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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Resonance Parameter Evaluation of n + 88 Sr reactions for ENDF/B-VIII.1 Library

An evaluation of n+ 88 Sr reactions up to 950 keV was compiled from a publicly available set of resonance parameters. Starting from the repository of the ENDF/B-VIII.0 library, an evaluated nuclear data file was assembled and submitted for inclusion to the Evaluated Nuclear Data File (ENDF)/B-VIII.1 release. This evaluation features an external function representation defined by pole strengths and R ∞ parameters over the entire resolved resonance range. This work improves the modeling of the R-matrix parameterization from multi-Level Breit-Wigner resonance parameters to Reich-Moore formalism, and it also extends thrice the upper energy range of the current ENDF/B-VIII.0 resolved resonance evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Evaluated Nuclear Data Requirements in Support of Fission and Fusion Applications [Slides]

This presentation touches on thermal scattering cross section and scattering lengths including criticality benchmarks (fission). Secondly, development and completeness of charged ­particle libraries: criticality benchmarks (fission), neutron source (fission/fusion), simulation benchmarks and light elements generation (fusion). Additionally, this presentation details on the covariances (methodology and completeness) with adjustment and optimization of nuclear data libraries (fission/fusion). Finally nuclear data reproducibility and conclusions are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Advancements in Validation of TSLs through Inelastic Neutron Scattering and Transmission Measurements [Slides]

This presentation finds that INS measurements are not as variable based on sample composition, because phonon spectra is a properly of the bulk material. Additionally, INS and transmission measurements are and should be the most significant part of TSL validation, as they are the fundamental quantities used by Monte Carlo neutronics codes. Relaying solely on theoretical atomistic calculations for TSL evaluation is not enough, they are highly dependent on inter-atomic potentials (which are not the most accurate depending on the quantity trying to be reproduced) and evaluators knowledge and understanding of the material being studied. When dealing with Crit. benchmarks - While extremely useful for validation of nuclear data at all energies, critical benchmarks are not the best tool to provide a definitive answer on conflicting TSLs. Finally, INS and transmission measurements need to be the basis of validation of TSLs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

(U) Correlated Sampling Using Batch Statistics to Reduce the Uncertainty of Combinations of KSEN Outputs with MCNP6

The relative sensitivity of k eff to the densities of nuclides in a material are combined to compute relative sensitivities to other inputs. When computed in a single Monte Carlo run, the nuclide density sensitivities are correlated, and the statistical uncertainties propagated to other inputs will be incorrect unless those correlations are accounted for. Equations are presented to apply correlated sampling using batch statistics for the sum of an arbitrary number of random tallies and the difference of two random tallies when each is multiplied by a different constant. When correlated sampling is used on a recent benchmark evaluation, the correct statistical uncertainties for certain combinations of sensitivities are dramatically smaller than the incorrect uncertainties. A user-controlled, regular output of MCNP6’s KSEN sensitivities that allows batch statistics to be applied to combinations would be extremely valuable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

High-Performance Electron Sources: Numerical Methods and Beam Dynamics at the Precision Frontier

Electron sources have a wide range of applications and there are many stakeholders that express continuing need for improvements and performance enhancements. Whether we consider ultra-cold, high-brightness, high-charge or high-average current source needs, there are some common themes from the point of view of the beam dynamics involved. These are the following ones: ability to model accurately the emission processes, including the presence of often complicated cathode and other boundary surfaces with a wide range of spatial scales; ability to deal accurately and efficiently with a large number of particles interacting pair-wise, including the stochastic part of these interactions with a wide range of spatial scales; and ability to propagate the particle distributions in time, including collisions with a wide range of temporal scales. These tasks require high precision and accuracy since the goal is usually generation, transport and preservation of very high-quality beams. This grant addressed one of the rem

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

(U) A Tool to Set Up an MCNP6 Input to Use Correlated Sampling with Batch Statistics

Correlated sampling using batch statistics with MCNP6’s tally fluctuation charts (TFCs) is a powerful means of reducing the statistical uncertainties of various combinations of tallies. Because MCNP6 prints a maximum of 20 entries in the TFCs, at least five inputs must be run to obtain the recommended number of at least 100 batches. A new software tool, MAKE_COSUBS, reads an MCNP6 input file and sets up a sequence of input files to be run. The user runs MAKE_COSUBS for the unperturbed and all perturbed MCNP6 inputs, runs MCNP6 for the inputs, and finally analyzes the outputs using COSUBS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A Family of Multi-Dimensional Thermal Radiative Transfer Test Problems

Many thermal radiative transfer (TRT) test problems have been introduced over the years. Here, we will combine the good features of several tests into one new problem. Our goals are to have a multi-dimensional, multi-group TRT problem that stresses the physics and numerics of codes in a realistic way, but the geometry and materials are idealized just enough to be simple to set up in any code. The proposed problem has no connection to any physical experiment; it is simply meant to have a combination of properties that stress the solvers with both the optically thick and thin limits. To achieve this, we are willing to give up any form of analytic solution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Celeritas R&D Report: Accelerating Geant4

Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a Graphics Processing Unit (GPU)-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.4, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling straightforward integration of Celeritas into the high energy physics (HEP) experimental frameworks CMSSW and ATLAS FullSimLight. On the Perlmutter supercomputer, Celeritas performs EM physics between 3× and 18× faster using the machine’s Nvidia GPUs compared to using only CPUs, corresponding to an electrical power efficiency up to a factor of 5. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.7–2.2× on GPU and 1.2× on CPU. In a CMS test application using tt¯ events and the prototype Run 4 configuration, compared to Geant4 CPU, Celeritas with a Nvidia A100 improves overall throughput up to a factor of 2.7× but cannot be efficiently shared with more than 8 cores.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Deep Neural Network Informed Markov Chain Monte Carlo Methods

