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.
Telemetry on-line monitoring, compression, and transmission system for manned space flight network
In the early nineties the first of the eye safe visible wavelength lidar systems known now as Micro Pulse Lidar (MPL) became operational. The important advance of the design was a system that, unlike most existing lidar, operated at eye safe energy densities and could thus operate unattended for full time monitoring. Since that time there have been many dozens of these systems produced and applied for full time profiling of atmospheric cloud and aerosol structure. There is currently an observational network of MPL sites to support global climate research. In thc course of application of these instruments there have been significant improvements in the, design and performance of the systems. In the last half decade particularly there has been significant application and technical development of MPL systems. In this paper we review progress. The current MPL systems in use are all single wavelength systems designed for cloud and aerosol applications. For the cloud and aerosol applications, both lidar depolarization and multi wavelength measurements have significant applications. These can be accomplished with the MPL, approach. The main current challenge for the lidar network activity are in the area of the reliability, repeatability and efficiency of data processing. The network makes use of internet data downloads and automated processing. The heights of all cloud and aerosol layers are needed. The recent emphasis has been in operationally deriving aerosol extinction cross section. Future emphasis will include adding cirrus optical parameters. For operational effectiveness, improvements to simplify routine data signal calibration are being researched. Overall the MPL systems have proven very effective. A large data base of results from globally distributed sites can be easily accessed through the internet. Applications have included atmospheric model development. Validation of current global satellite observations of aerosol and clouds, including now orbital lidar observations, was a primary goal for NASA. Although sampling issues require careful consideration, results have proven useful.
We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time.
In order to produce useful proxy data for the GOES-R Geostationary Lightning Mapper (GLM) in regions not covered by VLF lightning mapping systems, we intend to employ data produced by ground-based (regional or global) VLF/LF lightning detection networks. Before using these data in GLM Risk Reduction tasks, it is necessary to have a quantitative understanding of the performance of these networks, in terms of CG flash/stroke DE, cloud flash/pulse DE, location accuracy, and CLD/CG classification error. This information is being obtained through inter-comparison with LMAs and well-quantified VLF/LF lightning networks. One of our approaches is to compare "bulk" counting statistics on the spatial scale of convective cells, in order to both quantify relative performance and observe variations in cell-based temporal trends provided by each network. In addition, we are using microsecond-level stroke/pulse time correlation to facilitate detailed inter-comparisons at a more-fundamental level. The current development status of our ground-based inter-comparison and evaluation tools will be presented, and performance metrics will be discussed through a comparison of Vaisala s Global Lightning Dataset (GLD360) with the NLDN at locations within and outside the U.S.
The author has identified the following significant results. The General Electric DCP has proven to be a versatile, rugged piece of hardware and has surpassed original expectation; it is very simple to use and does not require skilled staff for its use, installation, and operation. It is well suited for use in remote sites where no power is available. From this experience, it is concluded that the data collection system will be very useful in operating a network of hydrometeorological stations situated in sites remote from normal communication links.
This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.
The activities and services of the National Space Science data Center (NSSDC) and the World Data Center A for Rockets and Satellites (WDC-A-R and S) are described with special emphasis on ionospheric physics. The present catalog/archive system is explained and future developments are indicated. In addition to the basic data acquisition, archiving, and dissemination functions, ongoing activities include the Central Online Data Directory (CODD), the Coordinated Data Analysis Workshopps (CDAW), the Space Physics Analysis Network (SPAN), advanced data management systems (CD/DIS, NCDS, PLDS), and publication of the NSSDC News, the SPACEWARN Bulletin, and several NSSD reports.
Precise ephemerides have been determined for the U.S. Navy Geosat Exact Repeat Mission (ERM) using an improved gravity-field model, PTGF-4A (Shum et al. 1989). The Geosat orbits were computed in a terrestrial reference system which is tied to the reference system defined by satellite laser ranging (SLR) to Lageos through a survey between the Tranet Doppler receiver and the SLR system located at Wettzell, FRG. The remaining Doppler tracking station coordinates were estimated simultaneously with the geopotential in the PTGF-4A solution. In this analysis, three continuous 17-day Geosat orbits, which were computed using the 46-station Tranet data and global altimeter crossover data, have a crossover residual rms of 20 cm, indicating that the Geosat radial orbit error is of the order of 20 cm. The orbits computed based on data collected by a 7-station OPNET tracking network and crossover data have the same level of accuracy.
3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks
Flexible Airspace Management (FAM) is a mid- term Next Generation Air Transportation System (NextGen) concept that allows dynamic changes to airspace configurations to meet the changes in the traffic demand. A series of human-in-the-loop (HITL) studies have identified procedures and decision support requirements needed to implement FAM. This paper outlines a suggested FAM procedure and associated decision support functionality based on these HITL studies. A description of both the tools used to support the HITLs and the planned NextGen technologies available in the mid-term are presented and compared. The mid-term implementation of several NextGen capabilities, specifically, upgrades to the Traffic Management Unit (TMU), the initial release of an en route automation system, the deployment of a digital data communication system, a more flexible voice communications network, and the introduction of a tool envisioned to manage and coordinate networked ground systems can support the implementation of the FAM concept. Because of the variability in the overall deployment schedule of the mid-term NextGen capabilities, the dependency of the individual NextGen capabilities are examined to determine their impact on a mid-term implementation of FAM. A cursory review of the different technologies suggests that new functionality slated for the new en route automation system is a critical enabling technology for FAM, as well as the functionality to manage and coordinate networked ground systems. Upgrades to the TMU are less critical but important nonetheless for FAM to be fully realized. Flexible voice communications network and digital data communication system could allow more flexible FAM operations but they are not as essential.
