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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Deep Impact comet encounter: design, development, and operations of the big event at Tempel 1

Deep Impact is NASA's eighth Discovery mission. This low-cost, focused planetary science investigation gathered the data necessary to help scientists unlock early secrets of our solar system. The comet encounter with Tempel 1 was a complex event - requiring extremely accurate timing, robustness to an unknown environment, and flight team adaptibility. The mission operations and flight systems performance were spectacular for approach, impact, and lookback imaging on July 4, 2005.

sequence design↗
NASA NTRS2005

Deep Impact comet encounter: design, development, and operations of the Big Event at Tempel 1

Deep Impact is NASA's eighth Discovery mission. This low-cost, focused planetary science investigation gathered the data necessary to help scientists unlock early secrets of our solar system. The comet encounter with Tempel 1 was a complex event - requiring extremely accurate timing, robutstness to an unknown environment, and flight team adaptability. The mission operations and flight systems performance were spectacular for approach, impact, and lookback imaging on July 4, 2005.

encounter↗
DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Using Likwid and Byfl to Benchmark Hardware Performance

This paper outlines a benchmarking study conducted during my internship at LANL, focusing on CPU (Computer Processing Unit) and program performance assessment. The primary goal was to gather memory access data using three methods across five polybench kernels The data gathered would then be used to compare and contrast to one another and calculate operational intensity for performance comparisons. Benchmarking tools like Byfl and Likwid were employed, with Byfl offering hardware-independent data through LLVM compiler communication and Likwid directly interacting with computer hardware. The study considered various benchmarking factors, including optimization levels, Big O notation ((n)), CPU diversity and specific kernel equations. Big O notation was utilized to simplify code complexity, with detailed breakdwons of operations and memory components for each polybench application. Specific O(n) equations enabled nuanced kernel compariosns, facilitating the identification of performance variations. CPU efficiency assessments were conducted using Likwid tests on two CPUs. The central focus on code optimization aimed at achieving higher speeds and reduced memory usage through streamlined code. Future work propsoes creating a roofline model, synthesizing benchmarking data into a comprehensive data graph to assist in optimizing code and improving hardware performance. The potential impact on the laboratory or national mission was underscored, emphasizing the importance of optimizing applications and hardware to conserve resources and accelerate program execution. The specific relevance to LANL’s operations in math-intensive fields such as Nuclear Fission, Space Exploration, and Nanotechnology highlights the necessity of efficient benchmarking for resource conservation and proram speed. Overall, this study contributes to the understanding of CPU and program performance, providing insights for future optimization efforts in a laboratory setting

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

Satellite cloud climatology of summertime cumulus research areas

Defense Meteorological Satellite Program data available for the summer of 1974 was used to construct a cloud climatology of areas where weather modification experiments are currently being conducted or planned; the three High Plains Experiment sites at Colby, Kansas, Big Springs, Texas, and Miles City, Montana; South Park, Colorado, where the South Park Area Cumulus Experiment is being conducted; and the National Hail Research Experiment area in northeastern Colorado. Digital data tapes were produced from the transparencies, obtained from the sun-synchronous polar-orbiting satellite passing over the study areas at about 1200 local time, and a computer analysis was carried out, producing areas and numbers of clouds for each area and day as well as providing data for cumulative averages over selected time periods for each study area.

Stodt, R. W.↗
DOE OSTI2018

Machine Learning to Improve Retrieval by Category in Big Volunteered Geodata

Nowadays, Volunteered Geographic Information (VGI) is commonly used in research and practical applications. However, the quality assurance of such a geographic data remains a problem. In this study we use machine learning and natural language processing to improve record retrieval by category (e.g. restaurant, museum, etc.) from Wikimapia Points of Interest data. We use textual information contained in VGI records to evaluate its ability to determine the category label. The performance of the trained classifier is evaluated on the complete dataset and then is compared with its performance on regional subsets. Preliminary analysis shows significant difference in the classifier performance across the regions. Such geographic differences will have a significant effect on data enrichment efforts such as labeling entities with missing categories.

