- API data.nasa.gov | Last Updated 2020-01-29T04:05:26.000Z
Resident of a smart home, who may be an old person or an Alzheimer patient needing permanent assistance, actuates the world by realizing activities, which are observed through the embedded sensors of smart home. Typically, this person may sometimes forget completion of the activities; may realize the activities of daily living incorrectly, and may enter to dangerous states. In order to provide automatic assistance for the smart home resident through the embedded electronically controllable actuators and make the smart home resident able to live independently at home we propose to calculate a possibilistic logical space for correct realization of activities, which may be represented in form of a multivariable problem. Regardless from the physical entity (modality and location) of the intelligence source and the quantity of individuals who perform the activities; per each possible goal or activity, we consider a unique source of intelligence (for example a social mind) who directs the order of fuzzy events that occur in the ambient environment, then the plan behind world actuations is modeled applying extensions of the fuzzy logic. The main key point that we deal with is the analysis of the observations in order to make inferences about possible simultaneous activities that may be planned and realized by one or more individuals; so that we can reason in the cases the parallel activities are interrupted.
- API data.nasa.gov | Last Updated 2020-01-29T04:02:43.000Z
NASA seeks new materials and systems for the mitigation of structural damage, and new concepts for the activation of healing mechanisms to improve structural durability and enhance safe operation of aerospace structural systems. Nanotrons Corporation proposes to develop advanced multifunctional carbon fiber-reinforced polymer (CFRP) composites with built-in non-catalytic nanocomposite-based self-healing microcapsules. The proposed self-healing approach integrates high performance functionalized carbon nanotube (CNT) nanofillers, reactive monomer solution, non-catalytic curing mechanism, and mass-production self-healing microcapsules. By uniformly dispersing these nanocomposite-based self-healing microcapsules throughout the CFRP composite matrix, self-healing multifunctional composite materials will be fabricated. The resulting materials should selectively repair the damaged areas at ambient conditions without catalysts. Nanotrons' proposed novel multifunctional CFRP composites could heal the damaged area over 90% of the original strength. Added benefits are that the addition of self-healing microcapsules will increase fracture toughness of the matrix polymer and the incorporated CNT nanofillers will improve electrical conductivity and EMI/RF shielding performance of the healed CFRP composites. These features are unattainable from existing systems. Nanotrons' proposed non-catalytic nanocomposite-based self-healing microcapsules embedded in multifunctional CFRP composites can be economically scaled up for manufacture. This Phase I program will demonstrate the feasibility of our proposed self-healing approach.
- API data.nasa.gov | Last Updated 2019-12-12T23:50:14.000Z
CAL_LID_L2_05kmCPro-Prov-V3-40 data are CALIPSO Lidar Level 2 Cloud Profile data. The Lidar Level 2 Cloud Profile data product contains cloud profile data and ancillary data. The cloud profile product is produced at 5 km horizontal resolution and is written in HDF. Note that there is no atmospheric volume characterization associated with the cloud profile products. Also, the 1064 calibration scheme assumes that both the extinction and the backscatter from clouds are spectrally independent. Consistent with this assumption, extinction and backscatter profiles will be reported for clouds only at 532 nm. Additionally, it is important to note that the aerosol profile product extends upward to 30.1 km, while the cloud profile product ceases at 20.2. Therefore, users interested in polar stratospheric clouds will need to order the aerosol profile data product. The science algorithms used to produce the V3.40 CALIOP data products are identical to those used to generate the V3.01 and V3.02 products; however, some of the ancillary data used in the V3.40 analyses is different. All CALIOP data products rely on meteorological data provided by NASA's Global Modeling and Assimilation Office (GMAO). The V3.01 and V3.02 data products were produced using the GMAO's GEOS 5.2 data products. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth's radiation budget and climate. It flies in the international A-Train constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
- API data.nasa.gov | Last Updated 2020-01-29T03:39:20.000Z
<p>The primary objective of this activity is to develop, design, and test (DD&T) the QUAD-core siTARA (QUATARA) computer to distribute computationally intensive processes such as: communication, sensors, attitude determination, attitude control, cameras, robotic manipulators, and science payloads. An example of the current state-of-the art for a COTS CubeSat flight computer is, a 16 bit 80 MHz Microchip dsPIC33 microcontroller capable of managing the satellite attitude determination, control system, communication system, power, and science payloads. Adding more capability to these COTS flight computers required the development, under a previous CIF proposal, of the Modular Attitude Determination System (MADS) board. MADS lessened the I/O load from the flight computer so it could focus on higher priority tasks such as managing a Real-Time Operating System (RTOS) or carrying out an attitude control algorithm. The MADS board utilized a 16 bit 80 MHz Texas Instruments ARM Cortex-M4 Stellaris microcontroller to execute the attitude determination algorithm independently of the dsPIC33 flight computer. Once the MADS board processes the data, the dsPIC33 receives the estimated states and determines the desired attitude control.