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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 991 records · Page 55

Unprecedented Analysis of LA’s Clean Energy Transformation

Jurisdictions like the City of Los Angeles are boldly establishing ambitious energy objectives—and NREL can be a key partner in informing these transitions.The City of Los Angeles is one of several U.S. local governments setting monumental, measurable goals to transform their energy economies. At the direction of its City Council, LA has embarked on a plan to modernize its electricity system infrastructure—aiming for a 100% renewable energy supply by 2045, along with aggressive electrification targets for buildings and vehicles.

LA100↗

A Transformational Graduate Program: Mines and NREL Join Forces To Shape the Future of Energy

Developing secure, resilient, and adaptive energy infrastructure that fosters economic growth while reducing environmental impact is among the most pressing challenges—and greatest opportunities—of our time. It will require the next generation of thought leaders to capably and creatively guide this vital energy sector transition. Through a new interdisciplinary graduate program, Colorado School of Mines (Mines) and the National Renewable Energy Laboratory (NREL) are cultivating the rich opportunity landscape needed to develop these future innovators. The Mines/NREL Advanced Energy Systems (AES) degree program prepares researchers at the doctoral level and energy professionals at the master’s level to address the full complexity of tomorrow's infrastructure, economic, and environmental challenges. The combination of a thriving cleantech market in Colorado, world-class resources and researchers at NREL, and rigorous educational and technical programs at Mines create a truly one-of-a-kind opportunity for advancing fields related to energy systems. These links can uniquely equip top-caliber students to become the scientists and engineers at the forefront of our global energy economy transformation.

Advanced Energy Systems↗

Device and method for constructing and displaying high quality images from imaging data by transforming a data structure utilizing machine learning techniques

Constructing a computer image from raw imaging data or encoded imaging data by transforming a first data structure in which the raw imaging data or the encoded imaging data is stored into a second data structure storing reorganized imaging data. The raw imaging data or the encoded imaging data is received, stored in the first data structure. The computer reorganizes the raw imaging data or the encoded imaging data into the reorganized data and stores the reorganized data in the second data structure, which is a multi-dimensional array having subarrays containing local information needed by a convolutional neural network for processing the reorganized data. Other portions of the multi-dimensional array store other portions of the raw imaging data or the encoded imaging data. The computer also processes the reorganized data using the convolutional neural network to construct the image, whereby a constructed image is formed.

Korbin, John P.↗

Transformation enabled nitride magnets absent rare earths and a process of making the same

A process for producing an ordered martensitic iron nitride powder that is suitable for use as a permanent magnetic material is provided. The process includes fabricating an iron alloy powder having a desired composition and uniformity; nitriding the iron alloy powder by contacting the material with a nitrogen source in a fluidized bed reactor to produce a nitride iron powder; transforming the nitride iron powder to a disordered martensitic phase; annealing the disordered martensitic phase to an ordered martensitic phase; and separating the ordered martensitic phase from the iron nitride powder to yield an ordered martensitic iron nitride powder.

Matthiesen, David↗

Design and performance of a multi-terahertz Fourier transform spectrometer for axion dark matter experiments

Dedicated spectrometers for terahertz radiation with [0.3, 30] THz frequencies using traditional optomechanical interferometry are substantially less common than their infrared and microwave counterparts. This paper presents the design and initial performance measurements of a tabletop Fourier transform spectrometer (FTS) for multi-terahertz radiation using infrared optics in a Michelson arrangement. This is coupled to a broadband pyroelectric photodetector designed for [0.1, 30] THz frequencies. We measure spectra of narrowband and broadband input radiation to characterize the performance of this instrument above 10 THz, where signal-to-noise is high. This paves the groundwork for planned upgrades to extend below 10 THz. We also briefly discuss potential astroparticle physics applications of such FTS instruments to broadband axion dark matter searches, whose signature comprises low-rate monochromatic photons with unknown frequency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Metal-organic frameworks for the adsorption and catalytic transformations of carbon dioxide

Novel crystalline porous materials known as metal-organic frameworks (MOFs) and methods for their synthesis are provided herein. The MOFs include a M6(μ3-OH)8(OH)8(μ2,η2-(O2C)2cyclam)8 cluster, and a metal atom coordinated to the one or more cyclam of the cluster, wherein M is Zr or Hf, and the metal atom is any one of Cu, Ni, Cr, Ru, Co, and Gd. The MOFs can be used as an adsorbent, alone or in a medium with other components, of CO2. The MOFs can also be used as a catalyst for the transformation of CO2 and epoxides to cyclic carbonates. The MOFs can also be used in the electrochemical catalytic reduction of CO2. The MOFs can also be used for photocatalytic CO2 reduction for the production of carbon-based fossil fuels. The MOFs can also be used for light-induced nitric oxide (NO) release. The MOFs can also be used as magnetic resonance imaging (MRI) agents.