Sorokine, Alexandre↗
NASA NTRS2010

Sonic Booms on Big Structures (SonicBOBS) Phase I Database; NASA Dryden Sensors

This DVD contains 13 channels of microphone and up to 22 channels of pressure transducer data collected in September, 2009 around several buildings located at Edwards Air Force Base. These data were recorded by NASA Dryden. Not included are data taken by NASA Langley and Gulfstream. Each day's data is in a separate folder and each pass is in a file beginning with "SonicBOBS_" (for microphone data) or "SonicBOBSBB_" (for BADS and BASS data) followed by the month, day, year as two digits each, followed by the hour, minute, sec after midnight GMT. The filename time given is for the END time of the raw recording file. In the case of the microphone data, this time may be several minutes after the sonic boom, and is according to the PC's uncalibrated clock. The Matlab data files have the actual time as provided by a GPS-based IRIG-B signal recorded concurrently with the data. Microphone data is given for 5 seconds prior to 20 seconds after the sonic boom. BADS and BASS data is given for the full recording, 6 seconds for the BADS and 10 seconds for the BASS. As an example of the naming convention, file "SonicBOBS_091209154618.mat" is from September 12, 2009 at 15:46:18 GMT. Note that data taken on September 12, 2009 prior to 01:00:00 GMT was of the Space Shuttle Discovery (a sonic boom of opportunity), which was on September 11, 2009 in local Pacific Daylight Time.

Haering, Edward A., Jr.↗
DOE OSTI2015

DETECTION OF SHOCK MERGING IN THE CHROMOSPHERE OF A SOLAR PORE

It was theoretically demonstrated that a shock propagating in the solar atmosphere can overtake another and merge with it. We provide clear observational evidence that shock merging does occur quite often in the chromosphere of sunspots. Using Hα imaging spectral data taken by the Fast Imaging Solar Spectrograph of the 1.6 m New Solar Telescope at the Big Bear Soar Observatory, we construct time–distance maps of line-of-sight velocities along two appropriately chosen cuts in a pore. The maps show a number of alternating redshift and blueshift ridges, and we identify each interface between a preceding redshift ridge and the following blueshift ridge as a shock ridge. The important finding of ours is that two successive shock ridges often merge with each other. This finding can be theoretically explained by the merging of magneto-acoustic shock waves propagating with lower speeds of about 10 km s{sup −1} and those propagating at higher speeds of about 16–22 km s{sup −1}. The shock merging is an important nonlinear dynamical process of the solar chromosphere that can bridge the gap between higher-frequency chromospheric oscillations and lower-frequency dynamic phenomena such as fibrils.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

MO-FG-213-04: Managing the Relationship

Academic-industrial collaborations are playing an increasingly prominent role in medical physics research. Successful partnerships have enabled truly translational, benchtop-to-bedside research that has significantly and positively impacted our field. Given the current flat or depleting trends in federal funding, and the increasing emphasis in the medical physics community on demonstrating translatability, efficacy, and safety prior to widespread clinical use, it is anticipated that such partnerships will become ever more important in advancing our field. In the future, it is likely that neither academia alone, nor industry alone, will be able to bring significant innovation to successfully impact patient care in radiotherapy. Such innovation will require partnership and symbiosis through the lifetime of the project. This symposium is aimed at professionals from academia and the industry who are interested in either initiating new collaborations or maintaining and improving existing partnerships. We will hear from four thought leaders from industry and academia on critical aspects of building and maintaining successful academic-industrial research partnerships. The following topics will be addressed: 1. Motivations: The industry perspective [Kevin Brown, Elekta] What goes into the development of a company’s R&D roadmap What are the motivations and expectations of the industry from academic partners How can academics make a successful pitch by identifying projects aligned with a company’s roadmap Why are some relationships successful and some not Milestones and progress reports - Why do we need them 2. Motivations: The academic perspective [T. Rock Mackie, Univ. of Madison, WI; Tomotherapy] What are the motivations and expectations of academic partners from the industry What are the cultural differences in academia vs industry on sharing information, exchanging ideas Partnership or entrepreneurship? When does each option make sense 3. Industrial Grants and Research Contracts – a Primer [Norbert Pelc; Stanford University] What topics are suited to industrial grants vs. academic grants How do resources (personnel effort, tuition) get allocated and charged in academia What are reasonable resource and timeline requests for small and big projects; from small and big companies “Fair market value” considerations Sections of a research agreement (IP including software confidential information, publications, data, exclusivity, support) 4. Managing the relationship [John Wong, Johns Hopkins University] How to effectively collaborate with each other How to adapt to changes in the relationship How to renew funding with the industry Moderated Panel Discussion [All speakers + moderators] Learning Objectives: 1. Understand the motivations of each partner 2. Elements that contribute to a successful partnership 3. Avoiding pitfalls - Challenges on either side that may derail a project 4. How to frame a research grant and agreement 5. How to sustain the collaborative relationship Amit Sawant: Funding from: NIH. Varian, Elekta and VisionRT; Michelle Svatos: Employee and shareholder: Varian, Board Member, TopasMC; Kevin Brown: Employee, Elekta; T. Rock Mackie: Consultant, Accuray; Norbert Pelc: Research support: Philips Healthcare, GE Healthcare; John Wong: Funding from NIH, Xstrahl and Elekta. Co-founder and advisor for JPLC Associates, LLC.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1981

Applications of digital image analysis capability in Idaho

The use of digital image analysis of LANDSAT imagery in water resource assessment is discussed. The data processing systems employed are described. The determination of urban land use conversion of agricultural land in two southwestern Idaho counties involving estimation and mapping of crop types and of irrigated land is described. The system was also applied to an inventory of irrigated cropland in the Snake River basin and establishment of a digital irrigation water source/service area data base for the basin. Application of the system to a determination of irrigation development in the Big Lost River basin as part of a hydrologic survey of the basin is also described.

