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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Comparison of experimental and simulated critical heat flux tests with various cladding alloys: Sensitivity of iron-chromium-aluminum (FeCrAl) to heat transfer coefficients and material properties

In this paper we analyze the differences between previous transient critical heat flux (CHF) experiments using iron-chromium-aluminum (FeCrAl), Inconel 600, and stainless steel 316 (SS316) alloy test sections and best-estimate modeling results from widely-used nuclear engineering systems and subchannel analysis tools. FeCrAl is an Accident Tolerant Fuel (ATF) candidate cladding material. The thermal hydraulic performance and safety characteristics of FeCrAl are being evaluated to determine viability as a cladding material in Light Water Reactors (LWRs). In this study, the results of the CHF experiments conducted at atmospheric pressure and fixed inlet coolant temperature and mass flux are compared to models built in the fifth version of the Reactor Excursion and Leak Analysis Program (RELAP5-3D) and CTF, the modernized version of COBRA-TF developed by the Consortium for Advanced Simulation of LWRs (CASL). Results from RELAP5-3D and CTF showed differences from the experiments and from each other in predicting CHF. In the Inconel 600 case, both computational tools overpredicted CHF, which led to an underprediction in the tube outer surface temperature. In the SS316 and FeCrAl cases, CHF was underpredicted by the codes, leading to an overprediction of the tube outer surface temperature. To understand the discrepancies in CHF and post-CHF predictions, studies were performed using RELAP5-3D and RAVEN to determine the sensitivity of CHF and peak test section temperature, an analog to peak cladding temperature (PCT), to heat transfer coefficients, a CHF multiplier, and uncertainties in the thermal conductivity and volumetric heat capacity. We found that CHF depends most strongly on the CHF multiplier and thermophysical properties. A combination of these factors that produced the best match to the experiment based on CHF, PCT, and the total energy deposited into the tube was determined. The best match parameters were able to provide best-estimate predictions of the CHF and integral heat flux, but were still conservative when predicting the PCT. The best match set of parameters developed in this paper are intended only as a demonstration of an approach that could be applied in the future with a larger set of experiments to produce more accurate models of CHF and post-CHF behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

RELAP5-3D validation studies based on the High Temperature Test facility

In the spring and summer of 2019, experiments were conducted at the High Temperature Test Facility (HTTF) that form the basis of an upcoming high-temperature gas-cooled reactor (HTGR) thermal hydraulics (T/H) benchmark. HTTF is an integral effects test facility for HTGR T/H modeling validation. This paper presents RELAP5-3D models of two of those experiments: PG-27, a pressurized conduction cooldown (PCC); and PG-29, a depressurized conduction cooldown (DCC). These models used the RELAP5-3D model of HTTF originally developed by Paul Bayless as a starting point. The sensitivity analysis and uncertainty quantification code, RAVEN was used to perform calibration studies for the steady-state portion of PG-27. Here we developed four PG-27 calibrations based on steady-state conditions. These calibrations all used an effective thermal conductivity equal to 36 % of the measured thermal conductivity, but they differed with respect to the frictional pressure drops and radial conduction models. These models all captured the trends in steady-state temperature distributions and transient temperature behavior well. All four calibrations show room for improvement in predicting the transient temperature rise. The smallest error in temperature rise during the transient was a 21 % underprediction, and the largest was a 48 % underprediction. The errors in transient temperature rise are largely a result of a mismatch in power density between the RELAP5-3D model and the experiment due to the location of active heater rods along the boundary between heat structures in the model. The best of these calibrations was applied to PG-29 to model the DCC. Once again, temperatures during the transient were underpredicted but trends in temperature were captured. The RELAP5-3D model captured trends in the data but could not reproduce measured temperatures exactly. This result is not attributed to deficiencies in the experimental data or to RELAP5–3D itself. Rather, this result likely arises due to the some of the assumptions and decisions made when the RELAP5-3D model was first developed, prior to the execution of HTTF experiments. An agreement in prediction of temperature trends but challenges reproducing HTTF temperatures within measurement uncertainty is consistent with previous analyses of HTTF in the literature. Future RELAP5-3D validation activities centered around HTTF may be able to provide greater insight into the code’s capabilities for HTGR modeling with a more finely nodalized model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated, where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Methods for automated genome-scale metabolic model reconstruction

