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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:54.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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SBIR/STTR Programs
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:22:21.000Z<p>The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.</p><p><strong>The SBIR and STTR programs have 3 phases</strong>:</p><ul><li><strong>Phase I</strong> is the opportunity to establish the scientific, technical, and commercial feasibility of the proposed innovation in fulfillment of NASA needs.</li><li><strong>Phase II</strong> is focused on the development, demonstration and delivery of the proposed innovation.</li></ul><p>The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.</p><ul><li><strong>Phase III</strong> is the commercialization of innovative technologies, products, and services resulting from either a Phase I or Phase II contract. Phase III contracts are funded from sources other than the SBIR and STTR programs and may be awarded without further competition.</li></ul><p><strong>Opportunity for Continued Technology Development Post-Phase II</strong>:</p><p>The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.&nbsp;</p><p><strong>Please review the links below to obtain more information on the SBIR/STTR programs.</strong></p><ul><li><strong><a target="_blank" href="http://sbir.gsfc.nasa.gov/sites/default/files/ParticipationGuide.pdf">Participation Guide</a></strong></li></ul><p>Provides an overview of the SBIR and STTR programs as implemented by NASA</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/solicitations">Program Solicitations</a></strong></li></ul><p>Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/prg_sched_anncmnt">Schedule and Awards</a></strong></li></ul><p>Schedule and links for the SBIR/STTR solicitations and selection announcements</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/content/additional-sources-assistance">Sources of Assistance</a></strong></li></ul><p>Federal and non-Federal sources of assistance for small business</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/abstract_archives">Awarded Abstracts</a></strong></li></ul><p>Search our complete archive of awarded project abstracts to learn about what NASA has funded</p><ul><li><strong><a href="http://sbir.gsfc.nasa.gov/content/frequently-asked-questions">Frequently Asked Questions</a></strong></li></ul><p>&nbsp;Still have questions? Visit the program FAQs</p>
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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:54.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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GPM, DPR, GMI Level 3 Combined Monthly Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:55.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product. ABSTRACTThe purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1) – Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). • count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. • mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. • stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. • hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) – Conditional mean rate for liquid precipitation. • count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. • mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. • stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. • hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) – Conditional mean water content for all precipitation phases. • count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. • mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. • stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. • hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) – Conditional mean liquid water content. • count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. • mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. • stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. • hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) – Conditional mass-weighted mean particle diameter. • count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. • mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. • stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. • hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) – Conditional mean total surface precipitation rate indexed by local time. • count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. • mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. • stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of ...
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Live From Space Station Outreach Payload Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:32:19.000ZThe Live from Space Station? Outreach Payload (LFSSOP) is a technologically challenging, exciting opportunity for university students to conduct significant research in the biological or physical sciences culminating in a university student built payload that is launched and placed on the International Space Station. Experiment features will be accessed and controlled by high school students via a Live From Space Station? (LFSS) Internet computer interface. A national competition for university students will be implemented to award the payload contract. A separate national competition designed for elementary students will be initiated to help the university awardee name their payload. Museums and science centers will be the LFSSOP curriculum dissemination and training sites, as well as public outreach sites intended to intrigue and excite individuals of all ages. Exhibit kiosks running LFSS systems data, audio, video and student payload-related computer interfaces will stimulate public interest in the space sciences and the uniqueness of on-orbit research. Further, the excitement of working on a scientific problem, devising a payload to collect data, and analyzing results to prove a theory that will contribute to the body of knowledge in the biological or physical sciences will motivate and inspire students to study math and science.
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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:53.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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Think Tek Learning Lab Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:32:40.000ZSteven Winter Associates, Inc. (SWA) proposes to develop a nation-wide informal technology education program that integrates math, science, engineering and technology (STEM) through its Think Tek Learning Lab. The goal of the Lab is three-pronged: providing an after-school enrichment program for teens; arousing interest in math and science; and achieving outreach for NASA commercial technologies. The Lab will serve middle/high school students through after-school and Saturday classes, summer institutes, and school visits. The focus of this informal technology learning laboratory includes hands-on experimentation and exploration, design and construction, and interaction with a variety of technologies, scientists, and learning materials. The Lab will be a living NASA outreach spin-off with experiments that showcase real-life NASA commercial technologies. The project will support NASA's efforts to publicize the positive ripple effects that the space funding generates on the domestic front.
