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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On the Solution of ℓ 0 -Constrained Sparse Inverse Covariance Estimation Problems

The sparse inverse covariance matrix is used to model conditional dependencies between variables in a graphical model to fit a multivariate Gaussian distribution. Estimating the matrix from data are well known to be computationally expensive for large-scale problems. Sparsity is employed to handle noise in the data and to promote interpretability of a learning model. Although the use of a convex ℓ 1 regularizer to encourage sparsity is common practice, the combinatorial ℓ 0 penalty often has more favorable statistical properties. In this paper, we directly constrain sparsity by specifying a maximally allowable number of nonzeros, in other words, by imposing an ℓ 0 constraint. Here, we introduce an efficient approximate Newton algorithm using warm starts for solving the nonconvex ℓ 0 -constrained inverse covariance learning problem. Numerical experiments on standard data sets show that the performance of the proposed algorithm is competitive with state-of-the-art methods.

$\ell_0$-Constrained↗
DOE OSTI2018

Evaluating Trade-offs in Potential Exascale Interconnect Topologies

This study looks at the high-level trade-offs for interconnect architectures that are likely to be available in HPC machines in the 2021-2022 timeframe. The study uses multiple simulation models to look at the effects of varying machine size, injection bandwidth and topology for a selected set of benchmark communication patterns. The studies show the sensitivity of various applications to these network parameters. This study can help inform decisions on node size versus number of nodes, which topology is most efficient for our applications, how much injection bandwidth to provision, etc. These simulations only look at interconnects with maximally configured global bandwidth, and studies of networks configured with less will be the subject of future milestones.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Co-Optimization of Fuels & Engines: FY18 Year in Review

The U.S. Department of Energy (DOE) Co-Optima initiative is accelerating the introduction of efficient, clean, affordable, and scalable high-performance fuels and engines. This first-of-its-kind effort is simultaneously tackling fuel and engine research and development (R&D) to maximize light-, medium-, and heavy-duty vehicle fuel economy and performance, while mapping lower-cost pathways to reduce emissions, leveraging diverse domestic fuel resources, boosting U.S. economic productivity, and enhancing national energy security. Co-Optima brings together DOE’s Office of Energy Efficiency & Renewable Energy (EERE), nine national laboratories, 13 universities, and numerous industry and government stakeholders in a collaboration exploring solutions with potential for near-term improvements to the types of fuels and engines found in most vehicles currently on the road, as well as potential for the development of revolutionary new engine technologies. An overview is provided of the research activities and accomplishments of the Co-Optima initiative during the 2018 Fiscal Year.

02 PETROLEUM↗
DOE OSTI2023

Accelerating Additive Manufacturing Process Design for Energy Conversion Materials using In-situ Sensing and Machine Learning

One promising candidate for manufacturing of the bismuth Telluride thermoelectric legs is laser powder bed fusion (LPBF) additive Manufacturing (AM). AM processing parameters highly influence the material properties, however current processing parameter development methods in AM are costly and time consuming. In-situ sensors allow for the capture of physically relevant process information on a layer-by-layer basis and will be used to aide process development. To optimize the AM process for the best thermoelectric performance, process variables, in-situ process sensor data and ex-situ material characterization data are collected. Several different interpretable machine learning (ML) approaches are used, and the performance of each method are assessed. Significant input process variables include laser focus, hatch spacing and laser power. The best performing models are used to determine the manufacturing parameters that maximize the power factor. AM of bismuth telluride material provides the ability to create complex geometries enabling more efficient energy conversion.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Flexible Fully-Decoupled Nuclear Plants with Thermal Energy Storage - Technoeconomic Optimization

New nuclear power plants may be one of the technologies for future zero carbon electricity production. These future systems will however also need significant flexibility to cope with fluctuating demand and large share of intermittent renewable supply, rather than running in conventional baseload generation. The present work explores the use of thermal energy storage (TES) as a buffer between the reactor heat and its conversion to electricity, enabling flexible operation of nuclear plants. The focus is on maximizing flexibility, ideally as full decoupling of the nuclear and power cycle islands, as well as on system efficiency in various modes. A system design presented for a high temperature gas cooled reactor (HTGR) presents a slightly complex solution, as separate high- and low-temperature TES systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation and system control. A technoeconomic analysis, furthermore, provides sizing and costing of the component, followed by size and dispatch economic optimization considering energy arbitrage. This optimization shows that in all explored markets, the addition of TES system with the proposed configuration results in positive impact on project net present value. Further sensitivity analyses show impact of multiple inputs and possible technical limitations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Fan, Ruidong↗
NASA NTRS1981

Orbital operations with the Shuttle Infrared Telescope Facility /SIRTF/

The Shuttle Infrared Telescope Facility (SIRTF) is a cryogenically-cooled, 1-m-class telescope that will be operated from the Space Shuttle as an observatory for infrared astronomy. This paper discusses the scientific constraints on and the requirements for pointing and controlling SIRTF as well as several aspects of SIRTF orbital operations. The basic pointing requirement is for an rms stability of 0.25 arcsec, which is necessary to realize the full angular resolution of the 5-micron diffraction-limited SIRTF. Achieving this stability requires the use of hardware and software integral to SIRTF working interactively with the gyrostabilized Shuttle pointing-mount. The higher sensitivity of SIRTF, together with orbital and time constraints, puts a premium on rapid target acquisition and on efficient operational and observational procedures. Several possible acquisition modes are discussed, and the importance of source acquisition by maximizing the output of an infrared detector is emphasized.