In the era of next-generation sequencing and ubiquitous assembly and binning of metagenomes, new putative genome sequences are being produced from isolate and microbiome samples at ever-increasing rates. Genome-scale metabolic models have enormous utility for supporting the analysis and predictive characterization of these genomes based on sequence data. As a result, tools for rapid automated reconstruction of metabolic models are becoming critically important for supporting the analysis of new genome sequences. Many tools and algorithms have now emerged to support rapid model reconstruction and analysis. We are comparing and contrasting the capabilities and output of a variety of these tools, including ModelSEED, Raven Toolbox, PathwayTools, SuBliMinal Toolbox and merlin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Demonstration of the Advanced Dynamic System Modeling Tool TRANSFORM in a Molten Salt Reactor Application via a Model of the Molten Salt Demonstration Reactor

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. Here, this paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Sensitivity Analysis of Transient Critical Heat Flux by RIA Under High-Pressure Flow Boiling Conditions in TRTL

A reactivity-initiated accident (RIA) is a design-basis accident under which critical heat flux (CHF) is likely to be exceeded. The operational margin for RIAs is currently determined using steady-state CHF lookup tables, which provide conservative estimates relative to transient CHF phenomena. The Transient Reactor Test Loop (TRTL) facility at Oregon State University is capable of performing out-of-pile rapid heating experiments representative of a RIA at conditions representative of a pressurized water reactor (PWR). Here, to further our understanding of and ability to predict transient CHF under PWR conditions, we performed a sensitivity analysis on a RELAP5-3D model of the TRTL facility coupled to the RAVEN code framework to define a proposed experimental test matrix to be performed at the TRTL facility. We then implemented a flow boiling CHF correlation into RELAP5-3D and performed a secondary sensitivity analysis inspecting the impact of the built-in RELAP5-3D CHF and heat transfer multipliers on both the prediction of CHF and key safety parameters, such as peak cladding temperature and heat flux. The results show that the multiplier with the highest influence toward the prediction of CHF occurrence and the safety parameters is the transient CHF multiplier. Operational performance envelopes have been developed for each of the test matrix cases and will be used for validation once the experiments are performed. The TRTL facility is currently performing shakedown testing to verify system performance prior to proceeding with the experimental campaign. Restart testing results include pump curve restart testing, pressure tests, and heater rod thermocouple transients.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Risk-Informed Safety Analysis for Accident Tolerant Fuels

Accident Tolerant Fuels (ATF) are being tested by different nuclear vendors and research organizations and their introduction in the US light water reactors fleet is planned for the second half of the 2020`s. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Systems Analysis pathway, researches are being conducted at the Idaho National Laboratory for developing tools and methods that can help the industry quantifying the benefits from the adoption of ATF technology. In this paper we describe the developed risk-informed methodology including the safety analysis codes improvements, and we present some results for selected accident scenarios. The developed methodology combines INL state-of-the-art deterministic Best Estimate code RELAP5-3D, and Probabilistic Risk Analysis tools RAVEN and SAPHIRE. The analyses are performed on a three-loops pressurized water reactor, simulating Station Blackout and LB-LOCA accidents and considering near-term ATFs, or FeCrAl and Chromium-coated clads. Finally, we show how, applying our methodology, the new Core Damage Frequency can be assessed. The results indicated that the main benefits in introducing near-term ATFs concern a significant reduction in the hydrogen production during accident conditions. No significant Core Damage Frequency reduction was found.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

TRISO SiC Failure Probability for Reactivity Initiated Accidents in High-Temperature Gas-Cooled Reactors