</p><p>The addition of cameras, proximity sensors, robotic manipulators, thruster systems, complex science payloads and video guidance systems, would cause current CubeSat flight computers to be overwhelmed. Because of the desire to expand the capabilities of CubeSats, the innovation of the QUATARA architecture enhances the capabilities of data handling and computer processing by replacing the 16 bit 80 MHz microcontrollers with four 64 bit 1 GHz microprocessors. The QUATARA allows for tasks to be processed at a faster rate not only because of the difference in clock speed between the platforms but also because of the fact that there are four individual microprocessors which can run these tasks independently without the need to serialize the execution of the code like in a single microcontroller.</p><p>The QUATARA computer aims to be fault-tolerant by means of a software voting scheme to guard against the effects of Single Event Effects (SEE) such as Single Event Upsets (SEU). Each ‘node’ (Gumstix Computer-On-Modules (COM)) of the QUATARA computer will be connected to its own set of sensors and actuators. These individual nodes will collect their respective data and share it between themselves over a data bus (such as RS-485). Once each node has all the data from all of the other nodes it will process it and come up with a result. This result can then be used to determine if a node is considered as ‘failed’ and that node then needs to be disabled, (this can be done by ignoring future data received from that node or by completely shutting it off). In the case a node is lost a support node is available to be switched in for the failed node. This support node will focus on low priority tasks, (such as housekeeping), if it is not required as a voting node. Synchronization between the nodes can be maintained by having a precise timing source on each of the processors, (such as a ticking timer interrupt routine), that ticks at a set time interval. This timing information will be passed between the nodes and the tick rate of the interrupt routine will be modified as required to ensure that all of the nodes data remains in sync.</p>
- API data.nasa.gov | Last Updated 2020-01-29T04:12:36.000Z
Current-day capabilities for performing post operations analysis (POA) of air traffic operations at airports, airlines and FAA facilities are mostly limited to creating reporting type of analysis results which compare mean values of key performance indicators against the respective expected nominal levels (e.g., average daily delay). This single point comparison method does not directly enable a POA analyst to identify the root-cause for a particular observed inefficiency, nor does it help in identifying a solution for mitigating that inefficiency. This SBIR develops a machine learning based approach for improving POA and for potentially making it more autonomous. We call this tool Collective Inference based Data Analytics System for POA (CIDAS-P). CIDAS-P will provide airport, airline, FAA and NASA personnel with a fast, flexible and streamlined process for analyzing the day-of-operations, rapidly pinpointing exact causes for any observed inefficiencies, as well as recommending actions to be taken to avoid the same inefficiencies in the future. It does this by developing an innovative, collective inference algorithm for cross-comparing performance of the same facility on different days as well as cross-comparing performance across different facilities. The algorithm leverages sophisticated probabilistic modeling techniques that consider the subtle nuances by which cross-facility and cross-day operational scenarios differ to enable apples-to-apples comparisons across traffic scenarios and identify what works well and what does not in similar situations. User acceptance of NASA Trajectory Based Operations research products stands to benefit from CIDAS-P because CIDAS-P's automated recommendations can help identify and fix problems with these products early on in their deployment life-cycle.
- API data.nasa.gov | Last Updated 2020-01-29T04:04:16.000Z
slowed rotor / compound (SL/C) aircraft offer VTOL combined with fixed-wing flight-efficiencies. They are safer than any other type aircraft -- with much lower acquisition, maintenance and operational cost than helicopters and tiltrotors. Carter Aviation Technologies began developing SL/C aircraft in 1994 and began flying a prototype, the CarterCopter Technology Demonstrator (CCTD) in 1998. This proposal, using CCTD data, will provide a prototype 2-seat SR/C, VTOL aircraft that meets NASA?s PAVE goals. Reduced community noise is provided by a computerized propeller, designed for quietness, which operates at low tip-speeds and is protected by tail-booms. The non-stalling autorotating rotor provides low tip-speeds, eliminates the helicopter ?dead man zone? and provides the equivalent of an emergency parachute. Low cost per seat mile is provided by simplified construction, reduced parts count and high flight-efficiency. During VTOL and low-speed flight, SR/C aircraft fly like an autogyro having the same hp to weight ratio. Autogyros are the easiest aircraft to learn to fly safely. Pilot workload is simplified by an automated tilting pylon that keeps the wings in best L/D, an automated boosted collective and automated rotor flapping controls. The landing gear absorbs 24 ft/sec impacts. Only the tilting pylon is untested.