Morris, Amanda Jean↗

EMPOWER: Accelerating the Transformation of the Global Energy Economy - 2022 JISEA Annual Report

The 2022 JISEA Annual Report describes accomplishments from the past year at the Joint Institute for Strategic Energy Analysis, which is accelerating the transformation of the global energy economy. 2021 was filled collaboration and high-impact multidisciplinary projects, exploring everything from the energy-water-food nexus, to the cobalt supply chain, to sustainable communities. This year also welcomed the JISEA Catalyzers Initiative that is accelerating research capabilities at the National Renewable Energy Laboratory. The Catalyzers are empowering communities and research partners to by bringing together experts working within one space to discuss capabilities and future needs to continue to stay ahead of the research curve.

clean energy↗

Uncertainty Quantification in High-Low Dynamic System Coupling using RAVEN and TRANSFORM

This work demonstrates new functionality and applications stemming from the development of high-fidelity to low-fidelity (high-low) coupling for system simulations and to further explore the capabilities of the Risk Analysis Virtual Environment (RAVEN) in the performance of uncertainty quantification in this kind of high-low coupled system models. The work builds from previous work on high-low coupling that utilized COBRA-TF (CTF), the high-fidelity subchannel analysis code, with a low fidelity model built in ORNL’s TRANSFORM, the system analysis code, utilizing the Functional Mock-Up Interface (FMI). Steady-state and transient analysis examples using the high/low coupled models generated from CTF and TRANSFORM/FMI are investigated. The workflows for both steady-state and transient coupled simulations are described. A steady-state parameter sweep and uncertainty analysis of the primary flow rates and reactor power are demonstrated. Likewise, a transient pump trip and power ramp sensitivity studies are also demonstrated. This work elucidates some of the potential benefits and future needs of using RAVEN for high/low system coupling analysis of energy systems. It also shows some of the difficulties that can be encountered in coupling system simulations.

Williams, Wesley↗

ADDITIVELY MANUFACTURED SURFACE HEAT TRANSFER ENHANCEMENTS FOR THE TRANSFORMATIONAL CHALLENGE REACTOR

The Transformational Challenge Reactor (TCR) is a high-temperature gas-cooled reactor design that uses additively manufactured fuel elements. TCR fuel elements have walls made of silicon carbide and are filled with tristructural-isotropic fuel particles. These fuel elements can have radically different shapes and integrated features than existing designs due to the reduced cost for complex structures in binder jet additive manufacturing. As such, binder jet additive manufacturing enables wall surface features to be embedded that can deliver superior heat transfer performance than smooth wall designs. In this work, the authors conducted a computational fluid dynamics study to evaluate selected wall features integrated into TCR fuel elements. Results show that surface features can outperform smooth wall designs; however, there are unique challenges for gas-cooled reactor core designs that have not been fully explored by previous research. For example, the rough surface finish and process variability of ceramics additive manufacturing make it challenging to predict surface roughness effects before fabrication. Additionally, the small hydraulic diameters of coolant channels in reactor cores make it difficult to engineer surface features that do not significantly increase the pressure drop. Engineers must carefully size surface features for heat transfer enhancement in additive fuel elements to operate above the base material's surface roughness effects and below the coolant channel size.

Weinmeister, Justin↗

PIVOT: Powering the Transformation of the Global Energy Economy - 2023 JISEA Annual Report

The 2023 JISEA Annual Report describes accomplishments from the past year at the Joint Institute for Strategic Energy Analysis, which is powering the transformation of the global energy economy. 2022 was filled with high-impact work in supply chain analysis, industrial decarbonization, sustainable communities, and more. This year, JISEA also launched the Green Computing Catalyzer and welcomed the American-Made program to the center.

catalyzer↗

Symmetric Random Butterfly Transform (SRBT) Based Preconditioner

Summary of work using Symmetric Random Butterfly Transformation (SRBT) in conjunction with Incomplete LDL T factorization as a preconditioner for FGMRES solver as a way of solving linear systems arising from interior point methods applied to power system problems. These linear systems have proven difficult to parallelize and this represents a possible route forward.

interior point optimization↗

Induced Generative Adversarial Particle Transformers

In high energy physics (HEP), machine learning methods have emerged as an effective way to accurately simulate particle collisions at the Large Hadron Collider (LHC). The message-passing generative adversarial network (MPGAN) was the first model to simulate collisions as point, or ``particle'', clouds, with state-of-the-art results, but suffered from quadratic time complexity. Recently, generative adversarial particle transformers (GAPTs) were introduced to address this drawback; however, results did not surpass MPGAN. We introduce induced GAPT (iGAPT) which, by integrating ``induced particle-attention blocks'' and conditioning on global jet attributes, not only offers linear time complexity but is also able to capture intricate jet substructure, surpassing MPGAN in many metrics. Our experiments demonstrate the potential of iGAPT to simulate complex HEP data accurately and efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A new track finding algorithm based on a multi-dimensional extension of the Hough Transform

We introduce a new pattern recognition algorithm for track finding in High Energy Physics Experiments based on an extension of the Hough Transform to multiple dimensions. A remarkable property of this algorithm is that the execution time is simply proportional to the total number of the hits to be processed, making it particularly attractive for high occupancy situations. The algorithm needs to be trained using a sufficiently large set of simulated tracks. The same track finding algorithm can be used for very different detector geometries and only the set of simulated tracks used for training needs to be changed. The particular structure of the algorithm also lends itself naturally to parallel hardware implementations which, combined with its intrinsic flexibility, should provide a most powerful tool for triggering at future colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Transient MOC with frequency transform and DSA on unstructured mesh

We present an implementation of the transient method of characteristics (MOC) with isotropic time derivatives, accelerated by diffusion synthetic acceleration (DSA). The fully implicit frequency transform method is used to solve the transient problem with analytic precursor integration. The code works on meshes composed of almost any of the commonly used non-curvilinear finite element types, and can handle the deformation of geometry in time-dependent transport calculations. We present results of a continuous Fourier analysis for the transient multigroup DSA problem, and representative benchmarking results are presented for the C5G7-TD benchmark in 2D showing reasonable performance and agreement compared to other codes. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Status of Power System Transformation: Leading Topics of 2024

This presentation provides an overview of key power sector transformation topics that are relevant for global power system decarbonization and net zero goals. It includes examples of strategies to achieve rapid power system decarbonization and enable clean energy deployment.

21st Century Power Partnership↗

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