This work analyzes the failure process of the silicon carbide (SiC) layer in tristructural isotropic (TRISO) during reactivity-initiated accident scenarios for a high-temperature gas-cooled reactor (HTGR) with BISON. Two cases are considered—a group control rod withdrawal (CRW) and a control rod ejection (CRE)—reproduced from a previous study. Failure probability is modeled using Weibull statistics, and worst-case scenario Weibull parameters are adopted to simulate the envelopes in BISON with a one-dimensional TRISO model. CRW scenario results are characterized by higher values of maximum energy deposition and final temperature and volumetric strain with respect to the CRE ones, but the latter have remarkably higher SiC failure probability, mainly due to the offset in strain rates between the two cases. This work also confirms the validity and conservatism of the performance envelopes produced in a previous work by replicating the envelope formulation using RELAP5-3D and RAVEN with a different sampling technique and obtaining consistent results. A sensitivity analysis using the Sobol variance decomposition method on SiC failure probability is then performed involving a set of inputs on both CRW and CRE. The two most important parameters are Weibull modulus and characteristic stress, and their relative importance depends on the specific case. The proposed interpretation of the results is that both energy deposition and strain rate influence the relative degree of importance of the failure parameters. Computation of 95% confidence intervals around worst-case scenario SiC failure probability values is also carried out for four different sets of Weibull parameters. Heren a new criterion for SiC TRISO quality classification built upon safety-based ranges of Weibull parameters is proposed to be integrated in future Fuel-Production Quality Assurance Plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Rethinking Sensitivity Analysis of Nuclear Simulations with Topology

In nuclear engineering, understanding the safety margins of the nuclear reactor via simulations is arguably of paramount importance in predicting and preventing nuclear accidents. It is therefore crucial to perform sensitivity analysis to understand how changes in the model inputs affect the outputs. Modern nuclear simulation tools rely on numerical representations of the sensitivity information -- inherently lacking in visual encodings -- offering limited effectiveness in communicating and exploring the generated data. In this paper, we design a framework for sensitivity analysis and visualization of multidimensional nuclear simulation data using partition-based, topology-inspired regression models and report on its efficacy. We rely on the established Morse-Smale regression technique, which allows us to partition the domain into monotonic regions where easily interpretable linear models can be used to assess the influence of inputs on the output variability. The underlying computation is augmented with an intuitive and interactive visual design to effectively communicate sensitivity information to the nuclear scientists. Our framework is being deployed into the multi-purpose probabilistic risk assessment and uncertainty quantification framework RAVEN (Reactor Analysis and Virtual Control Environment). We evaluate our framework using an simulation dataset studying nuclear fuel performance.

computational topology↗
DOE OSTI2016

SU-F-T-232: Monthly Quality Assurance in External Beam Radiation Therapy Using a Single System

Purpose: Monthly quality assurance (QA) is time consuming for external beam radiation therapy, taking as long as 6–8 hours for each machine. It is due to the use and setup of multiple devices for different QA procedures. We have developed a single system with rotational capability for the measurement of both optical light and radiation which significantly reduces the time spent on Monthly QA. Methods: A single system using mirrors, a phosphor screen and a CCD camera is housed on a cylindrical motor so that it can rotate 360 degrees. For monthly QA, the system is placed on the patient couch of the medical accelerator with the plane of the phosphor screen at isocenter for all measurements. For optical QA such as optical distance indicator, room laser and light field, the optical image is collected directly with the camera. For radiation QA such as beam profile, MLC speed, picket-fence test, collimator rotation, table rotation and gantry rotation, a brass build-up plate is attached to the top of the phosphor screen. Two brass plates with islands of different thickness were designed for photon energy and electron energy constancy checks. Flex map, distortion map and uniformity map were developed to calibrate the motor bearing, camera/lens distortion, and the phosphor screen’s measured response across the field. Results: Following the TG142 guidelines for monthly QA with our system, the overall run time is reduced from 6–8 hours to 1.5 hours. Our system’s rotating design allows for quick testing of the gantry radiation isocenter test that is also independent of the sag of the gantry and the EPID. Conclusion: Our system significantly shortens the time needed for monthly QA by unifying the tests with a single system. Future work will be focused on extending the technology to Brachytherapy, IMRT and proton therapy QAs. This work is funded in part by a sponsor research grant from JPLC who owns the Raven technology. John Wong is a co-founder of JPLC.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

