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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Exploring Container Technologies for Large Scientific Libraries: Docker and Trilinos

The Trilinos Project produces, maintains and distributes a large collection of reusable, parallel scientific libraries. Docker provides container technologies that support compilation, packaging, distribution and execution of software on Linux, Mac OS and Windows systems, with emerging support for Cray platforms. In this short article we describe recent efforts to explore the potential for using Docker in a variety of settings to enhance several Trilinos Project workflows. The technical foundation for this article is presented in an Honors thesis of one of the authors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Exploring the suitability of MXenes for sensing applications

The development of sensitive, yet easy-to-use methods for the detection of actinides (uranium, plutonium, etc.) is of continual interest for ensuring nuclear safety, enhancing nuclear nonproliferation efforts, and tracking nuclear species in the environment. In this project, researchers from SRNL and Fayetteville State University explored using films based on titanium carbide nanoparticles ("MXenes") as sensing materials to support trace-level measurements. We showed that MXenes could be used to measure low levels of a test molecule (Rhodamine B). The signal was linearly dependent on concentration, indicating that the method could be used for quantitative measurements and not just detection. We identified several ways to make the films better able to support routine measurements. Once these improvements are implemented, we will demonstrate their use for measuring uranium under conditions typical for environmental samples and waste streams in nuclear materials processing facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The Maunakea Spectroscopic Explorer

The Maunakea Spectroscopic Explorer is a next-generation massively multiplexed spectroscopic facility currently under development in Hawaii. It is completely dedicated to large-scale spectroscopic surveys and will enable transformative science. In this white paper we summarize the science case and describe the current state of the project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Power Sector Transformation Pathways: Exploring Objectives, Factors, and Technology Innovations to Inform Power Sector Pathway Decisions

The power and heating sectors are responsible for around 30% of global CO2 emissions and this share is likely to grow as countries move towards electrification of the transportation and building sectors. Therefore, enabling forward-thinking, long term strategies in the power sector is a crucial area for international collaboration and support. The rapid transition of power systems toward modern, low-carbon pathways and technologies will be necessary to meet key climate goals while also enabling other critical objectives such as economic development, energy access, and energy system resiliency, among others. Many developed and developing countries are well-poised to champion power sector transformation (PST), however, further support is needed to identify pathways and implement critical near and long-term actions. To address this need, the Low Emission Development Strategies Global Partnership (LEDS GP) together with an expert team including Agora Energiewende, Energy Innovation, European Climate Foundation, Fraunhofer Institute for Systems and Innovation Research , Prayas Energy Group and LEDS Latin America and Caribbean Platform, developed a framework identifying four key pathways that can be integrated and combined to support low-carbon PST. These four pathways are: (1) Distributed Energy Resource Revolution, (2) Bulk Power Transformation, (3) Transmission and Distribution Interactivity, and (4) Distributed Transactional Future. To support exploration of pathways, this study examines PST objectives and factors that may lead countries or jurisdictions to place a greater relative emphasis on certain pathways as well as a framework and complementary tool for considering the emphasis in a hands on manner. The report provides case studies on application of the approach to bring life to the topic. The case studies include Haiti, Kenya, Mexico, Southeast Asia, and the European Union, among others. The report also presents actions to-be-taken in the near-, medium- and long-term to support the realization of pathways and long-term transformation of the power sector. The report, together with a complementary spreadsheet tool developed under the effort, can be used to enable stakeholder engagement and visioning for the power sector over the long-term, taking into account key factors and potential innovations. It can also be used to understand and inform relevant analysis tools and models based on which pathways are emphasized, and to identify key actions in the near- and medium-term to avoid lock-in of carbon-intensive technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Exploration of Two-Dimensional Materials for Remote Sensing Applications

Two-dimensional materials were explored through collaboration with Steve Howell and Catalyn Spataru, led by James Bartz during FY15 and FY16 at Sandia National Laboratories. Because of their two-dimensional nature, these materials may offer properties exceeding those of bulk materials. This work involved Density Functional Theory simulations and optical methods, instrumentation development, materials growth and materials characterization. Through simulation the wide variety of two dimensional materials was down-selected for fabrication and testing. Out of the two dimensional semiconductors studied, black phosphorus bilayers showed the strongest spectral absorption tuning with applied electric field. Laser scanning confocal microscopy, spectroscopy and atomic force microscopy allowed for identification of micron scale samples. A technique involving conductive tip atomic force microscopy and back-side illumination was developed simple assembly and characterization of material spectral response.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nuclear Spectroscopy for the Exploration of Mars and Beyond