An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorological Satellite (COMS). This model plays an important role in retrieving accurate AOD from a single visible channel measurement. For the single-channel retrieval, sensitivity tests showed that perturbations by 4 % (0.926 +/- 0.04) in the assumed single scattering albedo (SSA) can result in the retrieval error in AOD by over 20 %. Since the measured reflectance at the top of the atmosphere depends on both AOD and SSA, the overestimation of assumed SSA in the aerosol model leads to an underestimation of AOD. Based on the AErosol RObotic NETwork (AERONET) inversion data sets obtained over East Asia before 2011, seasonally analyzed aerosol optical properties (AOPs) were categorized by SSAs at 675 nm of 0.92 +/- 0.035 for spring (March, April, and May). After the DRAGON-NE Asia campaign in 2012, the SSA during spring showed a slight increase to 0.93 +/- 0.035. In terms of the volume size distribution, the mode radius of coarse particles was increased from 2.08 +/- 0.40 to 2.14 +/- 0.40. While the original aerosol model consists of volume size distribution and refractive indices obtained before 2011, the new model is constructed by using a total data set after the DRAGON-NE Asia campaign. The large volume of data in high spatial resolution from this intensive campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the new AOD data sets retrieved from a single-channel algorithm, which uses a precalculated look-up table (LUT) with the new aerosol model, show an improved correlation with the measured AOD during the DRAGON-NE Asia campaign. The correlation between the new AOD and AERONET value shows a regression slope of 1.00, while the comparison of the original AOD data retrieved using the original aerosol model shows a slope of 1.08. The change of y-offset is not significant, and the correlation coefficients for the comparisons of the original and new AOD are 0.87 and 0.85, respectively. The tendency of the original aerosol model to overestimate the retrieved AOD is significantly improved by using the SSA values in addition to size distribution and refractive index obtained using the new model.
The Mobile Satellite (MSAT) communications system will support mobile voice and data services using circuit switched and packet switched facilities with interconnection to the public switched telephone network and private networks. Control of the satellite network will reside in a Network Control System (NCS) which is being designed to be extremely flexible to provide for the operation of the system initially with one multi-beam satellite, but with capability to add additional satellites which may have other beam configurations. The architecture of the NCS is described. The signalling system must be capable of supporting the protocols for the assignment of circuits for mobile public telephone and private network calls as well as identifying packet data networks. The structure of a straw-man signalling system is discussed.
High capacity space communications has been a desire for Human Exploration and Science missions. Current Mars missions operate at data rates of 120 kbps for telemetry downlink and it is desirable to study high rate communication links in the range of 100 Mbps to 1 Gbps data rates from Martian distances. This paper will present some assumed scenarios along with link design assumptions and link analysis for high capacity communications from Mars. The paper will focus on RF subsystems namely antenna and power for the downlink communication from a relay orbiter at Mars. The relay orbiter will communicate with the low orbit spacecrafts at Mars or any Martian surface elements such as robots, and relay the data back to the ground networks on Earth. The study will dive into the spacecraft downlink system design and communication link analysis between the relay orbiter and ground network on Earth for data rates ranging from 100 Mbps to 1 Gbps based on the assumed scenarios and link assumptions. With high rate links at larger distances, there will be a significant impact on the antenna and power requirements and the link design will make an attempt to minimize the mass of the RF subsystem on the spacecraft. The results of this study will be presented for three data rates 1 Gbps, 500 Mbps and 100 Mbps at maximum Mars to Earth distance of 2.67AU. The design will use a Ka-band downlink with 90% link availability, along with various ground network G/T assumptions and possible bandwidth efficient modulations. The paper will conclude with what types of high rate communication links are feasible from Martian distances and also identify a range of requirements for antenna and power technologies for these high capacity communications from Mars.
A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.
Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.
Data handling system for Gemini network - telemetry on-line monitoring, compression, and transmission system
NCAR Graphics is a FORTRAN 77 library of over 30 high-level graphics modules which are heavily used by science and engineering researchers at over 1500 sites world-wide including many universities and government agencies. These Earth science oriented modules now have a FORTRAN callable subroutine interface which excludes their use by non-programming researchers. This proposal outlines the development of a fully interactive 'point and click' menu-based interface using the prevailing toolkit standard for the X-window systems. Options for direct output to the display window and/or output to a Computer Graphics Metafile (CGM) will be provided. X, PEX, and PHIGS will be implemented as the underlying windowing and graphics standards. Associated meteorological and geometric data sets would exploit the network extended NASA Common Data Format, netCDF.
NCAR Graphics is a FORTRAN 77 library of over 30 high-level graphics modules which are heavily used by science and engineering researchers at over 1500 sites world-wide including many universities and government agencies. These Earth science oriented modules now have a FORTRAN callable subroutine interface which excludes their use by non-programming researchers. This proposal outlines the development of a fully interactive 'point and click' menu-based interface using the prevailing toolkit standard for the X-Window System. Options for direct output to the display window and/or output to a computer Graphics Metafile (CGM) will be provided. X, PEX, and PHIGS will be implemented as the underlying windowing and graphics standards. Associated meteorological and geometric data sets would exploit the network extended NASA Common Data Format, netCDF.