In subsurface flow modeling, quantifying the uncertainty of model parameters and the corresponding uncertainly on output quantities is a crucial task for groundwater management. Markov chain Monte Carlo (MCMC) methods can take advantage of observed data to estimate parameters in a Bayesian setting. However, MCMC can be slow to converge and produce highly correlated samples when the dimensions of the parameters is high. Using gradients for the posterior distribution can help samplers explore the parameter space more efficiently, but obtaining gradients can be computationally challenging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

The Release of the Simplified Radionuclide Transport (SRT) Code (V.2.1)

Reactor licensing centers on the protection of the public and environment from the inadvertent release of radioactive material. Therefore, mechanistic source term analysis, or the realistic evaluation of radionuclide transport from the source to the environment for specific transient scenarios, is vital to reactor licensing efforts. Developed to resolve a gap in mechanistic source term modeling capabilities for sodium fast reactors (SFRs), the Simplified Radionuclide Transport (SRT) code created by Argonne National Laboratory (Argonne) is now utilized by advanced reactor vendors, universities, and research institutions to support a multitude of design, licensing, and research efforts. Recently, SRT version 2.1 was released, which includes improvements to code models and verification and validation (V&V) suite to support the SRT user community. The following work provides an overview of the improvements made as part of the release of SRT version 2.1. This effort is supported by the U.S. Department of Energy Office of Nuclear Energy (DOE:NE) Advanced Reactor Technologies (ART) Fast Reactor Program (FRP), as part of the program’s support of national laboratory design and safety analysis computer codes utilized by the fast reactor industry. The expansion of SRT code capabilities and improvements to code V&V associated with version 2.1 are in response to user requests and lessons learned from recent source term analyses performed by Argonne and advanced reactor vendors. They also align with the evolving role of SRT, from research and development tool to software utilized for reactor licensing calculations. The report is structured in alignment with the code improvements, as outlined in Figure 1-1. Section 2 provides background information on SRT, including its history, capabilities, and utilization. Section 3 details new code capabilities as part of version 2.1, while Section 4 focuses on the expansion of the code’s V&V suite. Lastly, Section 5 provides a summary and discussion of next steps.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

DUNE Data Management: Network Visualization Monitoring Software

Fermilab’s fagship Deep Underground Neutrino Experiment (DUNE) seeks to better understand the nature of neutrinos within the context of Leptogenesis, neutrino oscillations, multi-messenger Astronomy, and other scientifc phenomena. The experiment will send a beam of neutrinos from the Fermilab site in Illinois to the Sanford Underground Neutrino Facility (SURF) in South Dakota, generating petabytes of scientifc data. Given the high volume of data expected when measurements begin at the end of the decade, DUNE computing and the data management group must carefully monitor data transfers across the 15 remote storage sites and, more generally, the 36 global DUNE computing sites. This report will describe both the frontend and backend data monitoring software designed to analyze and visualize these data transfers. Specifc emphasis will be placed on the software’s setup, usage, and methods for future implementations. The full software code can be found under the DUNE/data-mgmt-testing GitHub repository.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

GEOMWRITER - A Workflow for Automatically Generating MCNP Geometry for Neutron Guide Simulations

This report describes the functionality of the geomwriter.py script, which is a python script for producing complex MCNP CSG geometries from the IGES CAD format. It is specifically written to handle neutron supermirror guides, but can handle more complex objects through utilizing a convex hull algorithm. This work flow reduces the amount of time spent on generating the surface definitions for a complex neutron guide system with hundreds of segments such that changes to the neutron guide system design in McStas can be rapidly incorporated into an MCNP model and integrated with the shielding geometry present in that model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗
DOE OSTI2024

Machine Learning Enabled Atomistic Study of the Micro-Cold Spray Process [Poster]

Micro-cold spray is typically conducted by impacting 200-2000 nm particles at velocities of ~500 m/s. Molecular dynamics simulations have been used to study micro cold spray, but the particles that can be simulated using conventional potentials are much smaller than those used experimentally. The viewgraphs taken from molecular dynamics simulations and shown below are cross-sections of a 50 nm Ta particle with a 3 nm oxide layer impacting at 500 m/s using a machine learning enabled DeePMD potential. Using more expensive reactive interatomic potentials, the previous largest particle size for a metal/oxide impact simulation was 12 nm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum-Hardware Focused Application Performance Benchmarks (Final Technical Report)

Quantum computers promise to transform how we do scientific calculations. In this project, we benchmark different current quantum computers for solving chemistry problems and find ways to build noise-resilient implementations. We also use the characterization techniques developed to test ion trap quantum computers.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Feasibility of Hybrid Electro- and Acousto-Dynamical Systems for Quantum Optical Networks

We present results on an exploratory research program that aims to study the feasibility of novel, sustained, dense, and efficient quantum information generation, storage, retrieval, relay and distribution devices and systems towards future advanced quantum networking architectures. The pathfinder program is anchored on original ideas and device conceptual designs that turn the phononic-sourced challenges into an opportunity towards optimized transduction chains over a broad range of length and energy/temperature scales. The proposal involves conceptual design and feasibility towards integration, commissioning and benchmarking of challenging transduction devices in a scaled quantum network setup.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