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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Liquid and Gamma-BCC Phase Equilibria in the Uranium-Niobium System: A Simple Thermodynamic Model for Phase Diagram and Other Predictions

A simple thermodynamic model for the uranium-niobium (U-Nb) system was created using a Calphad-type approach, circa 2002. Only the liquid and gamma-BCC phases were modeled, with their subregular solution mixing terms optimized by trial and error. The custom (user-defined) database file (.tdb) and experimental data file (.exp) are listed, both of which are compatible with Thermo-Calc software. This model is used to calculate the solidus, liquidus, miscibility gap on the U-Nb phase diagram and also the enthalpy of melting in the U-6Nb alloy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Laboratory Directed Research and Development Program Activities (LDRD 2021 Annual Report)

Each year, Brookhaven National Laboratory (BNL) is required to provide a report of its completed Laboratory Directed Research and Development Program (LDRD) projects to the Department of Energy (DOE) Office of Scientific and Technical Information in accordance with DOE Order 413.2C Chg1 (MinChg) dated August 2, 2018. This report provides a detailed look at the scientific and technical activities for each of the LDRD projects funded by BNL in FY 2021, in fulfillment of that requirement. In FY 2021, the BNL LDRD Program funded 68 projects, 24 of which were new starts, at a total cost of $17.1M. The investments that BNL makes in its LDRD program support the Laboratory’s strategic goals. BNL has identified six scientific initiatives that define the Laboratory’s scientific future and that will enable it to realize its overall vision. This requires simultaneous excellence in all aspects of BNL’s work – from science and operations, to external partnerships with the local, state, and national communities, and beyond. This is enabled by safe, efficient, and secure operations; by an unwavering commitment to a diverse, equitable, and inclusive environment, including workforce development, both with staff and reaching out to the community; and by a strong focus on renewed infrastructure. The six scientific initiatives are: (1) Nuclear Physics: The Electron Ion Collider, (2) Clean Energy and Climate, (3) Quantum Information Science and Technology, (4) Discovery Science Driven by the Human-AI-Facility Integration, (5) High Energy Physics: Building for Discovery, and (6) Accelerating Isotope Production: Ensuring the Nation’s Supply is Secure. The funded projects support BNL’s six scientific initiatives and priority programs as well as new areas of research and competencies at the Laboratory that are consistent with the Laboratory’s vision and mission. In total, these LDRD investments supported 80 postdoctoral researchers and graduate students in whole or in part and resulted in 136 publications and 3 awards. This Program Activities Report represents the future of BNL science; it is an impressive body of exploratory work that investigates many scientific and technical directions in support of the DOE and BNL missions.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Performance Analysis of the Expected Track Length Estimator

This work investigates whether performance of the MCNP code is improved by the implementation of the expected track length estimator. The expected track length estimator is known to decrease variance when compared to the track length estimator in many classes of Monte Carlo particle transport simulations. However, the computational cost of computing an exponent for every particle collision within a tallied cell has previously been considered prohibitively expensive. Therefore, the goal of this work is to determine whether the variance improvements seen by the expected track length estimator in most cases makes up for the increase in transport time when implemented in the MCNP code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Efficient Data Query for Gaussian Process Compressed Data through Value Range Estimation [Slides]

When the resolution of the data increases, data reduction methods are applied to simulation output, including Gaussian process, neural representation and compression algorithms. Lots of data analysis/visualization techniques requires data query, but data query from reduced representation is still challenging. This report will provide examples and provide possible answers to why data query from reduced representation is still challenging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Automating neutron resonances classification with Machine Learning [Slides]

Team reported the following accomplishments: the development of a Machine-Learning method to properly assign spins to neutron resonances (automated, general, reproducible); full integration with evaluated resonances in the Atlas (automation of new editions); training and optimization in synthetic data; validation and deployment to real experimental resonances. Future perspectives include exploration of other classifiers and hyper-parameter combinations, further validation with well-known nucleus (e.g. 235 U), and publication pipeline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

NJOY work in FY21 [Slides]

LANL lists several NJOY priorities for the future, including the maintenance of NJOY2016 for the foreseeable future, as well as the delivery of usable NJOY21 components.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Verification of Revised and Upcoming Nuclear Data Sensitivity MCNP Features [Poster]

Nuclear data is ubiquitous across nuclear applications. Improved nuclear data means more accurate simulations. Past focus on k eff caused compensating error and areas of unvalidated nuclear data. Sensitivity can be used to optimize experiments to focus on specific areas. Sensitivity capabilities must be expanded and improved to design multivariate experiments focused on nuclear data needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