Nuclear spectroscopy will continue to play a critical role in planetary exploration in the next decade, including searching for habitable environments and biosignatures, identifying ideal targets for in-situ resource utilization, and continuing its track record in understanding planetary evolution. Nuclear spectroscopy is the only technique that provides bulk geochemical abundance at depth, at a range of spatial scales depending on platform.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Exploring new small system geometries in heavy ion collisions [Slides]

We explore various new collision geometries in the context of the publicly available hydrodynamic model SONIC. We incorporate full A-nucleon configurations for 4 He, 12 C, and 16 O obtained from quantum Monte Carlo calculations with realistic nuclear potentials, and use a Monte Carlo Glauber calculation for the initial conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Modular hybrid modeling to increase efficiency, explore structural uncertainty, and allow multidimensional complexity scaling in land surface models

Land surface models (LSMs) are indispensable tools for predicting hydrologic extremes, as well as a particularly uncertain component of Earth system models that has stubbornly resisted the convergence in projections over several successive generations of model intercomparisons. This uncertainty in LSMs is poorly quantified and poorly attributed to specific processes, which has hampered efforts to focus research in reducing uncertainty. This has resulted from sparse sampling of the possible uncertainty space—which is high-dimensional and has contributions from parametric, structural, initial, and boundary condition uncertainties—as an artifact of CMIP-type ensembles of opportunity and limitations inherent in observational benchmarks. A new approach is needed to understand and reduce this uncertainty, based around individual LSMs that can represent the breadth of assumptions represented in current CMIP-type efforts, while at the same time exploring that uncertainty in a systematic way, confronting multiple types of observations, and where justified, replacing process representations with ML-driven emulators. We propose an approach of modular hybrid modeling to address these challenges.

58 GEOSCIENCES↗
DOE OSTI2021

COVID-19: Spatiotemporal social data analytics and machine learning for pandemic exploration and forecasting

This task focused on developing a preliminary approach to use machine learning (ML) to explore the relationship between county-level societal variables and COVID-19 parameters, including COVID-19 cases rates and counts and COVID-19 death rates and counts. The objective was to develop and test a prototype approach for linking COVID-19 and county-level data. The task focused on enhancing and applying existing LANL ML techniques to COVID-19. Our novel ML methods have been a subject of a recently approved U.S. patent. The codes based on these methods are already open-source released. Our ML tools (NMFk/NTFk) are applied to extract hidden features (signals, waves) in the analyzed datasets and automatically identify their optimal number. The features are extracted by identifying counties that have similarities between the county-level societal variables and the COVID-19 parameters. These demonstration analyses will facilitate the ongoing pandemic simulations and predictions performed by Los Alamos other institutions, as well as lay the groundwork for future work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Exploring OpenSNAPI Use Cases and Evolving Requirements [Slides]

Emerging system architectures are rapidly transforming in order to meet shifting requirements. Motivated by expanding data volumes, energy efficiency concerns, and the omnipresent need to improve performance, architectures are increasingly adopting a data-centric approach. At the core of this concept is the goal of minimizing data motion and instead processing data in-situ to the greatest degree possible. Therefore, data-centric designs, in contrast to conventional CPU-centric models, typically distribute compute capabilities throughout the architecture. As part of this paradigm shift, a novel class of devices known as data processing units (DPUs), alongside CPUs and GPUs, are quickly forming a third pillar of data-centric systems. These devices, which include smart network adapters and switches, seek to offload computation on data at the network edge as well as in-flight within the network fabric. The Open Smart Network API (OpenSNAPI) project seeks to develop a unified API for DPU devices. In our previous talks, we introduced the OpenSNAPI project and detailed our investigations regarding the viability of offloading compute intensive kernels to BlueField DPUs. In contrast, in this talk we detail our efforts to offload application-level file I/O to the DPU. We also discuss plans and early efforts to explore in-network compute capabilities. Finally, we describe our observations with respect to the evolving design of OpenSNAPI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Exploring Whether Subsurface Fluid Production Can Minimize Triggered Seismicity in Geothermal Fields

