Site C1 UTD LIDAR Windcube 200S / Processed Data
Site C1a UTD LIDAR Windcube 200S / Processed Data
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Site C1a UTD LIDAR Windcube 200S / Processed Data
Telemetry and data processing systems for scientific satellites
Orbital remote sensors, data processing and recognition techniques for natural resource surveying and geoscience investigations
User manual for launch abort data processing software
The fundamental features of coherent optical data processing systems are reviewed for potential application to image processing. The application of optical spatial filtering to image mapping and cloud motion is discussed.
Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.
An optical data processing system using paraboloidal reflecting surfaces is disclosed. In the preferred embodiment the paraboloidal reflecting surfaces are segments of a paraboloidal mirror. A source of coherent light is in the focal plane of the first paraboloidal mirror segment which collimates the beam and reflects it toward a second paraboloidal mirror surface. The information to be analyzed, on a transparency for example, is placed in the collimated beam. The beam is reflected from the second paraboloidal mirror segment and focused on a Fourier transform plane. A photon detector could be placed in the Fourier transform plane or suitable spatial filters, with the filtered beam then being reflected from a third paraboloidal mirror segment to be focused on a reconstruction plane.
The majority of developed physics data processing applications (PDP) are single, sequential processes that start at a point in time, and advance one step at a time until they are finished. In the current era of cloud computing and multi-core hardware architectures this approach has noticeable limitations. In this paper we present a detailed evaluation of the FBP-based Clas12 event reconstruction program that was deployed and operated both in cloud and in batch processing environments. We demonstrate the programming methodology and discuss some of the issues and optimizations affecting performance. We will also discuss our choice of using the Petri-Net process modeling formalism for the representation of the Clas12 PDP application building blocks which exhibit concurrency, parallelism, and synchronization.
Marshall Space Flight Center computer and data processing system workload analysis
Explorer xvii real time pcm telemetry data processing and display test stand
The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.
With the recent emphasis in performing multiphysics calculations using Monte Carlo transport codes such as MC21, the need for accurate estimates of the energy deposition-and the subsequent heating - has increased. However, the availability and quality of data necessary to enable accurate neutron and photon energy deposition calculations can be an issue. A comprehensive method for handling the nuclear data required for energy deposition calculations in MC21 has been developed using the NDEX nuclear data processing system and leveraging the capabilities of NJOY. The method provides a collection of data to the MC21 Monte Carlo code supporting the computation of a wide variety of energy release and deposition tallies while also allowing calculations with different levels of fidelity to be performed. Detailed discussions on the usage of the various components of the energy release data are provided to demonstrate novel methods in borrowing photon production data, correcting for negative energy release quantities, and adjusting Q values when necessary to preserve energy balance. Since energy deposition within a reactor is a result of both neutron and photon interactions with materials, a discussion on the photon energy deposition data processing is also provided. (authors)
This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Energy Oceanographic Mooring (THEOM) bottom lander and two Mid-Water Mooring (MWM) Stablemoor buoys from 1 July 2021 to 31 August 2021 (60 days). The west-most mooring (MWM1) was deployed at 60.720225 N, 151.436196 W in ~50 m of water. The middle mooring (THEOM) was deployed at 60.720703 N, 151.429500 W in ~52 m of water. The east-most buoy (MWM2) was deployed at 60.720081 N, 151.420896 W in ~50 m of water. Each Stablemoor carried three instruments: 1. A Nortek Vector acoustic Doppler velocimeter (ADV) mounted at the Stablemoor's nose. Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was motion-corrected using the internal IMU and external ADCP bottom-track data and then bin-averaged into 4 minute bins and converted to the Principal (streamwise, cross-stream, vertical) coordinate system. (Note: 30 seconds were trimmed from the beginning and end of each 5 minute duty cycle to account for the filter end-effects from turning on and turning off the IMU.) 2. A down-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the first Stablemoor instrument well. Data were recorded in 2 Hz with 5-beam burst and bottom-track enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. 3. An up-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the second Stablemoor instrument well. Data were recorded at 4 Hz with 5 beam burst enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. Note: the down-facing ADCP on MWM1 failed on July 10th, 2021, only recording 9 days of data. Because ADV motion-correction required bottom track, the ADV from MWM1 also only has 9 days processed. Additionally, only 25 days of data were processed from the MWM2 ADV because it appeared to have been impacted by debris on 7/25. Two instruments were mounted on the THEOM (see MHKDR link further below for THEOM raw data): 4. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was bin-averaged into 5 minute bins, and converted to the Principal coordinate system. 5. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 10 minutes bins and converted to the Principal coordinate system.
The SpaceCubeTM v2.0 system is a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This paper provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on nine years of engineering and operations. Five systems have been successfully operated in space starting in 2008 with four more to be delivered for launch vehicle integration in 2015. The SpaceCube v2.0 system is also baselined as the avionics solution for five additional flight projects and is always a top consideration as the core avionics for new instruments or spacecraft control. This paper will highlight how this multipurpose system is currently being used to solve design challenges of three independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (CDH) computer for a space robotics technology demonstration.
On line analog-to-digital data processing system for static rocket test firing
This dataset contains processed and standardized data from DOE Buoy 140 deployed during WFIP3.
A software program was developed and tested to process microwave radiometry data to be acquired by the microwave sensor (SSM/T) on the Defense Meteorological Satellite Program spacecraft. The SSM/T 7-channel microwave radiometer and systems data will be data-linked to Air Force Global Weather Central (AFGWC) where they will be merged with ephemeris data prior to product processing for use in the AFGWC upper air data base (UADB). The overall system utilizes an integrated design to provide atmospheric temperature soundings for global applications. The fully automated processing at AFGWC was accomplished by four related computer processor programs to produce compatible UADB soundings, evaluate system performance, and update the a priori developed inversion matrices. Tests with simulated data produced results significantly better than climatology.
The SpaceCube (sup TM) v2.0 system is a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This paper provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on nine years of engineering and operations. Five systems have been successfully operated in space starting in 2008 with four more to be delivered for launch vehicle integration in 2015. The SpaceCube v2.0 system is also baselined as the avionics solution for five additional flight projects and is always a top consideration as the core avionics for new instruments or spacecraft control. This paper will highlight how this multipurpose system is currently being used to solve design challenges of three independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (C&DH) computer for a space robotics technology demonstration.