Johnson, K. A.↗
NASA NTRS1981

LANDSAT demonstration/application and GIS integration in south central Alaska

Automated geographic information systems were developed for two sites in Southcentral Alaska to serve as tests for both the process of integrating classified LANDSAT data into a comprehensive environmental data base and the process of using automated information in land capability/suitability analysis and environmental planning. The Big Lake test site, located approximately 20 miles north of the City of Anchorage, comprises an area of approximately 150 square miles. The Anchorage Hillside test site, lying approximately 5 miles southeast of the central part of the city, extends over an area of some 25 square miles. Map construction and content is described.

Burns, A. W.↗
DOE OSTI2014

Big Explosives Experimental Facility - BEEF

The Big Explosives Experimental Facility or BEEF is a ten acre fenced high explosive testing facility that provides data to support stockpile stewardship and other national security programs. At BEEF conventional high explosives experiments are safely conducted providing sophisticated diagnostics such as high speed optics and x-ray radiography.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Measurements of striae in CR+ doped YAG laser crystals

Striations in Czochralski (CZ) grown crystals have been observed in materials such as GaAs, silicon, photorefractive crystals used for data storage, potassium titanyl phosphate crystals and LiNbO3. Several techniques have been used for investigating these defects including electron microscopy, laser scanning tomography, selective photoetching, X-ray diffuse scattering, interference orthoscopy, laser interferometry and micro-Fourier transform infrared spectroscopy mapping. A 2mm thick sample of the material to be investigated is illuminated with light that is absorbed and non-absorbed by the ion concentration to be observed. The back surface of the sample is focused onto a solid-state image detector and images of the input beam and absorbed (and diffracted) beams are captured at two wavelengths. The variation of the coefficient of absorption asa function of distance on the sample can be derived from these measurements. A Big Sky Software Beamcode system is used to capture and display images. Software has been written to convert the Beamcode data files to a format that can be imported into a spreadsheet program such as Quatro Pro. The spreadsheet is then used to manipulate and display data. A model of the intensity map of the striae collected by the imaging system has been proposed and a data analysis procedure derived. From this, the variability of the attenuation coefficient alpha can be generated. Preliminary results show that alpha may vary by a factor of four or five over distances of 100 mu m. Potential errors and problems have been discovered and additional experiments and improvements to the experimental setup are in progress and we must now show that the measurement techniques and data analysis procedures provide 'real' information. Striae are clearly visible at all wavelengths including white light. Their basic spatial frequency does not change radically, at least when changing from blue to green to white light. Further experimental and theoretical work can be done to improve the data collection techniques and to verify the data analysis procedures.

Cady, Fredrick M.↗
DOE OSTI2014

Overview and highlights of the Spin Asymmetries of the Nucleon Experiment – SANE

The Spin Asymmetries of the Nucleon Experiment – SANE took data on inelastic and elastic inclusive and coincidence beam-target asymmetries in the Hall C facility at Jefferson Lab, detecting the scattered electrons with the large non-magnetic Big Electron Telescope Array – BETA and the High Momentum Spectrometer. The Continuous Electron Beam Accelerator Facility – CEBAF delivered polarized electrons that were incident on the U. of Virginia polarized proton target. An overview and selected examples of the wealth of collected data, extending from the elastic to the deep inelastic scattering regions, and spanning the four-momentum range from 0.8 to 6GeV{sup 2}, will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Big Fish in Small Ponds: massive stars in the low-mass clusters of M83

We have used multi-wavelength Hubble Space Telescope WFC3 data of the starbursting spiral galaxy M83 in order to measure variations in the upper end of the stellar initial mass function (uIMF) using the production rate of ionizing photons in unresolved clusters with ages ≤ 8 Myr. As in earlier papers on M51 and NGC 4214, the uIMF in M83 is consistent with a universal IMF, and stochastic sampling of the stellar populations in the ∼<10{sup 3} M {sub ☉} clusters are responsible for any deviations in this universality. The ensemble cluster population, as well as individual clusters, also imply that the most massive star in a cluster does not depend on the cluster mass. In fact, we have found that these small clusters seem to have an over-abundance of ionizing photons when compared to an expected universal or truncated IMF. This also suggests that the presence of massive stars in these clusters does not affect the star formation in a destructive way.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BiG-SLiCE 2 v1.0.0