LOGOS

LOGOS is a software package which contains a set of discrete optimization models that can be employed for capital budgeting optimization problems. More specifically, provided a set of items (characterized by cost and reward values) and constraints, these models select the best combination of items which maximizes overall reward and satisfies the provided constraints. The developed models are based on different versions of the knapsack optimization algorithms. Two main classes of optimization models have been initially developed: deterministic and stochastic. Stochastic optimization models evolve deterministic models by explicitly considering data uncertainties (associated to constraints or item cost and reward). These models can be employed as stand-alone models or interfaced with the INL developed RAVEN code to propagate data uncertainties and analyze the generated data (i.e., sensitivity analysis).

Wang, Congjian↗
DOE OSTI2023

Optimization Of Real-time Capacity Allocation

ORCA is a modeling toolset to accelerate real-time control and optimization of digital twins, including virtual models of facilities, physical facilities, and interconnections to allow optimal control of physical facilities using virtual models. ORCA is enabled by INL's RAVEN and DeepLynx software codes.

Talbot, Paul [Idaho National Laboratory] (00000002↗
DOE OSTI2024

lanl-ansi/MG-RAVENS

The MG-RAVENS project with the DOE Office of Electricity Microgrid R&D Program is a project to develop a completely free, open-source data exchange standard (API) for the Department of Energy, targeted at software tools related to infrastructure modeling, particularly the modeling of microgrids and electric power distribution systems that are created with funding from the Microgrid R&D Program. This software produces formal definitions of an API, documentation, contains supporting functions for parsing, validating, etc., and will contain examples of workflows enabled by the developed API.

Fobes, David M↗
DOE OSTI2025

Plant Reload Optimization (prlo)

The PRLO framework is built on a modular and extensible architecture that tightly couples advanced evolutionary optimization algorithms with nuclear fuel depletion solvers (i.e., nuclear physics neutronics code). It supports exploring complex, high-dimensional design spaces constrained by user-specified operational, safety, and economic constraints. Objectives such as minimizing fresh fuel enrichment, flattening radial and axial power distributions, and maximizing discharge burnup are evaluated. PRLO’s equilibrium cycle optimization capability enables the identification of core configurations that maintain fuel cycle sustainability over extended planning horizons. Its integration with the RAVEN platform facilitates optimization of loading patterns or fuel shuffling schemes across multiple cycles. The interface with SIMULATE, a licensed industry-standard nodal code developed by Studsvik, ensures accurate neutronic and thermal-hydraulic feedback for reactor core design. PRLO’s automated workflow engine supports iterative design refinement, enabling utilities to streamline core design processes and meet evolving performance and regulatory targets.

Kim, Junyung [Idaho National Laboratory] (00090005↗
DOE OSTI2012

Science Campaign-1 Pulsed Power Efforts [Slides]

The PHELIX portable pulsed-power driver is discussed. It is composed of two air-insulated, single Marx modules capable of storing 300 kJ of electrical energy. The Marx are cable coupled to a toroidal transformer with a 4:1 winding ratio. The experimental load is located at the center of the transformer. The components are mounted in a 8’x10’x18’ boxcar which can be moved in and out of the beam line at the LANL proton radiography facility and prevents EMI within the facility. PHELIX has successfully completed two liner implosion experiments with full diagnostic return from flash X-ray imaging, optical Faraday load current, and multi-channel PDV. Computational modeling with both the legacy 1D MHD code RAVEN and the LANL ASC-LAP FLAG code show good agreement with data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

