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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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In the past 6 years, the UW team have collaborated extensively with the Battery500 Consortium team members, including The Pacific Northwest National Lab, The Idaho National Lab, Binghamton University, and UT Austin. We have accomplished all milestones and deliverables at the end of the program.
Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).
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Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.
Liquid propellant rocket engine performance computer program with distributed energy release
Development of a computer program for analyzing the effects of bipropellant spray combustion processes on liquid rocket performance is described and discussed. The distributed energy release (DER) computer program was designed to become part of the JANNAF liquid rocket performance evaluation methodology and to account for performance losses associated with the propellant combustion processes, e.g., incomplete spray gasification, imperfect mixing between sprays and their reacting vapors, residual mixture ratio striations in the flow, and two-phase flow effects. The DER computer program begins by initializing the combustion field at the injection end of a conventional liquid rocket engine, based on injector and chamber design detail, and on propellant and combustion gas properties. It analyzes bipropellant combustion, proceeding stepwise down the chamber from those initial conditions through the nozzle throat.
A computer program for analyzing rocket engine performance was developed. The program is concerned with the formation, distribution, flow, and combustion of liquid sprays and combustion product gases in conventional rocket combustion chambers. The capabilities of the program to determine the combustion characteristics of the rocket engine are described. Sample data code sheets show the correct sequence and formats for variable values and include notes concerning options to bypass the input of certain data. A seperate list defines the variables and indicates their required dimensions.
A recently developed model predicts an energy dependent phase lag in the modulated cosmic ray density U(t) given by U(t) approximately equal to US (t - tau) where US is the solution to the Fokker-Planck equation under time independent conditions and tau is the average time spent by particles inside the modulating region. The delay times tau are functions of modulating parameters R (the radius of the modulating cavity), V (the solar wind velocity), and K (the effective average diffusion-coefficient which is a function of energy). This model is applied to predict the time evolution of the modulated cosmic ray proton spectrum over a simulated solar cycle. A modulation produced mostly by varying R over the solar cycle is less consistent with the observations.
Additions or revisions of components of the SIMWEST program are provided for insertion into the manual used with the UNIVAC 1100 series computer.
The origin of the X-ray emission observed from the DA white dwarf Sirius B is investigated on the basis of low-resolution short wavelength IUE spectrum. Following a correction for the influence of scattered light from Sirius A, the intensity distribution of Sirius B is obtained as a function of wavelength. Comparison of the continuous energy distribution with model atmosphere energy distributions indicates an effective temperature of 25,500 K, which is not high enough to explain the observed X rays as normal photospheric radiation. In addition, with the exception of an unusual feature in the neighborhood of the C I 1657 line, no clear evidence is found of emission lines indicative of a corona, chromosphere or disk, and the origin of the X rays remains unknown.
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Observed late A star energy distributions for the wavelength range 1400-2500 A are compared. No difference is found between energy distributions of Am stars and those of normal slowly rotating A stars. The fluxes of rapidly rotating stars, however, appear to be increased for wavelengths smaller than 1530 A; this cannot be understood as an effect of pole heating or reduced gravity. In addition, the comparison of the UV energy distributions with model atmosphere energy distributions of Kurucz indicates some problems with the theoretical Si I absorption edges at 1530 A.
The absolute visual magnitudes of main-sequence Cepheid companions are here determined from their effective temperatures. The latter are obtained by comparing the measured relative energy distributions with model atmosphere energy distributions. Assuming an average Galactic extinction law, it is found that the distance moduli for the Cepheids should be smaller by Delta (mv-Mv) = -0.5 as compared to the Sandage-Tammann relation.
The results of an integrated multidisciplinary and multiexperimental investigation, using data from the Skylab program, of metabolic adaptation to space flight are summarized and discussed. The effects of space flight on fluid-electrolyte regulation, mechanisms of hormone disturbances, energy balance, and the etiology of weight loss are emphasized. A composite picture of the fluid, electrolyte, and energy response to weightlessness, based primarily on data gathered from the nine Skylab crewmen, is presented.