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Heated Thermoplastic Fiber Placement Head for NASA Langley Research Center Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:29:25.000ZReduced mass composite materials are crucial to the success of aerospace systems, but are inhibited by expensive autoclave consolidation, especially for large parts. To remedy this, NASA-LaRC has been developing cost-effective high-performance thermoplastic composite materials for years. NASA materials could dramatically reduce the cost of large aerospace structures, because those materials avoid the autoclave. However, NASA lacks a robust, cost-effective fabrication process to tow-place these emerging materials into laminates, and thus can?t evaluate their usefulness to industry. This program develops for NASA-LaRC the processing equipment that allows material evaluation and allows out-of-autoclave fiber placement. In particular, this program will deliver a heated in situ deposition head to fit on NASA-LaRCs placement machine. Heads can also be sold to industrial companies for existing placement machines so that aerospace composites can be fabricated out of the autoclave. In phase I, the deposition head will be designed and reviewed with NASA. The process window requirements for the placement head for NASA materials will be verified. In phase II, we will complete the design, fabricate, install, and prove-out the head equipment. We then start up the deposition head at NASA so that the emerging NASA-LaRC materials can be proven in laminates.
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INVESTIGATION OF NON ERODING NOZZLE MATERIALS FOR OPTIMIZED COATED HYBRID LEADING EDGE DESIGNS FOR REUSABLE LAUNCH VEHICALS WITH LEADING EDGE RADII OF 0.03? TO 1? AND TEMPERATURES NEAR 4000?F Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:32:08.000ZEffort explores using innovative hybrid reinforced carbon-carbon, refractory ceramics, super alloys and composite materials as thermal protection system specifically in the 4000?F range with leading edge radii of between 0.03? and 1.0?. The RLV leading edge is the primary TPS that space vehicles use re-entering the atmosphere traveling at hypersonic speeds. Depending on the Mach number spacecraft surface temperatures are as high 4000?F. The shape of the RLV leading edge, primarily the radius affects the functionality of the spacecraft including RLV drag, lift and leading edge aero-thermal heating. Sharper leading edges create lift and re-entry cross range capabilities. The downside of sharp leading edges is that aero-thermal heating is increased, resulting in steep thermal gradients. These thermal gradients create high thermal stresses. Blunt leading edges leading edges have less thermal gradient and therefore thermal stresses are lower. However, the cross range capabilities of the vehicle are reduced. Tasks include parametric definition of hybrid composite material architectures RLV leading edge for maximum lift, cross range and durability at temperatures of 4000?F for radii in the 0.03 to 1? range. The goal is finding the optimal hybrid composite material combinations/coatings and architectures for given leading edge radii. RLV. Analyses for hybrid leading edge designs include: Micro-mechanical material computations for hybrid material property, calculation of leading edge aerothermal heating heat transfer coefficient, heat rate and pressure load as a function of leading edge radius. Transient heat transfer analyses for calculation of leading edge thermal gradients. Thermal stress analyses using temperature gradients. Evaluation of leading edge response, as a function of hybrid material architecture via material failure ratios. The result of these analyses will provide the best hybrid material candidates and RLV leading edge designs.
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High Energy Density Li-Ion Batteries Designed for Low Temperature Applications Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:09:38.000ZThe state-of-the-art Li-ion batteries do not fully meet the energy density, power density and safety requirements specified by NASA for future exploration missions. Building upon our Phase I feasibility study, we propose to implement an advanced cathode material in practical Li-ion batteries. The cathode material offers superior electrochemical performance over its commercially used counterpart, particularly in terms of discharge capacity and energy density. In Phase I, working in collaboration with a leading university-based researcher, we demonstrated that intrinsic modifications in the crystal structure, and extrinsic modifications on the surface of cathode particles, can lead to energy densities greater than 1150 Wh/kg at room temperature and 800 Wh/kg at zero degrees C for the cathode powder. In the Phase II program, we intend to combine the intrinsic and extrinsic effects in the cathode material, which will deliver the needed energy density at low temperatures, along with other desirable attributes. This will represent a significant advancement of the state-of-the-art in cathode materials. The structural and morphological modifications introduced in the material will allow us to (i) maintain high energy and power density at low temperature (ii) lower the irreversible capacity loss and improve the efficiency, and (iii) further stabilize and enhance the safety of the cell. In Phase II, our university-based collaborator will fabricate and test small Li-ion pouch cells, which will help optimize the cathode material. In addition, prototype Li-ion cells with a capacity of ~ 5Ah will be fabricated and tested by a large Li-ion battery manufacturer and supplier to the aerospace industry. Further, a NASA prime contractor has offered to guide the Phase II program. The outcome of a successful Phase II program will be the demonstration of an advanced and robust energy storage system that can be used for future NASA applications.