Werner, M. W.↗
NASA NTRS1985

Space shuttle main engine: Interactive design challenges

The operating requirements established by NASA for the SSME were considerably more demanding than those for earlier rocket engines used in the military launch vehicles or Apollo program. The SSME, in order to achieve the high performance, low weight, long life, reusable objectives, embodied technical demands far in excess of its predecessor rocket engines. The requirements dictated the use of high combustion pressure and the staged combustion cycle which maximizes performance through total use of all propellants in the main combustion process. This approach presented a myriad of technical challenges for maximization of performance within attainable state of the art capabilities for operating pressures, operating temperatures and rotating machinery efficiencies. Controlling uniformity of the high pressure turbomachinery turbine temperature environment was a key challenge for thrust level and life capability demanding innovative engineering. New approaches in the design of the components were necessary to accommodate the multiple use, minimum maintenance objectives. Included were the use of line replaceable units to facilitate field maintenance automatic checkout and internal inspection capabilities.

Mccarty, J. P.↗
NASA NTRS1997

Electrical and Optical Performance Characteristics of 0.74-eV p/n InGaAs Monolithic Interconnected Modules

There has been a traditional trade-off in thermophotovoltaic (TPV) energy conversion development between system efficiency and power density. This trade-off originates from the use of front surface spectral controls such as selective emitters and various types of filters. A monolithic interconnected module (MIM) structure has been developed which allows for both high power densities and high system efficiencies. The MIM device consists of many individual indium gallium arsenide (InGaAs) cells series-connected on a single semi-insulating indium phosphide (InP) substrate. The MIM is exposed to the entire emitter output, thereby maximizing output power density. An infrared (IR) reflector placed on the rear surface of the substrate returns the unused portion of the emitter output spectrum back to the emitter for recycling, thereby providing for high system efficiencies. Initial MIM development has focused on a 1 sq cm device consisting of eight (8) series interconnected cells. MIM devices, produced from 0.74-eV InGaAs, have demonstrated V(sub oc) = 3.2 volts, J(sub sc) = 70 mA/sq cm, and a fill factor of 66% under flashlamp testing. Infrared (IR) reflectance measurements (greater than 2 micron) of these devices indicate a reflectivity of greater than 82%. MIM devices produced from 0.55-eV InGaAs have also been demonstrated. In addition, conventional p/n InGaAs devices with record efficiencies (11.7% AM0) have been demonstrated.

Wilt, David M.↗
NASA NTRS1997

Electrical and Optical Performance Characteristics of p/n InGaAs Monolithic Interconnected Modules

There has been a traditional trade-off in ThermoPhotoVoltaic (TPV) energy conversion development between system efficiency and power density. This trade-off originates from the use of front surface spectral controls such as selective emitters and various types of filters. A Monolithic Interconnected Module (MIM) structure has been developed which allows for both high power densities and high system efficiencies. The MIM device consists of many individual Indium Gallium Arsenide (InGaAs) devices series-connected on a single semi-insulating Indium Phosphide (InP) substrate. The MIMs are exposed to the entire emitter output, thereby maximizing output power density. An InfraRed (IR) reflector placed on the rear surface of the substrate returns the unused portion of the emitter output spectrum back to the emitter for recycling, thereby providing for high system efficiencies. Initial MIM development has focused on a 1 sq cm device consisting of eight (8) series interconnected cells. MIM devices, produced from 0.74eV InGaAs, have demonstrated V(sub infinity) = 3.2 volts, J(sub sc) = 70 mA/sq cm and a fill factor of 66% under flashlamp testing. IR reflectance measurements (greater than 2 microns) of these devices indicate a reflectivity of greater than 82%. MIM devices produced from 0.55 eV InGaAs have also been demonstrated. In addition, conventional p/n InGaAs devices with record efficiencies (11.7% AM0) have been demonstrated.

Wilt, David M.↗
NASA NTRS2001

A Global Optimization Methodology for Rocket Propulsion Applications

While the response surface method is an effective method in engineering optimization, its accuracy is often affected by the use of limited amount of data points for model construction. In this chapter, the issues related to the accuracy of the RS approximations and possible ways of improving the RS model using appropriate treatments, including the iteratively re-weighted least square (IRLS) technique and the radial-basis neural networks, are investigated. A main interest is to identify ways to offer added capabilities for the RS method to be able to at least selectively improve the accuracy in regions of importance. An example is to target the high efficiency region of a fluid machinery design space so that the predictive power of the RS can be maximized when it matters most. Analytical models based on polynomials, with controlled level of noise, are used to assess the performance of these techniques.

