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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Safety Design Strategy for the Transformational Research Reactor

The Department of Energy Office of Nuclear Energy is embarking on the Transformational Challenge Reactor (TCR) program to demonstrate application of advanced technologies in enabling rapid and cost effective deployment of nuclear power systems. The TCR program will design, manufacture, and operate a small nuclear reactor at the Oak Ridge National Laboratory incorporating advanced manufacturing. DOE Order 420.1C requires the integration of safety in the design process. Therefore, the general approach in DOE-STD-1189 as described in this Safety Design Strategy is applied to the project to establish requirements for safety design for the resultant Categorized Nuclear Facility/Activity and to ultimately allow the Department of Energy to authorize operation of the facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

TCR Data Management Plan

The Oak Ridge National Laboratory (ORNL) Transformation Challenge Reactor (TCR) program is developing additive manufacturing and artificial intelligence (AI) to deliver enabling technologies for advanced reactors. Through the application of these advanced technologies, the program targets delivering solutions to the high costs and lengthy deployment timelines that threaten the future of nuclear energy—the country’s largest source of carbon-free energy. This document describes the plan for integrating and managing TCR data from multiple sources throughout ORNL and external sources, including novel data sources associated with advanced manufacturing, characterization systems, and the TCR Digital Platform that incorporates various levels of AI and data analytics.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Monitoring for Additive Manufacturing Technologies: Report on Progress, Achievements, and Limitations of Monitoring Techniques

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology of choice for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence that can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree data sets is vital, should these data be generated before, during, or after the manufacturing process. This report focuses on the collection of manufacturing process data using systems instrumentation and monitoring. It presents an inventory of the various monitoring modalities installed on the manufacturing systems by the machine manufacturer or specifically designed by our team to fill information gaps. It also provides details on other relevant data streams available and leverageable to evaluate the manufacturing process on all classes of AM systems investigated during the first year of this program. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

42 ENGINEERING↗
DOE OSTI2021

Mechanical Properties of Additively Manufactured 316L Stainless Steel Before and After Neutron Irradiation (FY21)

This report presents the materials property data of additively manufactured (AM) 316L stainless steel (SS) accumulated for the assessment of core materials in the Transformational Challenge Reactor (TCR) program. The TCR manufacturing approach includes using the laser powder bed fusion (LPBF) method for metallic (316L and Inconel 718) components. To assess the mechanical performance of printed components in reactor-relevant conditions and build a property database for the AM materials, mechanical tests and evaluations were performed before and after neutron irradiation. Miniature tensile specimens were irradiated in the High Flux Isotope Reactor to 0.2, 2, 8, and 10 dpa at target temperatures of 300 and 600°C. Postirradiation evaluation for the 0.2 and 2 dpa specimens was performed during FY20 and FY21, and the results are presented and discussed in this document.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Hydrogen Diffusivity Measurements of YH 1.87 Moderator Material with Incoherent Quasielastic Neutron Scattering

Yttrium hydride is an optimal choice of moderator material for thermal neutron spectrum reactors requiring small core volumes. The Transformation Challenge Reactor (TCR) program at Oak Ridge National Laboratory (ORNL) aims to develop an additively manufactured microreactor core by leveraging recent advances in materials, manufacturing, data analytics, and high-fidelity modeling and simulation. Yttrium hydride was selected as the moderator material for TCR due to its high moderating power, which enables the spatially efficient reactor design and thermal stability that is superior when compared with zirconium hydride. Hydrogen desorption from yttrium hydride is expected at elevated temperatures, posing safety and performance concerns. As a lifetime component in advanced reactors, appropriate strategies to mitigate hydrogen release from yttrium hydride over long-term reactor operation are required. Understanding hydrogen mobility in yttrium hydride provides the scientific basis for developing a hydrogen barrier for hydride moderator and predicting the hydrogen redistribution within the material during various operational conditions. This study investigated the hydrogen motion in YH 1.87 as a function of temperature ranging from 200 to 1,173 K using incoherent quasielastic neutron scattering (IQNS) at the Spallation Neutron Source (SNS). The results are presented and discussed in terms of hydrogen self-diffusion coefficients, activation energy for translational hydrogen motion, and hydrogen jump distances. Based on the IQNS data, YH 1.87 is found to be stable at high temperatures with no translational H motion below 1,023 K within the IQNS detection limits. In the temperature range of 1,073–1,173 K, hydrogen diffusivity in YH 1.87 is $D = 4.57 X 10^{⁻3} [m^2/s] exp (⁻\frac{1.73[eV]}{RT}$). The hydrogen concentration’s dependence on hydrogen diffusivity is also discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Viability of Data Analytics to Ascertain Component Performance for Additive Manufacturing

