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NASA NTRS1990

Annual Research Briefs, 1989

This report contains the 1989 annual progress reports of the Research Fellows of the Center for Turbulence Research. It is intended as a year end report to NASA, Ames Research Center which supports this group through core funding and by making available physical and intellectual resources. The Center for Turbulence Research is devoted to the fundamental study of turbulent flows; its objectives are to simulate advances in the physical understanding of turbulence, in turbulence modeling and simulation, and in turbulence control. The reports appearing in the following pages are grouped in the general areas of modeling, experimental research, theory, simulation and numerical methods, and compressible and reacting flows.

Debra Spinks↗

DOE OSTI2015

Advanced Simulation and Computing Fiscal Year 2016 Implementation Plan, Version 0

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The purpose of this IP is to outline key work requirements to be performed and to control individual work activities within the scope of work. Contractors may not deviate from this plan without a revised WA or subsequent IP.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Advanced LIGO constraints on neutron star mergers and r-process sites

The role of compact binary mergers as the main production site of r-process elements is investigated by combining stellar abundances of Eu observed in the Milky Way, galactic chemical evolution (GCE) simulations, and binary population synthesis models, and gravitational wave measurements from Advanced LIGO. We compiled and reviewed seven recent GCE studies to extract the frequency of neutron star–neutron star (NS–NS) mergers that is needed in order to reproduce the observed [Eu/Fe] versus [Fe/H] relationship. We used our simple chemical evolution code to explore the impact of different analytical delay-time distribution functions for NS–NS mergers. We then combined our metallicity-dependent population synthesis models with our chemical evolution code to bring their predictions, for both NS–NS mergers and black hole–neutron star mergers, into a GCE context. Finally, we convolved our results with the cosmic star formation history to provide a direct comparison with current and upcoming Advanced LIGO measurements. When assuming that NS–NS mergers are the exclusive r-process sites, and that the ejected r-process mass per merger event is 0.01 M${}_{\odot }$, the number of NS–NS mergers needed in GCE studies is about 10 times larger than what is predicted by standard population synthesis models. Here, these two distinct fields can only be consistent with each other when assuming optimistic rates, massive NS–NS merger ejecta, and low Fe yields for massive stars. For now, population synthesis models and GCE simulations are in agreement with the current upper limit (O1) established by Advanced LIGO during their first run of observations. Upcoming measurements will provide an important constraint on the actual local NS–NS merger rate, will provide valuable insights on the plausibility of the GCE requirement, and will help to define whether or not compact binary mergers can be the dominant source of r-process elements in the universe.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Validation of material models for puncture of 7075-T651 aluminum plate

Plate puncture simulations are challenging computational tasks that require advanced material models including high strain rate and thermal-mechanical effects on both deformation and failure, plus finite element techniques capable of representing large deformations and material failure. The focus of this work is on the material issues, which require large sets of experiments, flexible material models and challenging calibration procedures. In this study, we consider the puncture of 12.7 mm thick, 7075-T651 aluminum alloy plates by a cylindrical punch with a hemispherical nose and diameter of 12.7 mm. The plasticity and ductile failure models were isotropic with calibration data obtained from uniaxial tension tests at different temperatures and strain rates plus quasi-static notched tension tests and shear-dominated tests described here. Sixteen puncture experiments were conducted to identify the threshold penetration energy, mode of puncture and punch acceleration during impact, The punch was mounted on a 139 kg mass and dropped on the plates with different impact speeds. Since the mass was the same in all tests, the quantity of interest was the impact speed. The axis and velocity of the punch were perpendicular to the plate surface. The mean threshold punch speed was 3.05 m/s, and the mode of failure was plugging by thermal-mechanical shear banding accompanied by scabbing fragments. Application of the material models in simulations of the tests yielded accurate estimates of the threshold puncture speed and of the mode of failure. Time histories of the punch acceleration compared well between simulation and test. Remarkably, the success of the simulations occurred in spite of even the smallest element used being larger than the width of the shear bands.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Deep Learning-based Surrogate Model for Efficient Reservoir Simulation in Large-scale Geological Carbon Storage: Application in IBDP Dataset

This project introduces an advanced deep learning (DL)-based surrogate modeling approach to enhance the efficiency and accuracy of large-scale geological carbon storage (GCS) simulations. Using the Illinois Basin Decatur Project (IBDP) dataset as training data, the study employs a residual U-Net architecture to predict critical state variables such as pressure and CO₂ saturation, as well as CO₂ plume migration. By incorporating key geological parameters (e.g., porosity, permeability, and rock facies) and physics-informed inputs like the diffusive time of flight and time step, the DL model effectively reduces computational complexity while maintaining robust physical constraints. Compared to traditional simulators like Eclipse, the DL model achieves remarkable accuracy, with a root mean square error (RMSE) of 1.57 psi for pressure and 0.007 for saturation, and dramatically reduces computational time from hours to just 69.9 seconds for 50-step simulations. These results demonstrate the potential of innovative DL methodologies to improve the predictivity and operational efficiency of GCS simulations, providing a reliable foundation for decision-making in CCS operations. Supported by the SMART initiative, this project underscores the success of leveraging computational innovations to advance CCS technologies.

