- API data.nasa.gov | Last Updated 2019-06-03T15:17:07.000Z
This data set provides a time series of global peatland carbon balance and carbon dioxide emissions from land use change throughout the Holocene (the past 11,000 yrs). Global peatland carbon balance was quantified using a) a continuous net carbon balance history throughout the Holocene derived from a data set of 64 dated peat cores, and b) global model simulations with the LPX-Bern model hindcasting the dynamics of past peatland distribution and carbon balance. CO2 emissions from land-use change are based on published scenarios for anthropogenic land use change (HYDE 3.1, HYDE 3.2, KK10) covering the last 10,000 years. This combination of model estimates with CO2 budget constraints narrows the range of past anthropogenic land use change emissions and their contribution to past carbon cycle changes.
- API data.nasa.gov | Last Updated 2018-07-19T08:50:38.000Z
<p>Superconducting transition-edge sensors (TESs) are the state-of-the art technology for microcalorimeter and bolometer applications across the electromagnetic spectrum. We propose to design, fabricate, and test what we call a magnetically-tuned TES (or MTES). The leading theoretical TES physics understanding predicts our MTES concept will take the current state of the art TES and (1) Increase the signal, (2) Decrease the pulse recovery time, (3) Reduce the noise, and (4) Increase the energy resolving power.<br /> </p> <p>The magnetically-tuned TES (or MTES) takes characteristics that we have only recently come to understand are present and important in all state-of-the-art TES sensors and uses them in an interesting new combination. Magnetic tuning simply changes the resistive transition of the TES sensor.</p><p>Our research program will answer the following questions in turn. Does an MTES reduce the relative sensitivity of the resistive transition in current? Does a MTES reduce the relative sensitivity of the resistive transition in current while maintaining a large relative sensitivity of the resistive transition in temperature? Does the MTES resistive transition depart from the weak-link theoretical model and if so in what ways?</p>
- API data.nasa.gov | Last Updated 2018-07-19T11:12:30.000Z
NASA's strategic goals call for innovation in space technology for our nation's explorative future. Early phase paraffin fuel technology could enable practical hybrid motor use by producing high regression rates. Further, the creation of a robust and novel fuel, that overcomes paraffin mechanical property drawbacks, would produce high payoffs. The proposed research specifically will investigate polymer addition to paraffin grains, study the particle entrainment theory, evaluate hydride and metal additives, and demonstrate hypergolic ignition. We hope to find that polymers strengthen the low mechanical properties of paraffin. We will design, build, and demonstrate an experiment in which particle entrainment can be seen and understood. We will evaluate additives to increase performance and facilitate reliable and hypergolic ignition. Outreach to student run clubs and undergraduate engineers will also play an integral role demonstrating the promise of paraffin propellants through sounding rockets. A high performance paraffin based grain is a game-changing technology that could lead to the economical use of hybrid rockets.
- API data.nasa.gov | Last Updated 2018-07-19T07:01:57.000Z
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"> <p>Global measurements of wind speed and direction from Doppler wind lidars, if available, would significantly improve forecasting of severe weather events such as hurricanes, severe thunderstorms, volcanic plume transport, and smoke from wildfires. Doppler wind lidar have been successfully demonstrated on the ground and on aircraft, but the scanning telescopes traditionally used for Doppler wind lidars are too large and complex for operation in space. </p> <p>The Airborne Cloud-Aerosol Transport System (ACATS) is a high spectral resolution lidar (HSRL) and Doppler wind lidar instrument managed at GSFC that flies on the high-altitude NASA ER-2 aircraft. ACATS is one of only two airborne Doppler wind lidar instruments developed and maintained at GSFC, and it is the only one that provides simultaneous measurements of cloud/aerosol properties and wind speed/direction within these layers. The performance of both wind and HSRL measurements was impeded by poor instrument calibration during previous flights. Previous work has resulted in improved instrument calibration and extinction measurements within cloud and aerosols layers. This project will enable testing and modifications to the receiver subsystem and/or instrument software to improve the quality of wind measurements from ACATS, and will also support the exploration of a new innovative telescope design that is scalable to space.</p> <p>The objectives of this project are as follows:</p> <ol> <li>Determine how ACATS calibration improvements have impacted the accuracy of the wind measurements.</li> <li>Improve the quality of wind measurements from ACATS by modifying the receiver subsystem and/or instrument software.</li> <li>Ensure the ACATS instrument is ready for future flights on the ER-2 aircraft.</li> <li>Develop an innovative telescope concept for a space-based wind lidar mission.</li></ol> <p>The overall goal of this project is to demonstrate ACATS wind measurements and design an innovative telescope that can inform the development of a future satellite Doppler wind lidar mission. The tasks that will be completed to achieve the goals of this project are as follows:</p> <ol> <li>Test ACATS line-of-sight (LOS) wind measurements from the ground at GSFC and compare to nearby radiosonde data to determine accuracy with the new calibration technique.</li> <li>Modify the ACATS receiver subsystem and instrument software as necessary to further improve the accuracy of wind measurements.</li> <li>Work with external “think-tank” engineers to explore an innovative telescope concept for a space-based wind lidar mission.</li></ol> <p>These tasks will ensure that this proposal’s overall goals of readying ACATS for future field campaigns and demonstrating its scalability to space are met.</p>