Fluid injection and production related to energy recovery and other industrial operations alter the pressure and stress state of subsurface reservoirs which can lead to induced seismicity. Here, the primary goal is to investigate the hypothesis that the modulation of stress state in subsurface reservoirs through fluid injection/production operations can reduce the likelihood of inducing seismicity. Validation of this mitigation strategy will provide an active operational method to control induced seismicity in subsurface reservoir exploitations such as geothermal energy recovery and carbon storage. In this project, we analyze the relationship between extensive fluid production and the paucity of aftershock activity at the Coso Geothermal plant (CGP) following the 2019 Ridgecrest earthquake sequence, where high rates of aftershock triggering were expected. We developed a high-fidelity multiphase coupled thermo-hydro-mechanical (THM) model to simulate fluid injection/production activities at the CGP between 1986 and 2020. THM results of surface subsidence due to high rates of fluid production agree well with field observations from global positioning system (GPS) and interferometric synthetic aperture radar (InSAR). Subsequently, the variations of pore pressure, temperature and stress state were used to drive numerical earthquake simulations of the aftershock response to the 2019 Ridgecrest earthquakes. The earthquake simulations show that seismic quiescence may occur following the Ridgecrest event, depending on the initial stress state at the time of the mainshock and at the initiation of geothermal energy production. Seismic quiescence occurs in 20% of the cases we explored, where rates are decreased by 50% of the background rate in the two years following the mainshock. In circumstances where aftershock rates increase near the CGP following Ridgecrest, the average rate change is a factor of two larger than background rates from simulations with no operations. These findings indicate that unlike many other operations that bring faults closer to failure, operations at the CGP are acting to stabilize faults such that triggering in the current stress state is minimal.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluation of Microhole Drilling Technology for Geothermal Exploration, Assessment, And Monitoring

One of the greatest barriers to geothermal energy expansion is the high cost of drilling during exploration, assessment, and monitoring. Microhole drilling technology—small-diameter 2–4 in. (~5.1–10.2 cm) boreholes—is one potential low-cost alternative for monitoring and evaluating bores. However, delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes needed to realize the cost savings. Coiled tube drilling technology is one solution, but these systems are limited by the torque resistance of the coil system, helical buckling in compression, and most of all, WOB management. The evaluation presented herein will: (i) evaluate the technical and economic feasibility of low WOB technologies (specifically, a percussive hammer and a laser-mechanical system), (ii) develop downhole rotational solutions for low WOB drilling, (iii) provide specifications for a low WOB microhole drilling system, (iv) implement WOB control for low WOB drilling, and (v) evaluate and test low WOB drilling technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Exploring Si Heterojunction Solar Cell Degradation: Bulk and Interface Processes Analyzed by Simulations and Experiments in Order to Develop Mitigation Strategies

The Si technology with the highest conversion efficiency is a-Si/c-Si heterojunction (HJ) PV. Its market penetration, however, is slowed by reports that fielded HJ modules degraded at twice the rate of regular c-Si modules. Our very recent work confirmed this degradation and attributed it to enhanced recombination at the a-Si/c-Si interface, caused by the slow, order-of-magnitude increase of the defect density. We propose to comprehensively explore degradation mechanisms in Si HJ cells by combining simulations and experiments. Theoretically, we will: (1) simulate structure of a-Si and a-Si/c-Si interfaces, identify defects; (2) determine statistics of energy barriers that control defect formation; (3) compute growth of defect density from the barrier distribution, and the resulting degradation of Voc. Experimentally, we will: (1) create a series of HJ-cell-representative stacks with varying layer thicknesses and deposition conditions by using PECVD tools; (2) use temperature and injection-dependent lifetime spectroscopy to determine effective lifetimes; (3) deconvolve the data to separate bulk and interface effects, and the effects of charge density and interface defects to analyze long time degradation. The goal is to identify material and device degradation mechanisms, to develop mitigation strategies for improved stability, such as the introduction of capping layers and hydrogen diffusion control.

14 SOLAR ENERGY↗
DOE OSTI2022

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

P&PD Explorer

The P&PD Explorer is an interactive, spreadsheet-based tool for examining the data tables in the Planning and Production Directive (P&PD).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Compositional Exploration of Additively Manufactured Ultra-High-Temperature Ceramic Composites for Use in Concentrated Solar Power Plant Heat Exchangers

The DOE has research interest in new technologies for high temperature concentrated solar power plants. Our project this summer was to explore the use of additively manufactured ultra-high-temperature ceramics in a heat exchanger. The heat exchanger would transfer heat between a molten chloride salt and supercritical CO 2 . We selected 22 compositions to test and were able to mix 14 of these compositions. We sintered these compositions using pressureless sintering and direct current sintering. We also conducted high temperature TGA on some ceramic samples. We also performed preliminary binder jet additive manufacturing trials with tungsten carbide powder. Our work so far points towards one of our titanium diboride samples being promising, but much more research needs to be done.