- API data.nasa.gov | Last Updated 2020-01-29T01:45:46.000Z
One of the most demanding and high-stakes crew tasks aboard the International Space Station (ISS) is the capture of a visiting spacecraft by manual operation of the Space Station Robotic Manipulator System (SSRMS, or Canadarm2). The cost of a missed capture or improper arm/vehicle contact is likely to be very high. Since these operations may be performed up to six months after the most recent ground-based training, crews aboard the ISS prepare for such manual robotic tasks with the Robotics On-Board Trainer, a laptop-based graphical/dynamic simulator using NASA Dynamic Onboard Ubiquitous Graphic (DOUG) software from Johnson Space Center's Virtual Reality Laboratory. This system, however, does not utilize any real-world, 3-D, out-the-window views. Building upon recent advances in head-mounted augmented reality systems, the team of Systems Technology, Inc. and Dr. Stephen Robinson of UC Davis propose the Station Manipulator Arm Augmented Reality Trainer (SMAART) that will offer ISS crews significantly more realistic on-board refresher training for vehicle capture by manipulating the actual SSRMS with real out-the-Cupola-window views, but with a graphically-simulated vehicle overlaid on the astronaut's non-simulated view via a head-mounted display. Providing multi-sensory realism in on-board training for such high cognitive-demand skills is expected to increase crew readiness and therefore reduce operational risk for visiting vehicle capture.
- API data.nasa.gov | Last Updated 2019-12-13T00:12:54.000Z
The SSM/I Derived Oceanic Monthly Rainfall Indices data set is a GlobalbPrecipitaton Climate Project (GPCP) product. Monthly rainfall indices overnthe oceans are derived from Special Sensor Microwave Imager (SSM/I) data from the Defense Meteorological Satellite Program (DMSP) satellites F8 and F11 on channels 19 and 22 V. The data set covers the period from July 1987 to December 1995. The monthly rainfall indices are on a 5 degree by 5 degree grid extending from 50 N to 50 S. The Wilheit, Chang and Chiu (1991) method used to derive the indices gives valid values only over ocean areas. Land pixels (including island pixels) and erroneous pixels return a -10 flag. The data are stored on a 72 x 20 grid. Grid point (1,1) contains the index for 45-50 N, 0-5 E, grid point (2,1) contains the index for 45-50 N, 5-10 E, ... and grid point (72,20) contains the index for 45-50 S, 175-180 W. In the data set, each month starts with an ASCII header to identify the year and month. The data is in 10F8.1 format. Each value is the average of AM and PM estimates and corrected for beam filling error. The equation used is: (AM PM)/2.0 * 1.8. Land pixels are set to -10.0. Also there are 33 pixels blocked out due to island contamination (-10.0). If the rain retrieval did not converge, a -10.0 is assigned to the pixel. The objective of this data set is to provide a long term monthly rainfall data set to be used in EOS global change and GEWEX related research. The data set can be accessed through the IMS. Data maintained in an off-line archive will also be listed in the IMS, and orders will be filled as the data is requested. The SSM/I Derived Oceanic Monthly Rainfall Indices data set will be reviewed every six months to ensure that the most current version of the data is available.
- API data.nasa.gov | Last Updated 2020-01-29T04:04:12.000Z
Deployable Space Systems (DSS) will focus the proposed Phase 2 SBIR program on the hardware-based development and TRL advance of a highly-modularized and extremely-scalable solar array (Mega-ROSA) that provides immense power level range capability from 100kW to many Megawatts in size. Mega-ROSA will enable extremely high power spacecraft applications, including: Solar Electric Propulsion (SEP) spacecraft, SEP space-tug, and large-scale Planetary and Human Exploration missions because of its ground-breaking stowed packaging efficiency, high deployed stiffness / strength, low-cost and straightforward ground test capability. The innovative and synergistic Mega-ROSA solutions, to be validated to a TRL 6 level during the proposed Phase 2 program, will enable future high power missions through low cost (25-50% cost savings depending on PV and blanket technology), high specific power (>200 W/kg to 400 W/kg BOL at the wing level depending on PV and blanket technology), extremely compact stowage volume (>50 kW/m3 for very large arrays), high deployment reliability, platform simplicity (low parts count and reduced potential failure modes), high deployed strength/stiffness (>5X stiffer and stronger than rigid panel arrays of similar sizes), high voltage capability, scalability to ultra-high power (100kW to several Megawatts), and operability in unique environments (high/low illumination, high/low sun intensity and high radiation).
- API data.nasa.gov | Last Updated 2020-01-29T03:28:31.000Z
An innovative, ultra low noise, single chip cavity oscillator is proposed. The oscillator is fully integrated on standard MMIC process. It operates in the frequency range of 50 -- 100 GHz with phase noise of -112 at 100 KHz offset. At the core of the oscillator is a rectangular cavity based resonator. To our knowledge, this is the first ever implementation of a waveguide cavity on standard MMIC process. This new technique, will allow the realization of ultra small high performance integrated oscillators for future market demands. In the future, a phase locked oscillator can be implemented on a single chip. The PLO will consist of a cavity oscillator, phase frequency detector, prescaler and a loop filter. All components can be integrated on a standard GaAs HBT process.