Source record↗
NASA NTRS2002

Design and architecture of the Mars relay network planning and analysis framework

In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

Mars relay network planning analysis↗
NASA NTRS2008

AutoBayes Program Synthesis System Users Manual

Program synthesis is the systematic, automatic construction of efficient executable code from high-level declarative specifications. AutoBayes is a fully automatic program synthesis system for the statistical data analysis domain; in particular, it solves parameter estimation problems. It has seen many successful applications at NASA and is currently being used, for example, to analyze simulation results for Orion. The input to AutoBayes is a concise description of a data analysis problem composed of a parameterized statistical model and a goal that is a probability term involving parameters and input data. The output is optimized and fully documented C/C++ code computing the values for those parameters that maximize the probability term. AutoBayes can solve many subproblems symbolically rather than having to rely on numeric approximation algorithms, thus yielding effective, efficient, and compact code. Statistical analysis is faster and more reliable, because effort can be focused on model development and validation rather than manual development of solution algorithms and code.

Schumann, Johann↗
DOE OSTI2019

Co-Optimization of Fuels & Engines: FY18 Year in Review

The U.S. Department of Energy (DOE) Co-Optima initiative is accelerating the introduction of efficient, clean, affordable, and scalable high-performance fuels and engines. This first-of-its-kind effort is simultaneously tackling fuel and engine research and development (R&D) to maximize light, medium, and heavy-duty vehicle fuel economy and performance, while mapping lower-cost pathways to reduce emissions, leveraging diverse domestic fuel resources, boosting U.S. economic productivity, and enhancing national energy security. Co-Optima brings together DOE's Office of Energy Efficiency & Renewable Energy (EERE), nine national laboratories, 13 universities, and numerous industry and government stakeholders in a collaboration exploring solutions with potential for near-term improvements to the types of fuels and engines found in most vehicles currently on the road, as well as potential for the development of revolutionary new engine technologies.

09 BIOMASS FUELS↗
DOE OSTI2024

Integrating Variable Renewable Energy Into the Grid: Key Issues

To foster sustainable, low-emission development, many countries are establishing ambitious renewable energy targets for their electricity supply. The variability of solar and wind compared to traditional sources, coupled with growing demand for electricity, requires changes to power system planning and operations to meet these targets. Grid integration is the practice of developing efficient ways to deliver variable renewable energy (VRE), primarily wind and solar, to the grid. Good integration methods maximize the cost-effectiveness of incorporating VRE while maintaining or increasing system stability and reliability. To inform decarbonization strategies, policymakers, regulators, and system operators consider a variety of costs and opportunities associated with VRE integration, which can be organized into five topics: New renewable energy generation and transmission; Power system reliability; Transmission and distribution coordination; Cross-sectoral decarbonization opportunities; Energy equity and justice.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE

As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

High-performance broadband optical coatings on InGaN/GaN solar cells for multijunction device integration

We demonstrate InGaN/GaN multiple quantum well solar cells grown by metalorganic chemical vapor deposition on a bulk (0001) substrate with high-performance broadband optical coatings to improve light absorption. A front-side anti-reflective coating and a back-side dichroic mirror were designed to minimize front surface reflections across a broad spectral range and maximize rear surface reflections only in the spectral range absorbed by the InGaN, making the cells suitable for multijunction solar cell integration. Application of optical coatings increased the peak external quantum efficiency by 56% (relative) and conversion efficiency by 37.5% (relative) under 1 sun AM0 equivalent illumination.

14 SOLAR ENERGY↗
DOE OSTI2019

A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering

Abstract Modern scientific instruments are acquiring data at ever-increasing rates, leading to an exponential increase in the size of data sets. Taking full advantage of these acquisition rates will require corresponding advancements in the speed and efficiency of data analytics and experimental control. A significant step forward would come from automatic decision-making methods that enable scientific instruments to autonomously explore scientific problems—that is, to intelligently explore parameter spaces without human intervention, selecting high-value measurements to perform based on the continually growing experimental data set. Here, we develop such an autonomous decision-making algorithm that is physics-agnostic, generalizable, and operates in an abstract multi-dimensional parameter space. Our approach relies on constructing a surrogate model that fits and interpolates the available experimental data, and is continuously refined as more data is gathered. The distribution and correlation of the data is used to generate a corresponding uncertainty across the surrogate model. By suggesting follow-up measurements in regions of greatest uncertainty, the algorithm maximally increases knowledge with each added measurement. This procedure is applied repeatedly, with the algorithm iteratively reducing model error and thus efficiently sampling the parameter space with each new measurement that it requests. We validate the method using synthetic data, demonstrating that it converges to faithful replica of test functions more rapidly than competing methods, and demonstrate the viability of the approach in an experimental context by using it to direct autonomous small-angle (SAXS) and grazing-incidence small-angle (GISAXS) x-ray scattering experiments.

36 MATERIALS SCIENCE↗