advanced deep learning↗

DOE OSTI2024

Advanced Simulation and Computing: FY25 Implementation Plan

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

Advanced Models for Aeroelastic Analysis of Propulsion Systems

This report describes an integrated, multidisciplinary simulation capability for aeroelastic analysis and optimization of advanced propulsion systems. This research is intended to improve engine development, acquisition, and maintenance costs. One of the proposed simulations is aeroelasticity of blades, cowls, and struts in an ultra-high bypass fan. These ducted fans are expected to have significant performance, fuel, and noise improvements over existing engines. An interface program was written to use modal information from COBSTAN and NASTRAN blade models in aeroelastic analysis with a single rotation ducted fan aerodynamic code.

Keith, Theo G., Jr.↗

NASA NTRS1977

Rotor systems research aircraft simulation mathematical model

An analytical model developed for evaluating and verifying advanced rotor concepts is discussed. The model was used during in both open loop and real time man-in-the-loop simulation during the rotor systems research aircraft design. Future applications include: pilot training, preflight of test programs, and the evaluation of promising concepts before their implementation on the flight vehicle.

Houck, J. A.↗

DOE OSTI2022

SCALE Analysis of a Fluoride Salt-Cooled High-Temperature Reactor in Support of Severe Accident Analysis

As part of a US Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with SCALE and MELCOR, SCALE was used for the modeling and simulation of a fluoride salt-cooled high-temperature reactor (FHR). Based on the preconceptual design for a small modular 236 MWth FHR developed by the University of California, Berkeley (PB-FHR-Mk1), a SCALE model of the PB-FHR-Mk1 reactor core was developed. The reactor was modeled at equilibrium state with different fuel compositions in different regions of the reactor. An iterative approach was used to interpolate and mix the burnup-dependent fuel compositions obtained through the depletion calculation of a core slice model. After demonstrating the applicability of SCALE’s multigroup (MG) approach for the simulation of the PB-FHR-Mk1, the resulting equilibrium core was studied in terms of the power profile, the flux profile, temperature reactivity coefficients, and the xenon reactivity. Furthermore, the tritium production rate in the salt coolant was determined, and the dependence of the one-group cross sections on the burnup and location in the reactor core was studied. The results obtained with SCALE were post-processed to provide the MELCOR team with the core inventory and decay heat of the equilibrium core, a zone-wise power profile, temperature feedback coefficients, the tritium production rate, and the xenon worth.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Application of SCALE to Molten Salt Fueled Reactor Physics in Support of Severe Accident Analyses

As part of a US Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with SCALE and MELCOR, SCALE was used for the modeling and simulation of a molten salt-fueled reactor (MSR). SCALE capabilities for the modeling of MSR physics were demonstrated based on the Molten Salt Reactor Experiment (MSRE). Of primary interest were the determination of the system’s nuclide inventory, as well as the inventories in the various regions of the loop, considering that the fuel is continuously pumped through the system. This report contains discussions on the following: 1. Determination of the system-average fuel salt inventory considering fission gas removal in the off-gas system and noble metal removal through plating out at the heat exchanger using recent enhancements in SCALE’s depletion sequence TRITON, 2. Assessment of the nuclide spatial distribution throughout the loop using SCALE’s depletion solver ORIGEN, 3. Calculation of the core’s power profile, flux profile, temperature reactivity coefficients, and xenon reactivity using full-core calculations with SCALE’s Monte Carlo code KENO-VI. The results obtained with SCALE were post-processed to provide the MELCOR team with the core inventory and decay heat of the system, as well as the inventory and decay heat of individual regions in the loop, a zone-wise power profile, temperature feedback coefficients, and the xenon worth.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Advanced Simulation and Computing (FY22 Implementation Plan Rev 0)

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY22. The Initial IP, effective , should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2026

Modeling Radiolysis and Chemical Reactions during Dry Storage of Aluminum-clad Spent Nuclear Fuel