MOOSE Enhancements Towards Delivery of an Integrated Framework

Started in 2008, the Mulitphysics Object Oriented Simulation Environment (MOOSE) project delivers a comprehensive framework for development of parallel, multiphysics simulation tools. MOOSE provides an object-oriented interface that allows scientists and engineers to quickly and efficiently describe all aspects of a physical system relevant to numerical modeling. The MOOSE software development strategy has been quite successful: over thirty different MOOSE-based applications are under development both internally and outside the DOE complex, and over forty different external institutions have licensed MOOSE. Several NEAMS products have been built using MOOSE, including BISON (Williamson et. al., 2012), MARMOT (Tonks et. al., 2012), RELAP-7 (Zou et. al., 2013) and RAVEN (Rabiti, 2013).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

RELAP-7 Simulation Resolving an SBO Scenario on a Simplified Geometry of a BWR

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 will become the main reactor systems toolkit for the Risk-Informed Safety Margin Characterization Pathway of the Light Water Reactor Sustainability Program and the next generation tool in the RELAP reactor safety/systems analysis application series (i.e., the replacement for RELAP5). The code is being developed based on Idaho National Laboratory’s modern scientific software development framework – MOOSE (the Multi-Physics Object-Oriented Simulation Environment). During Fiscal Year 2013, a number of physical components with two-phase flow capability have been developed to support the simplified boiling water reactor (BWR) station blackout analyses. The case selected for demonstration calculation is built from the specifications documented in an Organization for Economic Cooperation and Development benchmark problem for BWR turbine trip analysis. The reference design for the benchmark problem was from the Peach Bottom-2 nuclear station, which is a General Electric BWR-4 design. The demonstration case includes the major components for the primary system of a BWR, as well as the safety system components for reactor core isolation cooling (RCIC) and the wet well of a BWR containment. The case was initially run to steady-state with RELAP-7. The station blackout transient simulations were subsequently initiated by using the INL-developed RAVEN code. Two scenarios for the station blackout simulations have been considered. Scenario I represents an extreme station blackout accident with no safety injection functioning. The reactor core could experience dry out fairly quickly with this scenario. Scenario II represents a more probable station blackout accident progression with the RCIC system functioning. In this scenario, the RCIC system is fully coupled with the reactor primary system and the safety injection to provide makeup cooling water to the reactor core from the suppression pool is dynamically simulated. With the RCIC system functioning, the core dry out is significantly postponed when compared to the results from Scenario I. This fully coupled RCIC system simulation capability represents the first-of-a-kind simulation capability. Sensitivity studies have also been carried out to study the effect of RCIC control strategy with varying core makeup cooling water mass flow rates. The next stage of development will be to demonstrate more refined BWR station blackout analyses with more realistic geometries, to be reported in the next demonstration simulation report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Effects of Transcranial Direct Current Stimulation (tDCS) on Human Memory.

Training a person in a new knowledge base or skill set is extremely time consuming and costly, particularly in highly specialized domains such as the military and the intelligence community. Recent research in cognitive neuroscience has suggested that a technique called transcranial direct current stimulation (tDCS) has the potential to revolutionize training by enabling learners to acquire new skills faster, more efficiently, and more robustly (Bullard et al., 2011). In this project, we tested the effects of tDCS on two types of memory performance that are critical for learning new skills: associative memory and working memory. Associative memory is memory for the relationship between two items or events. It forms the foundation of all episodic memories, so enhancing associative memory could provide substantial benefits to the speed and robustness of learning new information. We tested the effects of tDCS on associative memory, using a real-world associative memory task: remembering the links between faces and names. Working memory refers to the amount of information that can be held in mind and processed at one time, and it forms the basis for all higher-level cognitive processing. We investigated the degree of transfer between various working memory tasks (the N-back task as a measure of verbal working memory, the rotation-span task as a measure of visuospatial working memory, and Raven's progressive matrices as a measure of fluid intelligence) in order to determine if tDCS-induced facilitation of performance is task-specific or general.

Matzen, Laura E.↗