BiG-SLiCE was originally an open source Python-based command line bioinformatics software that offers a highly scalable clustering analysis on biosynthetic gene clusters (BGC) data. It allows a simultaneous analysis of millions of BGCs, exceeding the capability of other existing tools (around one hundred thousands). As a tradeoff, the clustering accuracy is relatively lower and sometimes fall short in corner cases and specific BGC classes such as the RiPPs (Ribosomally-translated, Post-translationally modified Peptides). In BiG-SLiCE V2 (developed in LBNL), the clustering algorithm has been significantly improved to deliver a much accurate result even for RiPPs and other previous corner case classes. Moreover, the speed of the overall pipeline has been improved by 50-100%. Finally, additional features were implemented to support downstream analyses of BiG-SLiCE results, such as customized tabular (TSV/CSV) and columnar (Parquet) outputs.

Kautsar, Satria↗
DOE OSTI2016

A Dirichlet process mixture model for automatic {sup 18}F-FDG PET image segmentation: Validation study on phantoms and on lung and esophageal lesions

Purpose: The aim of this study was to implement a Dirichlet process mixture (DPM) model for automatic tumor edge identification on {sup 18}F-fluorodeoxyglucose positron emission tomography ({sup 18}F-FDG PET) images by optimizing the parameters on which the algorithm depends, to validate it experimentally, and to test its robustness. Methods: The DPM model belongs to the class of the Bayesian nonparametric models and uses the Dirichlet process prior for flexible nonparametric mixture modeling, without any preliminary choice of the number of mixture components. The DPM algorithm implemented in the statistical software package R was used in this work. The contouring accuracy was evaluated on several image data sets: on an IEC phantom (spherical inserts with diameter in the range 10–37 mm) acquired by a Philips Gemini Big Bore PET-CT scanner, using 9 different target-to-background ratios (TBRs) from 2.5 to 70; on a digital phantom simulating spherical/uniform lesions and tumors, irregular in shape and activity; and on 20 clinical cases (10 lung and 10 esophageal cancer patients). The influence of the DPM parameters on contour generation was studied in two steps. In the first one, only the IEC spheres having diameters of 22 and 37 mm and a sphere of the digital phantom (41.6 mm diameter) were studied by varying the main parameters until the diameter of the spheres was obtained within 0.2% of the true value. In the second step, the results obtained for this training set were applied to the entire data set to determine DPM based volumes of all available lesions. These volumes were compared to those obtained by applying already known algorithms (Gaussian mixture model and gradient-based) and to true values, when available. Results: Only one parameter was found able to significantly influence segmentation accuracy (ANOVA test). This parameter was linearly connected to the uptake variance of the tested region of interest (ROI). In the first step of the study, a calibration curve was determined to automatically generate the optimal parameter from the variance of the ROI. This “calibration curve” was then applied to contour the whole data set. The accuracy (mean discrepancy between DPM model-based contours and reference contours) of volume estimation was below (1 ± 7)% on the whole data set (1 SD). The overlap between true and automatically segmented contours, measured by the Dice similarity coefficient, was 0.93 with a SD of 0.03. Conclusions: The proposed DPM model was able to accurately reproduce known volumes of FDG concentration, with high overlap between segmented and true volumes. For all the analyzed inserts of the IEC phantom, the algorithm proved to be robust to variations in radius and in TBR. The main advantage of this algorithm was that no setting of DPM parameters was required in advance, since the proper setting of the only parameter that could significantly influence the segmentation results was automatically related to the uptake variance of the chosen ROI. Furthermore, the algorithm did not need any preliminary choice of the optimum number of classes to describe the ROIs within PET images and no assumption about the shape of the lesion and the uptake heterogeneity of the tracer was required.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Light sterile neutrinos in the early universe

Cosmological and terrestrial data suggests the number of light neutrinos may be greater than 3, motivating a careful reexamination of cosmological bounds on extra light species. Big bang nucleosynthesis constrains the number of relativistic neutrino species present during nucleosynthesis, N{sub eff}{sup BBN}, while measurements of the cosmic microwave background (CMB) angular power spectrum constrain the effective energy density in relativistic neutrinos at the time of matter-radiation equality, N{sub eff}{sup CMB}. We review a scenario with two sterile neutrinos and explore whether partial thermalization of the sterile states can ease the tension between cosmological constraints on N{sub eff}{sup BBN} and terrestrial data. We conclude that, still, two additional light sterile neutrinos species cannot fit all the data at the 95% confidence level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