- API data.nasa.gov | Last Updated 2018-07-19T20:33:24.000Z
We propose to develop Mg rockets for Martian ascent vehicle applications. The propellant can be acquired in-situ from MgO in the Martian regolith (5.1% Mg by mass) and combusted with H20 that exists at the poles and below the surface. The vacuum Isp of a Mg-H20 rocket would be ~300 s. Mg can also be combusted with CO2 condensed from the Martian atmosphere to yield Isp ~215 s. The technology can also be used on the Moon, where regolith is 5.5% Mg. Al-H20 rockets would also be enabled; like Mg, Al is present in Martian and Lunar regolith. In Phase I, we will prove the feasibility of Mg rockets. Chemical Equilibrium Analysis codes will be used to predict rocket performance at various operating conditions and O/F ratios. Combustion with CO2, H20, and pure O2 will be considered. Experiments will focus on developing and characterizing delivery, ignition and combustion systems, starting with ARL's existing Mg combustion system. Ways to achieve low temperature, electrolytic ignition and stable combustion will be studied. Drawing upon both experimental and theoretical results, we will then design a 5-10 N metal-water rocket system to be built and tested in Phase II.
- API data.nasa.gov | Last Updated 2018-07-19T04:29:06.000Z
This browse data consists of resampled data from the Low Energy Charged Particle (LECP) experiment on Voyager 2 while the spacecraft was in the vicinity of Uranus. This instrument measures the intensities of in-situ charged particles (>26 keV electrons and >30 keV ions) with various levels of discrimination based on energy, mass species, and angular arrival direction. A subset of almost 100 LECP channels are included with this data set. The LECP data are globally calibrated to the extent possible (see below) and they are time averaged to about 15 minute time intervals with the exact beginning and ending times for those intervals matching the LECP instrumental cycle periods (the angular scanning periods). The LECP instrument has a rotating head for obtaining angular anisotropy measurements of the medium energy charged particles that it measures. The cycle time for the rotation if variable, but during encounters it is always faster than 15 minutes. For this browse data set only scan average data is given (no angular information). The data is in the form of 'rate' data which has not been converted to the usual physical units. The reason is that such a conversion would depend on uncertain determinations such as the mass species of the particles and the level of background. Both mass species and background are generally determined from context during the study of particular regions. To convert 'rate' to 'intensity' for a particular channel one performs the following tasks: 1) decide on the level of background contamination and subtract that off the given rate level. Background is to be determined from context and from making use of sector 8 rates (sector 8 has a 2 MM al shield covering it). 2) divide the background corrected rate by the channel geometric factor and by the energy bandpass of the channel. The geometric factor is found in entry 'CHANNEL_GEOMETRIC_FACTOR' as associated with each channel 'CHANNEL_ID'. To determine the energy bandpass, one must judge the mass species of the of the detected particles (for ions but not for electrons). The energy band passes are given in entries 'MINIMUM_INSTRUMENT_PARAMETER' and 'MAXIMUM_INSTRUMENT_PARAMETER' in table 'FPLECPENERGY', and are given in the form 'ENERGY/NUCLEON'. For channels that begin their names with the designations 'CH' these bandpasses can be used on mass species that are accepted into that channel (see entries 'MINIMUM_INSTRUMENT_PARAMETER' and 'MAXIMUM_INSTRUMENT_ PARAMETER' in table 'FPLECPCHANZ', which give the minimum and maximum 'Z' value accepted -- these entries are blank for electron channels). For other channels the given bandpass refers only to the lowest 'Z' value accepted. The bandpasses for other 'Z' values are not all known, but some are given in the literature (e.g. Krimigis et al., 1979). The final product of these instructions will be the particle intensity with the units: counts/(cm**2.str.sec.keV). Some channels are subject to serious contaminations, and many of these contaminations cannot be removed except with a region-by-region analysis, which has not been done for this data. Thus, to use this data it is absolutely vital that the contamination types ('CONTAMINATION_ID' , 'CONTAMINATION_DESC') and the levels of contamination ('DATA_QUALITY_ID' corresponding to the definitions 'DATA_QUALITY_DESC') be carefully examined for all regions of study. A dead time correction procedure has been applied in an attempt to correct the linear effects of detector overdrive (Pulse-Pileup). This procedure does not fix severely overdriven detectors. A procedure is available for correcting Voyager 2 LECP electron contamination of low energy ion channels, but its effectiveness has been evaluated only for the Uranus data set. Thus, corrections have been applied only to the Uranus data set.