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to produce multiple nuclear components to be assembled into a fully functional microreactor core. AM was selected as the main manufacturing technology for TCR because it has the potential to disrupt the nuclear industry on two fronts: (1) it enables the manufacturing of very complex geometries with optimized and tailored material properties for the intended use of the component, opening up new options for reactor designs, and (2) it allows for a better understanding of the manufacturing process through real-time in situ monitoring, data analytics, and artificial intelligence, which can lead to a streamlined qualification and certification process. Within TCR, the development and deployment of a digital platform aims at addressing the latter opportunity. As part of this effort, the collection of pedigree datasets is vital, should these data be generated before, during or after the manufacturing process. This report focuses on the development of data analytics tools enabling qualitative assessment of the manufacturing processes to automate the identification of flaws in in situ monitoring imagery and to correlate those flaws to the resulting mechanical testing data. Through examples, the report gives an overview of the data collected and presents a path forward for the digital platform.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

ARM Aerial Instrument Workshop Report

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program is to “support transformative science and scientific user facilities to achieve a predictive understanding of complex biological, earth, and environmental systems for energy and infrastructure security, independence, and prosperity.” (https://science.osti.gov/ber) Aligned with the BER central mission, the Earth and Environmental Systems Sciences Division (EESSD) plays a vital role in supporting the fundamental research to understand and predict Earth’s climate and environmental systems, and is also in a unique position to inform the development of sustainable solutions to the nation’s energy and environmental challenges. Specifically, EESSD manages two scientific user facilities: the Atmospheric Radiation Measurement (ARM) user facility and the Environmental Molecular Sciences Laboratory (EMSL). These facilities provide the broader scientific community with scientific expertise, technical capabilities, and unique data sets to facilitate science in areas of importance to DOE. As a multi-platform scientific user facility, ARM aims to fulfill the needs predominantly within the EESSD Atmospheric System Research (ASR) and the Earth and Environmental System Modeling (EESM) mission areas, and provide the critical measurements required to improve understanding of aerosol and cloud life cycles and their interactions, and their coupling with the Earth’s surface. Over the years, ARM has carried out piloted and unmanned aircraft campaigns under different organizational and operational paradigms (Schmid et al. 2014, 2016). Building on its success, the ARM Aerial Facility (AAF) continues to complement the ground-based observations with airborne in situ cloud, aerosol, and trace gas observations as well as measurements of atmospheric state and atmospheric radiation. During the past three years, ARM has managed field campaigns using unmanned aerial systems (UAS) and tethered balloon systems (TBS) at Oliktok Point in Alaska to improve understanding of atmospheric processes in the Arctic. In 2019, following a careful evaluation of scientific community needs, ARM acquired a Bombardier Challenger 850 regional jet to replace the vintage Grumman Gulfstream-159 turboprop aircraft previously used by AAF. With this new “laboratory in the sky”, AAF is evaluating its current and future aerial observation capabilities to continue satisfying the needs of the research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Candidate Core Designs for the Transformational Challenge Reactor

Early cycle activities under the Transformational Challenge Reactor (TCR) program focused on analyzing and maturing four reactor core design concepts: two fast-spectrum systems and two thermal-spectrum systems. A rapid, iterative approach has been implemented through which designs can be modified and analyzed and subcomponents can be manufactured in parallel over time frames of weeks rather than months or years. To meet key program initiatives (e.g., timeline, material use), several constraints—including fissile material availability (less than 250 kg of HALEU), component availabilities, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small (less than one cubic meter in volume) cores with near-term viability. The fast-spectrum designs did not meet the fissile material constraint, so the thermal-spectrum systems became the primary design focus. Since significant progress has been made on advanced moderator materials (YH x ) under the TCR program, gas-cooled thermal-spectrum systems using less than 250 kg of HALEU that occupy less than 1 m 3 are now feasible. The designs for two of these systems have been evolved and matured. In both thermal-spectrum design concepts, bidirectional coolant flow is used. Coolant flows down through YH x moderator elements and is reversed in a bottom manifold and core support structure, and then flows up though or around the fuel elements. The main difference between the two thermal-spectrum design concepts is the fuel elements—one uses traditional UO 2 ceramic fuel, and the other uses UN-bearing TRISO fuel particles embedded inside a SiC matrix. Finally, core neutronics and thermal performance for these systems are assessed and summarized herein.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1972

Automated cloud tracking using precisely aligned digital ATS pictures.