After aluminum-clad spent nuclear fuel (ASNF) is removed from the reactor, it is initially stored in spent fuel pools, which are specially designed water-filled basins that provide temporary cooling to reduce the temperature of the fuel assemblies and provide radiation shielding. ASNF continues to generate heat due to the radioactive decay of elements within the fuel, which persists for many years post-shutdown as the residual radioactive products decay into more stable elements. During the wet storage period, an oxyhydroxide layer composed of boehmite/bayerite forms on the surfaces of the aluminum cladding from exposure to water in the pools. Road-ready packaging for long-term disposition of the ASNF involves dry storage in helium backfilled DOE standard canisters (DSCs). When the ASNF is removed from water storage and dried, most of the water is removed, but some physisorbed and chemisorbed water remains in the oxyhydroxide layers. This residual water can produce hydrogen when exposed to radiation from the ASNF during dry storage. Predicting hydrogen accumulation over time in the DSCs is critical for long-term storage considerations. Previous modeling efforts have developed coupled computational fluid dynamics (CFD)-chemical models to simulate temperature, pressure, and gas phase concentrations within the DSCs. These models use the thermal field predicted by CFD as input to a radiolysis model for the gas phase and the surface oxyhydroxide layer chemistry. Given the long storage period of the DSCs and the impracticality of long-term experiments, a simulation-based approach is necessary to assess chemical evolution within the canisters. This study advances the development of a modeling framework designed to simulate the chemical evolution of spent fuel canisters. Both thermal and radiation-driven reactions are considered, with radiation kinetics quantified using G-values. Sensitivity analysis identifies key parameters influencing species composition. Reaction pathway diagrams offer insight into dominant species formation routes, enabling more effective comparisons between model predictions and experimental observations, particularly regarding the production of hydrogen. Results show that the model predicts significant hydrogen gas production with minimal oxygen generation, primarily due to hydrogen formation via boehmite pathways. These findings underscore the importance of accurately characterizing surface-bound species and radiolysis kinetics. A deeper understanding of these mechanisms is critical for evaluating the long-term safety of nuclear waste storage.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

NASA NTRSDate not supplied

Reducing Barriers in Space Weather Research and Operations with Next-Generation Simulation Services at the Community Coordinated Modeling Center (CCMC)

Space weather forecasting capabilities are becoming increasingly important to the health of advanced technological infrastructure. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) serves as a key liaison in the US space weather program between the research and operations communities by providing a wide range of tools and capabilities that help to evaluate, compare, exercise, and archive the results of simulations of a growing list of space weather models. With its unique toolset, CCMC supports space weather research and model development that advances our understanding of space weather phenomena and improves forecasting skill, while also facilitating development of space weather applications and deployment of operational capabilities. Guided by experience from over 20 years of providing simulation services, feedback from its research, operational and educational users world-wide, recommendations from CCMC Advisory Group and Programmatic Review Panel, the CCMC has begun work on the next generation system for its simulation services and model output archives. The new system has been envisioned to employ state-of-the-art technologies and standards to provide a user-oriented experience while improving ease of access, transparency, interoperability with partner systems, and enhancing reliability by incorporating advanced automation for performance monitoring and intelligent failover. In the presentation, we will give an overview of the current CCMC ecosystem and discuss updates to some of the key services of the system, including Runs-on-Request, Instant Runs, and Continuous Runs. We will also describe how a planned expansion and standardization of data archival activities will enhance the role of CCMC as a world-class provider of heliophysics information for the research and analysis of space weather. It is our hope that this evolution of the services can further reduce the barriers and burdens on researchers, forecasters and decision makers who rely on CCMC for their daily research and operations.

Space Weather↗

DOE OSTI2026

Scenario-based analysis of electric vehicle adoption in the United States: Technology, infrastructure, and electricity pricing

This work investigates the impact of battery technology advancement, charging infrastructure development, and time-of-use (TOU) electricity pricing on vehicle adoption by 6 powertrain types in the United States through 2050. Using the Market Acceptance of Advanced Automotive Technologies (MA3T) model, we simulate 15 scenarios, examining individual cost factors and their combinations. We assess outcomes through market share, consumer surplus, and energy consumption. Results show that battery cost reductions are the strongest driver of EV adoption, increasing 2050 battery electric vehicle (BEV) share by 27 percentage points over baseline, raising annual consumer surplus by $511 per household, and reducing cumulative energy consumption by 16,610 trillion Btu. These gains are two to five times larger than those from other individual factors. Reducing home charging installation costs produces moderate impact, while TOU pricing alone yields only small gains, raising 2050 BEV market share by 1–2 percentage points. However, when cost factor improvements are combined, their effects are amplified beyond simple additivity. Pairing modest battery cost reductions with charging installation cost reductions and TOU pricing results in the largest 2050 BEV sales combined impact. The analysis demonstrates that moderate progress targeting multiple cost barriers may be more impactful than focusing on any single barrier.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Rapid development of the X-31 simulation to support flight-testing

The X-31 Enhanced Fighter Maneuverability Program has been recognized to form the International Test Organization, with the NASA Dryden Flight Research Facility (NASA-Dryden) as the responsible test organization. The two X-31 research aircraft and engineering support personnel were colocated at NASA-Dryden, with flight test operations beginning in Apr. 1992. Therefore, rapid development of a hardware-in-the-loop simulation was needed to support the flight test operations at NASA-Dryden, and to perform verification and validation of flight control software. The X-31 simulation system requirements, distributed simulation system architecture, simulation components math models to the visual system, and the advanced capabilities the X-31 simulation provides. In addition, unique software tools and the methods used to rapidly develop this simulation system will be highlighted.

Mackall, Dale↗

NASA NTRS1992

Rapid development of the X-31 simulation to support flight-testing

Mackall, Dale↗