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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Utility of Big Area Additive Manufacturing for Part Production for Low-Head Hydropower (CRADA NFE-18-07280 Final Report)

ORNL worked with Cadens, LLC, to explore the use of additive manufacturing (AM) to produce low-cost parts for low-head hydropower systems. Cadens develops design optimization software that leverages the flexible, low-cost, high-strength benefits of AM and composite materials. Cadens also operates a micro-hydro lab to test AM components in controlled environments. Until now, Cadens’ tests have been limited to components of a size that they can cost-effectively manufacture using local commercial systems. This project provided an opportunity for Cadens to scale up their modular AM hydropower parts using the capabilities of Big Area Additive Manufacturing (BAAM). This project was a success and resulted in the design and fabrication of several end-use parts of a hydropower system, using a Big Area Additive Manufacturing (BAAM) system. The fabricated parts include a draft tube, thimble, runner housing mold, PVC end fitting and two PVC pipe supports. In addition, a runner system was fabricated using fused deposition modeling on a 3D Platform Workbench 400 Series System.

13 HYDRO ENERGY↗
DOE OSTI2021

IC reports (2021)

We requested HPC support to continue research on the seismic waves generated by impacts. We used the following codes: (1) the Hybrid Optimization Software Suite (HOSS), developed at LANL. HOSS is based on a combined Finite and Discrete Element Method (FDEM). New material models are developed for the sedimentary rocks. HOSS has been recently benchmarked to iSale and FLAG codes. SPECFEM3D is an open-source code developed since the last 90s. It won the Gordon Bell award for best performance in 2003, was finalist again in 2008 for a run at 0.16 petaflops on 149,784 cores on the ‘Jaguar’ Cray system at Oak Ridge National Laboratory. It also won the BULL Joseph Fourier supercomputing award in 2010.; SW4 is a 4th-order finite difference code developed at LLNL which is currently actively developed to handle complex 3D models and to be ported on future exascale platforms. We assessed our need to a total of 3.9M CPU-hrs for year 1 and and 3.1 M for year 2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Forecasting Marine Sediment Properties with Geospatial Machine Learning

Using a combination of geospatial machine learning prediction and sediment thermodynamic/physical modeling, we have developed a novel software workflow to create probabilistic maps of geoacoustic and geomechanical sediment properties of the global seabed. This new technique for producing reliable estimates of seafloor properties can better support Naval operations relying on sonar performance and seabed strength, can constrain models of shallow tomographic structure important for nuclear treaty compliance monitoring/detection, and can provide constraints on the distribution and inventory of shallow methane gas and gas hydrate accumulations on the continental shelves.

58 GEOSCIENCES↗
DOE OSTI2021

Preliminary Radioisotope Screening for Off-site Consequence Assessment of Advanced Non-LWR Systems

Currently a set of 71 radionuclides are accounted for in off-site consequence analysis for LWRs. Radionuclides of dose consequence are expected to change for non-LWRs, with radionuclides of interest being type-specific. This document identifies an expanded set of radionuclides that may need to be accounted for in multiple non-LWR systems: high temperature gas reactors (HTGRs); fluoride-salt-cooled high-temperature reactors (FHRs); thermal-spectrum fluoride-based molten salt reactors (MSRs); fast-spectrum chloride-based MSRs; and, liquid metal fast reactors with metallic fuel (LMRs) Specific considerations are provided for each reactor type in Chapter 2 through Chapter 5, and a summary of all recommendations is provided in Chapter 6. All identified radionuclides are already incorporated within the MACCS software, yet the development of tritium-specific and carbon-specific chemistry models are recommended.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Evolution of Programmatic Asset Lifecycle Planning at MESA

Early on in 2018 Sandia recognized the Microsystems Engineering, Science and Applications (MESA) Programmatic Asset Lifecycle Planning capability to be unpredictable, inconsistent, reactive, and unable to provide strong linkage to the sponsor's needs. The impetus for this report is to share learnings from MESA's journey towards maturing this capability. This report describes re-building the foundational elements of MESA's Programmatic Asset Lifecycle Planning capability using a risk-based, Multi-Criteria Decision Analysis (MCDA) approach. To begin, MESA's decades-old Piano Chart + Ad Hoc Hybrid Methodology is described with a narrative of its strengths and weaknesses. Then its replacement, the MCDA /Analytical Hierarchy Process, is introduced with a discussion of its strengths and weaknesses. To generate a realistic Programmatic Asset Lifecycle Planning budget outlook, MESA used its rolling 20-year Extended Life Program Plan (MELPP) as a baseline. The new MCDA risk-based prioritization methodology implements DOE/NNSA guidelines for prioritization of DOE activities and provides a reliable, structured framework for combining expert judgement and stakeholder preferences according to an established scientific technique. An in-house Hybrid Decision Support System (HDSS) software application was developed to facilitate production of several key deliverables. The application enables analysis of the prioritization decisions with charts to display and provide linkage of MESA's funding requests to the stakeholders' priorities, strategic objectives, nuclear deterrence programs, MESA priorities, and much more.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Validation of SAS4A/SASSYS-1 for Steady-State Single-Phase Natural Circulation

