Passive gravity gradient libration dampers
Book on passive gravity gradient libration dampers covering design, flight experience, evaluation criteria, performance monitoring, failure prevention, etc
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Book on passive gravity gradient libration dampers covering design, flight experience, evaluation criteria, performance monitoring, failure prevention, etc
The concepts of radar remote sensing and microwave radiometry are discussed and their utility in earth resource sensing is examined. The direct relationship between the character of the remotely sensed data and the level of decision making for which the data are appropriate is considered. Applications of active and a passive microwave sensing covered include hydrology, land use, mapping, vegetation classification, environmental monitoring, coastal features and processes, geology, and ice and snow. Approved and proposed microwave sensors are described and the use of space shuttle as a development platform is evaluated.
Ice concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)- York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100%. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS'S estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS'S estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations.
A computer-implemented method of monitoring activity of devices in a network is provided. The method comprises passively collecting data regarding how the devices access the network, and for each device on the network, identifying all other devices on the network with which the device communicates. All communication traffic from the devices to outside the network is identified. A determination is made if there are any required updates and if patches for the devices execute in a fashion defined as safe. A number of risk indicators for privacy risks are determined according to device communication within the network, device communication to outside the network, and update and patch execution. A visualization of any identified risk factors is displayed to a user through a user interface.
Materials International Space Station Experiment 7B (MISSE 7B) is the most recent in a series of experiments flown on the exterior of International Space Station for the purpose of determining the durability of materials and components in the space environment. A collaborative effort among the Department of Defense, the National Aeronautics and Space Administration, industry, and academia, MISSE 7B will be flying a number of NASA experiments designed to gain knowledge in the area of space environmental effects to mitigate risk for exploration missions. Consisting of trays called Passive Experiment Containers, the suitcase sized payload opens on hinges and allows active and passive experiments contained within to be exposed to the ram and wake or zenith and nadir directions in low Earth orbit, in essence, providing a test bed for atomic oxygen exposure, ultraviolet radiation exposure, charged particle radiation exposure, and thermal cycling. New for MISSE 7B is the ability to monitor experiments actively, with data sent back to Earth via International Space Station communications. NASA?s active and passive experiments cover a range of interest for the Agency. Materials relevant to the Constellation Program include: solar array materials, seal materials, and thermal protection system materials. Materials relevant to the Exploration Technology Development Program include: fabrics for spacesuits, materials for lunar dust mitigation, and new thermal control coatings. Sensors and components on MISSE 7B include: atomic oxygen fluence monitors, ultraviolet radiation sensors, and electro-optical components. In addition, fundamental space environmental durability science experiments are being flown to gather atomic oxygen erosion data and thin film polymer mechanical and optical property data relevant to lunar lander insulation and the James Web Space Telescope. This paper will present an overview of the NASA experiments to be flown on MISSE 7B, along with a summary of the thermal environment to be expected during the 1 yr mission scheduled for launch in 2009.
The primary purpose of ICESat-2 mission is to monitor changes in the cryosphere. Fortunately, additional, and unrealized information from the penetration of laser light below ocean surface offers a new and exciting opportunity to study the ocean biology globally. The objective of this study is to provide the global ocean subsurface results (e.g., depolarization ratio and particulate backscattering coefficient) from ATLAS/ICESat-2 lidar measurements. The seasonal maps of ATLAS retrieved subsurface results exhibit all the major ocean plankton features anticipated from the earlier passive ocean color and CALIOP/CALIPSO lidar measurements. The ICESat-2 ATLAS lidar can continue to monitor global ocean phytoplankton properties after CALIOP/CALIPSO mission. Moreover, the ICESat-2 ocean subsurface results provide unique information to augment existing ocean color measurements by adding nighttime observations and the depth dimension with high horizontal and vertical resolutions.
Polarimetry is one of the most promising types of remote sensing for improved characterization of atmospheric aerosol. Indeed, aerosol particles constitute a highly variable atmospheric component characterized by a large number of parameters describing particle sizes, morphologies (including shape and internal structure), absorption and scattering properties, amounts, horizontal and vertical distribution, etc. Reliable monitoring of all these parameters is very challenging, and therefore the aerosol effects on climate and environment are considered to be among the most uncertain factors in climate and environmental research. In this regard, observations that provide both the angular distribution of the scattered atmospheric radiation as well as its polarization state at multiple wavelengths covering the UV–SWIR spectral range carry substantial implicit information on the atmospheric composition. Therefore, high expectations in improving aerosol characterization are associated with detailed passive photopolarimetric observations. The critical need to use space-borne polarimetry for global accurate monitoring of detailed aerosol properties was first articulated in the late 1980s and early 1990s. By now, several orbital instruments have already provided polarization observations from space, and a number of advanced missions are scheduled for launch in the coming years by international and national space agencies. The first and most extensive record of polarimetric imagery was provided by POLDER-I, POLDER-II, and POLDER/PARASOL multi-angle multi-spectral polarization sensors. Polarimetric observations with the POLDER-like design intended for collecting extensive multi-angular multi-spectral measurements will be provided by several instruments, such as the MAI/TG-2, CAPI/TanSat, and DPC/GF-5 sensors recently launched by the Chinese Space Agency. Instruments such as the 3MI/MetOp-SG, MAIA, SpexOne and HARP2 on PACE, POSP, SMAC, PCF, DPC–Lidar, ScanPol and MSIP/Aerosol-UA, MAP/Copernicus CO2 Monitoring, etc. are planned to be launched by different space agencies in the coming decade. The concepts of these future instruments, their technical designs, and the accompanying algorithm development have been tested intensively and analyzed using diverse airborne prototypes. Certain polarimetric capabilities have also been implemented in such satellite sensors as GOME-2/MetOp and SGLI/GCOM-C.