EUCLID: Experiments Underpinned by Computational Learning for Improvements in Nuclear Data [Slides]

EUCLID will design validation experiments optimized to resolve compensating errors and adjust nuclear data to experiments. A big part of the success of the EUCLID proposal was due to previous work supported by NCSP (MCNP, nuclear data, and NCERC capabilities). The work performed under EUCLID will similarly benefit the NCSP mission. It will lead to new MCNP capabilities, improved nuclear data and nuclear data capabilities, and new methodology and tools that will have large impact on future NCERC experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear Data Adjustment with Whisper for Criticality Safety Applications [Slides]

Nuclear data adjustment is used by Whisper to compute residual nuclear data uncertainties within a full suite of benchmarks; in order to do so, a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications) is required. For applications that are similar to the full benchmark suite, the residual uncertainties add a small margin to the overall USL calculation. For applications that are dissimilar to the full benchmark suite, the residual uncertainties add a reasonable margin to the overall USL calculation (more conservative). This methodology helps to overcome any issues in the released covariance libraries where nuclear data uncertainties appear to be too large.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Investigating Fission Reaction Rate Ratio Sensitivities [Slides]

One EUCLID project goal is to create a NEW capability in the MCNP6 code. This is being tested on reaction rate sensitivities and compared with SENSMG results. Reaction rate ratio sensitivities were added to EUCLID sensitivity library and investigated to determine value toward designing optimized experiments aimed at reducing compensating errors in nuclear data. The use of adjustment using multiple responses (and underlying/required capabilities) may benefit many applications. These include a tool for adjustment using multiple integral responses (ND adjustment and validation community); sensitivities of additional responses (ND adjustment and validation community); sensitivity capabilities (users in many application areas including safeguards/nonproliferation, criticality safety, etc.); and experiment optimization capability (applications which can benefit from integral experiments). Team is working to build and test future tools and to understand compensating errors

235U↗
DOE OSTI2022

Verification of MCNP Critical Benchmark Model of U233-COMP-THERM-004 [Slides]

The verification of U233-COMP-THERM-004 contributed to the LANL centralized repository that’s currently under development. Revisions made to the MCNP model were statistically significant. Magnitude of bias is relatively small in comparison to other uranium benchmark biases and thus will likely have not a significant effect on the USL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Deterministic and Monte Carlo Nuclear Data Adjustment Methods [Slides]

For the Bayesian Monte Carlo methodology, a need to understand convergence of the posterior moments as a function of the number of parameter realizations is required. In high-dimensional systems, it can be very costly to sample entire parameter space and perform functional evaluation for every realization. Bayesian Monte Carlo allows one to relax the GLLS approximations of model linearity and prior/posterior PDF shape. The Bayesian Stochastic Collocation Method is a deterministic approach to “sample” the parameter space. It allows one to relax the GLLS approximations of model linearity and posterior PDF shape. Higher-order posterior moments (i.e., skewness, kurtosis, etc.) can be studied through polynomial expansion. Tensor product quadrature scales poorly and can use sparse grid quadrature methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Benchmark Evaluation of one Dimensional Array of HEU Moderated and Reflected by Lucite [Poster]

Two critical experiments with HEU-Lucite were performed using the Planet Universal Critical Assembly Machine at Los Alamos National Laboratory in 2019. HEU foils were interleaved with Lucite in a column stack for moderation and reflection from the square Lucite plates. The evaluation of the experiments is presented. A Monte-Carlo (MCNP6) calculation model was developed for the determination of uncertainties and their effect on the multiplication factor. Experimental uncertainties were found to be low with the overall uncertainty in k eff approximately 240 pcm. The comparison of calculations with experimental data is presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Comparative Critical Mass Calculations for NNL and ENDF/B-VIII.0 Zirconium Hydride Thermal Scattering Laws [Slides]

Zirconium Hydride (ZrH x ) is a moderator material for TRIGA reactors and SNAP-10A.The thermal scattering has the behavior of quantum oscillator favorable for moderator feedback. ZrH x occurs as a corrosion product in LWR. Previously new phase specific TSL evaluations were generated and submitted to ENDF/B- VIII.1. These include the effects of crystal structure on elastic scattering of Zr(ZrH x ), permit flexibility in stoichiometry for use in reactor physics calculations and fuel characterization, and expand the TSL material sub-library. ENDF/B-VIII.0 ZrH TSLs do not distinguish between material phase. Current work involves preliminary validation & verification testing on the effect of TSLs on critical mass and associated thermal flux.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