The development of numerical software for engineering applications requires the validation of the code against experimental benchmark datasets. To support the validation of SAS4A/SASSYS-1 in simulating the single-phase natural circulation within nuclear reactor systems, high-precision steady-state experiments are performed to capture single-phase natural circulation phenomena on an existing scaled facility with comprehensive instrumentation. Forced convection tests are designed precisely capturing the facility’s critical thermal-hydraulic parameters required for one-dimensional modeling, and a comprehensive single-phase natural circulation dataset is obtained with well-documented experimental uncertainty and facility description. Analysis and discussion based on the finalized dataset confirm the dataset’s ability in capturing dominant phenomena and address important physical interpretation of parameters. The dataset reported in this project provides a valuable benchmark resource for the validation of system analysis codes under single-phase natural circulation inside nuclear reactors. Validation of SAS4A/SASSYS-1 is then performed against the obtained benchmark dataset to confirm the capability of its physics model in simulating the steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators to quantify and restrict numerical errors from discretization. Numerical uncertainty originating from finite maximum pseudo-transient time is also quantified and restricted. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, directly quantifying the simulation output in a Monte Carlo approach. The composition of the output uncertainty is further determined by the estimators of Sobol’ indices through a variance-based sensitivity analysis. With uncertainty quantified for each individual condition, detailed comparison between the simulation results and experimental data is performed covering the whole dataset, which shows consistent agreement for all important quantities. The validation activity reported in this project demonstrates that SAS4A/SASSYS-1 can predict the primary parameters with satisfactorily accuracy under steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Surveying the LLNL WSC/CP DevOps Landscape - FY23 DevOps L2: Advanced Simulation and Computing (ASC) L2 Milestone 8542, "Spack Utilization in IC Code Projects”

This L2 milestone is a multifaceted review of DevOps practices across Weapon Simulation and Computing/Computational Physics (WSC/CP) Program, which includes Weapons, ICF, and Engineering simulation codes and supporting libraries. It complements the FY22 Spack/MARBL L2: Advanced Simulation and Computing (ASC) L2 Milestone 7904, “Workflow Portability Across Cloud Services”. The overall goal is to develop a path forward for improving DevOps practices in WSC/CP which will increase developer productivity, improve software quality, and speed up our ability to deliver capabilities to end users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $ \$ $6B annually (at $ \$ $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year), and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE) missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

42 ENGINEERING↗
DOE OSTI2023

Surface Roughness Effects from Additive Manufacturing in High Efficiency Gas Turbine Combustion Systems

In the past, clean combustion systems were characterized by high system development costs due to growing complexity and escalating manufacturing costs from conventional manufacturing processes. As a result, high efficiency concepts are difficult to design and more difficult to be cost-effectively manufactured. In recent years, with the introduction of additive manufacturing (AM) technologies, the rapid prototyping and mass production processes of clean combustion systems are promising to be significantly simplified with significant reduction in terms of engine manufacturing cost and engine energy cost. Compared with conventional manufacturing built parts, the AM process enabled a simpler design to be adopted for the nozzle, reducing the number of required braze and weld joints from twenty-five to just five. The resulting nozzle was 25% lighter and five times more durable and contributed to a 15% reduction in fuel burn in comparison with the previous model produced. Applying these improvements to a fleet of 5,000 turbofan engines at 150 kN thrust would result in fuel cost savings of $6B annually (at $5/gallon Jet-A fuel price, 700 gallon/hour fuel consumption rate, and 2,300 operational hours per year),and reduce CO2 emissions by more than 25 million tons per year. These advances support core Department of Energy (DOE)missions in energy efficiency, improving productivity, and environmental sustainability. Maximizing the benefit of these new capabilities will require high prediction capability of high speed turbulent flow with wall modeled Large Eddy Simulation (LES). GE Aviation maintains that advanced simulation technology and supercomputing is required in order to provide the appropriate boundary conditions to realize the maximum potential of AM and Ceramic Matrix Composite to reduce cooling flow, a first order penalty on the Brayton cycle. The algorithm developed using the ANSYS/Fluent software would provide the foundation for entirely new avenues of research and development with potential multi-billion dollar impact to the US economy, and significant reduction in carbon based emissions across the aerospace and power generation industries. The formulation of this iWLES (integral wall model for LES) is generic and allows to capture the changes in flow dynamics that have a significant impact on the wall bounded flow characteristics, such as swirler effective area, bulk swirl number, local pressure distribution, exit velocity profile, and turbulence kinetic energy profile. A periodic channel flow with rough flat plate is simulated using LES (Wall-Adapting Local Eddy-viscosity) model to verify the implementation of iWLES in the Fluent User Defined Function (UDF). As the flow fields are highly sensitive due to surface roughness of the wall bounded flows in the combustion systems, there is significant potential to conduct further LES studies focusing on the turbulence boundary layer interaction. Accurately capturing near wall physics will elucidate the impact of rough surfaces on combustor flow and aero-thermal interactions.

