- API performance.cityofcamas.us | Last Updated 2018-04-02T21:39:55.000Z
Datasets for the Engineering division of Public Works
- API data.nasa.gov | Last Updated 2018-07-19T08:26:53.000Z
<p>The goal of this project is to develop a specialized GPS sensor prototype to enable high-performance GPS navigation for future cis-lunar and lunar missions. This sensor will be based on the NavCube, the next-generation version of the record-setting high-altitude MMS-Navigator GPS receiver. The proposed GPS sensor will target future lunar missions including robotic and human spaceflight applications. The proposed lunar GPS sensor will combine enhanced GPS signal processing and use the Goddard Enhanced Onboard Navigation System (GEONS) flight software to provide position and timing information for future lunar missions and cis-lunar missions, and will benefit crewed and un-crewed science and exploration missions.</p>
- API data.nasa.gov | Last Updated 2018-07-19T08:34:46.000Z
To address NASA's need for compact optical isolators, Physical Optics Corporation (POC) proposes to continue the development of a new Miniature Optical Isolator (MOI). The novel optical isolator design is based on enhanced magneto-optical (MO) effects in magnetic photonic crystals. The innovation in the technology is its capacity to engineer MO effects not only by choosing the right material but also by adjusting the lattice parameters of 1 dimensional photonic crystals. While occupying a very small volume (~0.1 cm^3), a MOI device will achieve high optical transmission (2 dB or less forward loss) and excellent optical isolation (40 dB) at target wavelengths at a low cost. Therefore, the MOI technology directly addresses NASA's requirements for a compact, robust optical isolator for applications in cold atom systems. In Phase I, POC demonstrated the feasibility of the MOI technology through modeling and analysis, as well as fabrication of a proof-of-concept prototype with basic performance parameters characterized. In Phase II, POC will further optimize the device and fabricate prototypes for validation of key performance metrics, as well as evaluate life cycle and environmental performance.
- API performance.princegeorgescountymd.gov | Last Updated 2018-08-22T19:10:27.000Z
OMB Performance Metrics Objective 1.2- Percent of grant budgets available for use within 10 business days of submission to OMB, FY 2019 Proposed Budget
Automated Manufacture of Damage Detecting, Self-Healing Composite Cryogenic Pressure Vessels, Phase Idata.nasa.gov | Last Updated 2018-07-19T09:30:20.000Z
During Phase I, Aurora Flight Sciences and the University of Massachusetts Lowell propose to demonstrate the feasibility of enhancing a commercially available out-of-autoclave (OOA) carbon prepreg material system (e.g. IM7/5320) via embedded structural health monitoring (SHM) and self-healing capabilities, which can be manufactured by an automated fiber placement (AFP) machine. This proposed "smart" material will ultimately enable the cost-effective manufacture of large, lightweight core-stiffened composite cryogenic pressure vessels. Carbon nanotubes (CNTs) will be transferred either directly onto the prepreg, or onto adhesive film plies that are subsequently laminated with the prepreg material. Electrical conductivity measurements via the CNTs will provide embedded SHM capabilities, while localized Joule heating will accelerate self-healing polymerization reactions. The CNT-enhanced prepreg will also serve as a carrier layer to embed well-dispersed self-healing micro-/nano-capsules within the polymer matrix and which will allow for self-healing of microcracks resulting from impact damage and thermal cycling. Self-healing efficiency will be characterized via mechanical testing. This smart material will ultimately be produced in spools of half-inch wide unidirectional prepreg slit tape, and laid down using Aurora's 7-axis, 16-spool automated fiber placement (AFP) machine. Trade studies will be performed on the AFP machine to determine the optimal processing parameters for laying down the smart material. The targeted demonstrator structure, a "smart" cryogenic pressure vessel, will detect microcracks caused by incident impact damage and rapidly repair the damage in situ.
- API data.nasa.gov | Last Updated 2018-07-19T02:46:54.000Z
Galileo Orbiter Magnetometer (MAG) calibrated high-resolution data from the Earth-2 flyby in spacecraft, GSE, and GSM coordinates. These data cover the interval 1992-11-03 to 1992-12-19.
- API mydata.iowa.gov | Last Updated 2019-06-07T20:30:11.000Z
This dataset provides information on budget appropriations for each fiscal year starting in FY 2010. The data provides granular detail down to the budget organizational unit and and object class for the department request, the Governor's recommendation, the enacted budget, and the adopted budget. The state fiscal year runs from July 1 to the following June 30 and is numbered for the calendar year in which it ends. The State of Iowa operates on a modified accrual basis which provides that encumbrances on June 30 must be paid within 60 days after year end. The Legislature may enact exceptions to this statute and usually do so for capital items which may run for several years. Department names and budget units for FY 2010 - 2015 are based on names used in FY 2016.
- API stat.montgomerycountymd.gov | Last Updated 2014-07-09T20:31:06.000Z
FY15 APPR Each Program Approved Changes
- API data.nasa.gov | Last Updated 2018-07-19T07:20:39.000Z
Assistive Free-Flyers (AFFs) are flying robots designed to share the living space with human astronauts in orbit. These robots have shown the potential to assist astronauts with tasks such as surveillance, inspection, and mapping. However, AFFs are currently designed without manipulation capabilities, and can thus be deployed mainly for sensing and observation. In this project, we aim to provide AFFs with the capability to physically interact with the environment through manipulation. We plan to equip AFFs with compact yet dexterous robotic arms and hands developed in this project, along with the planning and control methods needed to operate them. We aim to demonstrate new capabilities on tasks such as object acquisition and transport, part insertion and extraction, button or lever operation, docking and perching. We believe these abilities will greatly increase AFFs' reach, literally and figuratively.
- API data.nasa.gov | Last Updated 2018-07-19T07:34:09.000Z
Simultaneous Localization and Mapping (SLAM) in robotics, is when a robot constructions a set of geometrical features of its environment (mapping) and uses sensing to estimate where it is relative to those features (localization). For example, the robot learns where walls are in a building and then can learn how to navigate between a start and goal without hitting them. SLAM sensors have been lidar (3D laser sensor like on Kinect) or bi/tri-ocular (two or three image cameras). This proposal suggests the use of a monocular sensor which is just a single camera that records images without any 3D data. Using the accelerometer and gyroscope along with the camera in a smartphone, some 3D information can be recovered. By using computer vision techniques, the sets of features are found in a sequence of camera frames. From the accelerometer and gyroscope data these are then fitted to statistical estimates of where these features are in the 3D environment. Then using sensor fusion techniques the data is compiled and then traditional SLAM algorithms are used. This would allow SLAM within lower weight, cost, and power sensors. The Smart SPHERES are a direct application of monocular SLAM that are being used to research robotic autonomy. Robotic navigation autonomy is important because it enables robots to aid astronauts with their numerous tasks around the space station with their highly limited time. Second, the technology extends to exploration probes such as the mars rovers which have too much of a communication time delay to be operated purely by teleoporation.