- API data.nasa.gov | Last Updated 2018-09-07T17:40:01.000Z
<p>In the latter half of the 20th century, microprocessors faithfully adhered to Moore’s law, the well-known formulation of exponentially improving performance. As Gordon Moore originally predicted in 1965, the density of transistors, clock speed, and power efficiency in microprocessors doubled approximately every 18 months for most of the past 60 years. Yet this trend began to languish over the last decade. A law known as Dennard scaling, which states that microprocessors would proportionally increase in performance while keeping their power consumption constant, has broken down since about 2006; the result has been a trade-off between speed and power efficiency. Although transistor densities have so far continued to grow exponentially, even that scaling will stagnate once device sizes reach their fundamental quantum limits in the next ten years. </p> <p>Due to this stagnation, processors, like those used for NASA’s navigation, communication, and telemetry systems, lack the scaling necessary to push space exploration further. A more energy efficient architecture/technology is required in order to increase the information bits per unit energy, and push processors architectures pass the thermal limits currently preventing increased speeds. Photonic integrated circuit (PIC) platforms provide a solution to this emerging challenge. PICs are becoming a key part of communication systems in data centers, where microelectronic compatibility and high-yield, low-cost manufacturing are crucial. Because of their integration, PICs can allow photonic processing at a scale impossible with discrete, bulky optical-fiber counterparts, and scalable, CMOS-compatible silicon-photonic systems are on the cusp of becoming a commercial reality. More specifically, Neuromorphic Photonics allow for the benefits of PICs to be merged with the benefits associated with non Von-Neumann processor architectures allowing for increases in both speed and energy efficiency.</p>
- API data.nasa.gov | Last Updated 2018-07-19T11:25:08.000Z
Ultrasensitive sensors used in NASAs scientific missions (for example infrared sensors) typically require operation at deep cryogenic temperatures for optimum performance. However, to make full use of their performance requires an ultralow-noise preamplifier co-located in the same, or a nearby, cryogenic environment at liquid-helium (~1-4 K) or sub-Kelvin temperatures. A severe impediment to making such preamplifiers is the lack of a semiconductor device with satisfactorily performance in the liquid-helium range (or even below ~40 K). Past use of Si JFETs (operating at ~80 K or higher) has required awkward work-arounds. More serious is that upcoming missions will employ ever more sophisticated and complex sensor systems. What served in the past will be inadequate. Specifically, Si-based technology will not be adequate for preamplifiers needed for advanced sensor systems in upcoming missions and could become the bottleneck in performance and scientific return. Consequently, we propose to develop GaAs JFETs that can exhibit extremely low noise to the lowest cryogenic temperatures (4 K and lower). Our approach is to fabricate the JFETs specifically for low-noise, deep cryogenic operation and to use a novel, proprietary design for the JFET that avoids factors that contribute to noise generation in standard GaAs JFETs.
- API data.nasa.gov | Last Updated 2018-07-19T18:17:23.000Z
In situations where the cost/benefit analysis of using physics-based damage propagation algorithms is not favorable and when sufficient test data are available that map out the damage space, one can employ data-driven approaches. In this investigation, we evaluate different algorithms for their suitability in those circumstances. We are interested in assessing the trade-off that arises from the ability to support uncertainty management, and the accuracy of the predictions. We compare here a Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), and a Neural Network-based approach and employ them on relatively sparse training sets with very high noise content. Results show that while all methods can provide remaining life estimates although different damage estimates of the data (diagnostic output) changes the outcome considerably. In addition, we found that there is a need for performance metrics that provide a comprehensive and objective assessment of prognostics algorithm performance.
- API data.nasa.gov | Last Updated 2019-04-22T03:01:22.000Z
The IceBridge Riegl Laser Altimeter L2 Geolocated Surface Elevation Triplets (ILUTP2) data set contains surface range values for Antarctica and Greenland derived from measurements captured using the Riegl Laser Altimeter. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC) with additional support from NASA Operation IceBridge.