99 GENERAL AND MISCELLANEOUS↗
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 OSTI2024

Ristra Project FY23 L2 Milestone Report, Rev.1: MRT #8541: Multiphysics Scaling on EAS-3

The findings of this report were used to close out the ATDM milestone MRT# 8541, which was designed to demonstrate readiness of ATDM multiphysics codes for mission-relevant work on ATS-4, El Capitan. To this end, the closure criteria were to run a 3D shaped charge problem at scale up to 50% of the El Capitan early-access system, RZVernal (AMD Trento CPUs and AMD MI-250X GPUs), demonstrate scalability, and document challenges with the software stack and environment. LANL’s approach to this milestone was to test our modular software capability by developing an entirely new code, Moya, built upon our FleCSI framework. The physics capability and the GPU infrastructure needed for the shaped charge problem on GPUs was added to Moya, and the required calculations were performed at scale. Moya showed good scaling without any fine-tuning of GPU kernels; there is still significant room for performance enhancements, especially for the Legion backend. Tied up in this L2 milestone was a closeout of KPP-3s for the ECP ST Projects at LANL; this material will be covered in a separate document.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Utility of Big Area Additive Manufacturing for Part Production for Low-Head Hydropower

ORNL worked with Cadens, LLC to explore the use of additive manufacturing (AM) for the production of low-cost parts for low-head hydropower systems. Cadens develops design optimization software that leverages the flexible, low-cost, high-strength benefits of AM and composite materials, and operates a micro-hydro lab to test AM components in controlled environments. Until now Cadens’ tests have been limited in size to components that they can cost-effectively manufacture using local commercial systems. This project provided an opportunity for Cadens to scale up their modular AM hydropower parts using the capabilities of Big Area Additive Manufacturing (BAAM). This project was a success and resulted in the design and fabrication of several end use parts of a hydropower system using a Big Area Additive Manufacturing (BAAM) system. The fabricated parts include draft tube, thimble, runner housing mold, PVC end fitting and two PVC pipe supports. The components have been in use for more than three years without a 3D printed component failing.

13 HYDRO ENERGY↗
DOE OSTI2024

Designing Cellular Metal Structures for Thermal Insulation

This project focused on developing topology optimization software to design advanced metal thermal insulators. Initially, solid designs were created that matched the thermal performance of current baseline designs but were significantly heavier. To address this, cellular materials were incorporated, specifically the octet structure which is known for its high strength-to-weight ratio and thermal properties. By leveraging these cellular designs at various densities, superior thermal and mechanical performance was achieved without added weight. This novel approach enhances thermal management and structural integrity under extreme conditions, offering promising advancements for thermal protection systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

FY24 Advancements in PFLOTRAN Development for GDSA Framework

The Spent Fuel & Waste Science and Technology (SFWST) Campaign of the Office of Spent Fuel & Waste Disposition of U.S. Department of Energy Office of Nuclear Energy (DOE-NE) is conducting research and development on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). This report describes fiscal year 2024 accomplishments in the Geologic Disposal Safety Assessment (GDSA) PFLOTRAN Development work package, which is charged with developing subsurface simulation software for postclosure performance assessment of deep geologic disposal of SNF and HLW.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An Update on Microreactor Automated Control System (MACS)

Automation of control systems is expected to be important in the economic and safe operation of microreactors. There is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a microreactor automated control system (MACS) testbed developed to test control system automation. While a future goal is to demonstrate this system using a prototypic microreactor such as MARVEL, the present focus is on developing and testing within a non-nuclear testbed. The testbed, developed in collaboration with Idaho National Laboratory, includes hardware-in-the-loop simulation and uses a Modelica-based model of a prototypic microreactor for use in testing control automation. Research to date at Oak Ridge National Laboratory has focused on the development of prototypic software for automating plant-level control under selected scenarios. Empirical testing on the integrated MACS testbed was performed to quantify key characteristics of the integrated testbed and to demonstrate the use of the software for automating the calculation and use of actuation setpoints for selected load-following scenarios. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Inspecta Technical Report

Sandia National Laboratories (SNL) is in the process of creating Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant), an Artificial Intelligence (AI)-powered smart digital assistant (SDA) with robotic capabilities, aimed at enhancing the effectiveness, efficiency, and safety of international nuclear safeguards inspections. This innovative tool is designed to assist inspectors on-site by supporting or automating tasks that are typically mundane, hazardous, or susceptible to errors. In 2021, the development team established the specifications for Inspecta by analyzing International Atomic Energy Agency (IAEA) documents and consulting with former IAEA inspectors and subject matter experts. This process involved aligning in-field inspection tasks with existing commercial or open-source technologies to outline a roadmap for the initial prototype of Inspecta, while also identifying areas needing further research and development. From 2022 – 2024, the focus has shifted to integrating a critical inspection activity, the examination of seals, into an early version of Inspecta. This has involved developing both the software and hardware capabilities necessary for this task. This report outlines the ongoing advancements in Inspecta's functionalities, specifically those supporting the seal examination process.

97 MATHEMATICS AND COMPUTING↗