPRE-01. For two-phase GE 3×3 cases, flow and quality discrepancies arise in the annular-mist flow regime, yet significant improvement is observed in CTF when void drift and two-phase turbulent mixing enhancement are considered. BFBT pressure drop benchmark shows close agreement between predicted and measured results in general, although considerable over-prediction of CTF is observed at relatively high void locations of the facility. This over-estimation tendency is confirmed by RISO cases. While overall statistics are satisfactory, the BFBT bubbly/slug/churn-turbulent flow void contents are markedly over-predicted by CTF, the latter being consistent with PSBT results. Such two-phase closure terms in CTF as turbulent mixing, interfacial and wall friction, and subcooled boiling heat transfer need further improvement using more mechanistic models and high-to-low calibration techniques
In the context of the European H2020 project SESAME, a work package was dedicated to the validation of code coupling for the thermal-hydraulics of pool type reactors. To this end, CEA proposed a benchmark exercise of the so-called dissymmetric test performed at the end of life of the PHENIX reactor. The PHENIX reactor was an experimental reactor operated by CEA in France from 1974 until 2009. The knowledge and data acquired over the lifetime of this reactor are of paramount importance for the development of future sodium-cooled generation IV reactors. At the beginning of this test, the reactor is operated at nominal power (350 MWth) with 3 primary pumps and 4 intermediate heat exchangers. During this test, a pump trip occurs at the secondary side of one of the two loops (one loop provides coolant to two intermediate heat exchangers). The chain reaction is then stopped while the pumps remain operating at nominal speed. Dissymmetric flow patterns are then observed in the cold pool as hot sodium leaves the intermediate heat exchangers that are no longer cooled. The failed secondary pump is then restarted while the rotational speed of the other is reduced. Eventually, a stable homogeneous state is reached. This transient is challenging for both modelers and codes since this exercise tackles an industrial scale reactor featuring complex flows and interactions between different scales. The physical phenomena observed include thermal stratification, flow mixing and buoyancy effects. In order to accurately model these phenomena for a reasonable computational costs, the partners used System Thermal Hydraulics codes coupled with Computational Fluid Dynamics codes and one even included a subchannel code. In this paper, the PHENIX reactor and its behavior during the dissymmetric test are described. Then, a comparison of the different modeling options selected by the partners is offered. Finally, the results are compared to the experimental data and discussed and modelling recommendations are proposed.
Phénix is a French pool-type sodium-cooled prototype reactor; before the definitive shutdown, occurred in 2009, a final set of experimental tests are carried out in order to increase the knowledge on the operation and the safety aspect of the pool-type liquid metal-cooled reactors. One of the experiments was the Dissymmetric End-of-Life Test which was selected for the validation benchmark activity in the frame of SESAME project. The computer code validation plays a key role in the safety assessment of the innovative nuclear reactors and the Phénix dissymmetric test provides useful experimental data to verify the computer codes capability in the asymmetric thermal-hydraulic behaviour into a pool-type liquid metal-cooled reactor. This paper shows the comparison of the outcomes obtained with six different System Thermal-Hydraulic (STH) codes: RELAP5-3D©, SPECTRA, ATHLET, SAS4A/SASSYS-1, ASTEC-Na and CATHARE. The nodalization scheme of the reactor was individually achieved by the participants; during the development of the thermal-hydraulic model, the pool nodalization methodology had a special attention in order to investigate the capability of the STH codes to reproduce the dissymmetric effects which occurs in each loop and into pools, caused by the azimuthal asymmetry of the boundary conditions. The modelling methodology of the participants is discussed and the main results are compared in this paper to obtain useful guide lines for the future modelling of innovative liquid metal pool-type reactors.
As distributed energy resources play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. The comparison of a distribution system run with fixed feed-in voltage is compared to the closely tied distribution-transmission co-simulation. It is determined that even without advanced voltage controls, the feed-in voltage response of the transmission system shows a lower level of voltage excursions. Therefore, control methods for voltage stability should be benchmarked on realistic transmission and distribution co-simulations for more accurate assessment of voltage profiles.
An integrated testbed using digital real-time simulator (DRTS) and a high-performance computing (HPC) cluster is presented here to compare speed and performance of computational schemes to mitigate time-critical issues in electric power systems. The first approach in this testbed validation is taken by running a set of closed-loop load shedding algorithms to compare and contrast two paradigms of arresting cascading failure propagation. Two algorithms involve solving DC and AC power flow model-based optimization problems to compute load shedding at different buses, while a model-based stochastic search using parallel computing provides a viable alternative. The algorithms are implemented in the DRTS-HPC testbed for the IEEE 14-bus benchmark transmission system. As a proof of the concept, simulation results are presented for implementation of closed-loop load-shedding algorithms for cascading failures in the DRTS-HPC testbed
This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.
Machine Learning (ML) has seen an exponential growth in its applications due to its advanced data driven prediction capabilities. The study presents a data-driven approach as a preliminary attempt to predict the power at which departure from nucleate boiling (DNB) occurs in pressurized water reactors (PWRs) by constructing an advanced ML algorithm that takes outlet pressure, inlet temperature and inlet mass flux as the input features. DNB is a critical heat flux (CHF) phenomenon seen in PWRs. The experimental data from the PWR subchannel and bundle tests (PSBT) benchmark is first used to train an artificial neural network (ANN) to predict the DNB power, which produces a root mean square error (RMSE) of 6.89 kW/m when tested on a blind subset of the PSBT data. Since the PSBT dataset is relatively small to train an accurate ANN, a data augmentation methodology based on generative adversarial networks (GANs) is used to expand the training dataset. By assuming that the real data follows a certain distribution, GANs try to learn that underlying distribution to generate similar synthetic data to augment the database and to improve the predictive capabilities of the ANN. The data generated from GANs are validated using 1-nearest neighbor and kernel maximum mean discrepancy. To further ensure data from GAN is similar to PSBT, the data is tested and filtered out using the sub-channel thermal-hydraulic code CTF. The results indicate that with the addition of 120 data points from GAN the RMSE reduces to 4.84 kW/m showing promising results for future developments.