14 SOLAR ENERGY↗
DOE OSTI2023

Exploring and Embracing Heterogeneity in Atomically Thin Energy Materials

Atomically thin semiconductors offer extraordinary opportunities for the manipulation of charge carriers, many-body optical excitations, quantum light emitters, and non-charge based quantum numbers. Confinement and reduced dielectric screening in these two-dimensional (2D) materials give rise to large characteristic energies so that many-body and quantum effects are important even at room temperature. Optical excitations in extended homogeneous areas have been investigated intensely, albeit mostly focusing on a limited set of materials, particularly transition metal dichalcogenides. Much less understood are light-matter interactions for other classes of 2D semiconductors, as well as effects that arise in heterogeneous materials, either near naturally occurring defects, impurities, edges and grain boundaries, or as a result of intentional interface formation in heterostructures. Addressing such systems experimentally involves significant challenges: Understanding the atomistic growth mechanisms of 2D semiconductors, so that novel systems with designed properties, specific ‘imperfections’, or controlled interfaces can be realized; and probing of local excitations at scales that match the relevant (micrometer to nanometer) length scales in heterogeneous materials. In this research project, we addressed these challenges by harnessing quantitative in-situ microscopy to study the growth of 2D and layered semiconductors and heterostructures, combined with local spectroscopic measurements of quasiparticles excited at the nanometer scale. An integral part of the research has been the development of novel experimental approaches, both for in-situ microscopy of synthesis and for nanometer-scale spectroscopy. In particular, advanced techniques were developed for cathodoluminescence in scanning transmission electron microscopy (STEM-CL) where a nanometer-focused electron beam is used to locally excite electron-hole pairs, excitons, as well as propagating hybrid light-matter modes such as exciton-polaritons. Experiments were guided and analyzed via computations of structure, chemistry, and excitation spectra. The particular materials focus has been on group IV chalcogenides, a family of less explored 2D/layered semiconductors whose diversity in crystal structure and properties promises access to novel materials architectures and the discovery of phenomena that can support emerging technology needs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exploring natural aerosol formation from DMS oxidation and implications for aerosol forcing (Final Technical Report)

Because of their interactions with sunlight and with clouds, aerosol particles in the atmosphere can play an important role in the Earth’s climate. Understanding this role, and climate change in general, requires understanding the sources of these aerosol particles – not only anthropogenic sources (such as particles emitted from fossil fuel combustion) but also natural sources as well. One of the most important natural aerosol sources is the atmospheric oxidation of dimethyl sulfide (DMS). DMS, a gas emitted by oceanic phytoplankton, is the largest natural source of sulfur to the atmosphere. Once in the air it undergoes natural oxidation processes, converting the sulfur into sulfate, a major component of atmospheric aerosol. However, the chemical mechanism by which DMS oxidation forms sulfate particles is highly complex and uncertain. The goal of this project was therefore to better understand the chemistry of DMS oxidation, via laboratory and global-modeling studies. In the laboratory studies, DMS was oxidized in an environmental chamber (a large Teflon bag surrounded by UV lights to simulate sunlight), under a range of atmospheric conditions. A number of instruments were used to measure the reaction products (gases and particles) within the chamber. The total sulfur in the products equaled the sulfur in the reacted DMS, indicating that all major sulfur-containing species were measured. Yields of these products, and rates of important processes within the mechanism, were determined, providing improved parameters for use in chemical mechanisms. On the global modeling side, a detailed DMS oxidation scheme (that included chemistry occurring in both the gas phase and in cloud droplets) was incorporated into the Community Earth System Model (CESM), and the effects of this more complex mechanism on predicted sulfate levels and climate effects were explored. The expanded chemistry scheme was found to increase global sulfate levels under present-day conditions (~9%) and even more substantially (~30%) under preindustrial conditions. This additional predicted sulfate has implications for our understanding of the role of present-day aerosol pollution on climate, though because of in-cloud chemistry this effect is quite complex, highlighting the need for additional study.

54 ENVIRONMENTAL SCIENCES↗