Discussion of the interactive man-computer system (WIMDCO) for measuring cloud motion from ATS pictures. The multipicture model of ATS navigation is used for consecutive ATS digital picture alignment to provide the required precision in cloud motion measurements by automated tracking techniques. Cloud motion is measured by tracking clouds between two digital pictures with the aid of two-dimensional cross correlation analysis. The fast Fourier transform method and other programming techniques are used for time and cost minimization. Cloud motion vectors were computed over three time intervals in July, 1969. The EW and NS components were reproducible within roughly 2 knots.

Smith, E. A.↗
NASA NTRS1964

Analytical Solutions for Non-Linear Differential Equations with the Help of a Digital Computer

A technique was developed with the help of a digital computer for analytic (algebraic) solutions of autonomous and nonautonomous equations. Two operational transform techniques have been programmed for the solution of these equations. Only relatively simple nonlinear differential equations have been considered. In the cases considered it has been possible to assimilate the secular terms into the solutions. For cases where f(t) is not a bounded function, a direct series solution is developed which can be shown to be an analytic function. All solutions have been checked against results obtained by numerical integration for given initial conditions and constants. It is evident that certain nonlinear differential equations can be solved with the help of a digital computer.

Cromwell, P. C.↗
NASA NTRS1989

The properties of the Neckel-Chini VRI system

Cousins (1980) data for 54 of the standard stars of Neckel and Chini (1980) and published measurements are used to investigate the properties of the Neckel-Chini VRI system. For red stars, this system diverges from the Johnson (1962) system, despite frequent claims of identity between the two. The Neckel-Chini and Cousins systems, however, are closely comparable. Both of these conclusions were previously reached in a paper by Bessell (1983); fair to good quantitative agreement with his results are obtained. Reddening ratios, the scatter in the Neckel-Chini standard-star data, and the effect of this scatter on published measurements for program stars, are discussed. Transformations from the Neckel-Chini system to the Cousins system are given.

Taylor, Benjamin J.↗
NASA NTRS1990

Masking failures of multidimensional sensors (extended abstract)

When a computer monitors a physical process, the computer uses sensors to determine the values of the physical variables that represent the state of the process. A sensor can sometimes fail, however, and in the worst case report a value completely unrelated to the true physical value. The work described is motivated by a methodology for transforming a process control program that can not tolerate sensor failure into one that can. In this methodology, a reliable abstract sensor is created by combining information from several real sensors that measure the same physical value. To be useful, an abstract sensor must deliver reasonably accurate information at reasonable computational cost. Sensors are considered that deliver multidimensional values (e.g., location or velocity in three dimensions, or both temperature and pressure). Geometric techniques are used to derive upper bounds on abstract sensor accuracy and to develop efficient algorithms for implementing abstract sensors.

Chew, Paul↗
NASA NTRS1995

Automatic differentiation evaluated as a tool for rotorcraft design and optimization

This paper investigates the use of automatic differentiation (AD) as a means for generating sensitivity analyses in rotorcraft design and optimization. This technique transforms an existing computer program into a new program that performs sensitivity analysis in addition to the original analysis. The original FORTRAN program calculates a set of dependent (output) variables from a set of independent (input) variables, the new FORTRAN program calculates the partial derivatives of the dependent variables with respect to the independent variables. The AD technique is a systematic implementation of the chain rule of differentiation, this method produces derivatives to machine accuracy at a cost that is comparable with that of finite-differencing methods. For this study, an analysis code that consists of the Langley-developed hover analysis HOVT, the comprehensive rotor analysis CAMRAD/JA, and associated preprocessors is processed through the AD preprocessor ADIFOR 2.0. The resulting derivatives are compared with derivatives obtained from finite-differencing techniques. The derivatives obtained with ADIFOR 2.0 are exact within machine accuracy and do not depend on the selection of step-size, as are the derivatives obtained with finite-differencing techniques.

Walsh, Joanne L.↗