Passive microwave remote sensing in the protected band at 1.413 GHz (L-band) is important for monitoring parameters of the ocean and land surface such as soil moisture and sea surface salinity. These parameters are needed for understanding energy exchange between the surface and atmosphere and therefore are important for improving our understanding of weather and climate change. Although the band at 1.413 GHz is protected for passive use, airborne radiometers experience problems with RFI. For example, during the Southern Great Plains Experiment (1997) the ESTAR radiometer experienced significant RFI associated with airports, presumably air traffic control radar. This is a potential problem for future sensors in space planned for remote sensing of the earth surface in this frequency band.
The use of satellite passive microwave observations for the detection of severe thunderstorms is investigated. Nimbus 7 SMMR data obtained from 1979 to 1980 over the U.S. east of 105 deg W are analyzed. The relative temperature brightnesses of the severe storms are examined; it is observed that temperature brightness decreases as the storm severity increases. The temperature brightness data were transformed into a quantitative measure of storm detection ability using the critical success index of Donaldson et al. (1975). Critical success indices of 0.32, 0.48, and 0.38 were obtained for the low-brightness-temperature thresholding of severe versus nonsevere storms during 1979, 1980, and 1979 and 1980 combined, respectively. The data reveal that the geostationary passive microwave imaging capability at 37 GHz is applicable to the detection and monitoring of severe convective storms.
Continued expansion of passive acoustic telemetry networks is allowing the movements of aquatic animals to be monitored over ever-larger distances and extended time periods. From modest beginnings in east-central Florida, the collaborative FACT Network has grown into one of the largest animal tracking networks in the world, with partners working throughout the southeastern US, Bahamas, and Caribbean. In the IRL region, tracking stations deployed across a continuum of habitats are revealing the behavior and habitat needs of our region’s most valuable sportfish, shark, and sea turtle species. This talk will summarize the status of the FACT Network as of 2022. Several ongoing and upcoming studies in the Canaveral region will be highlighted including those designed to understand the export of economically valuable sportfish from protected waters of Kennedy Space Center, inshore-offshore movements of spawning red drum, seasonal migrations of coastal sharks, and habitat use of juvenile IRL sea turtles.
Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA- a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
Timely, frequent, and complete cropland soil moisture information acquired throughout the growing season is critical for agricultural policy, production, food security, and food prices. The NASA Soil Moisture Active and Passive (SMAP) mission provides a reliable data source for cropland soil moisture assessment. This paper presents Crop-CASMA - a web GIS application tool for cropland soil moisture monitoring and assessment based on SMAP data. This interactive Web service-based GIS application tool enables CONUS SMAP derived soil moisture data visualization, dissemination, and analytics. In this paper, we describe the Crop-CASMA application system architecture, the application implementation, and the data it serves. In addition, we also present a few snapshots of the Crop-CASMA data for cropland soil moisture monitoring. The release of Crop-CASMA greatly enhances the user experience and facilitates using soil moisture data products for crop condition monitoring and decision support.
The goal of a coordinated effort between groups at GWU and NASA GSFC is the development of a low-cost, global, surface instrument network that continuously monitors three key carbon cycle gases in the atmospheric column: carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), as well as oxygen (O2) for atmospheric pressure profiles. The network will implement a low-cost, miniaturized, laser heterodyne radiometer (mini-LHR) that has recently been developed at NASA Goddard Space Flight Center. This mini-LHR is designed to operate in tandem with the passive aerosol sensor currently used in AERONET (a well established network of more than 450 ground aerosol monitoring instruments worldwide), and could be rapidly deployed into this established global network. Laser heterodyne radiometry is a well-established technique for detecting weak signals that was adapted from radio receiver technology. Here, a weak light signal, that has undergone absorption by atmospheric components, is mixed with light from a distributed feedback (DFB) telecommunications laser on a single-mode optical fiber. The RF component of the signal is detected on a fast photoreceiver. Scanning the laser through an absorption feature in the infrared, results in a scanned heterodyne signal io the RF. Deconvolution of this signal through the retrieval algorithm allows for the extraction of altitude contributions to the column signal. The retrieval algorithm is based on a spectral simulation program, SpecSyn, developed at GWU for high-resolution infrared spectroscopies. Variations io pressure, temperature, composition, and refractive index through the atmosphere; that are all functions of latitude, longitude, time of day, altitude, etc.; are modeled using algorithms developed in the MODTRAN program developed in part by the US Air Force Research Laboratory. In these calculations the atmosphere is modeled as a series of spherically symmetric shells with boundaries specified at defined altitudes. Temperature, pressure, and species mixing ratios are defined at these boundaries. Between the boundaries, temperature is assumed to vary linearly with altitude while pressure (and thus gas density) vary exponentially. The observed spectrum at the LHR instrument will be the integration of the contributions along this light path. For any absorption measurement the signal at a particular spectral frequency is a linear combination of spectral line contributions from several species. For each species that might absorb in a spectral region, we have pre-calculated its contribution as a function of temperature and pressure. The integrated path absorption spectrum can then by calculated using the initial sun angle (from location, date, and time) and assumptions about pressure and temperature profiles from an atmospheric model. The modeled spectrum is iterated to match the experimental observation using standard multilinear regression techniques. In addition to the layer concentrations, the numerical technique also provides uncertainty estimates for these quantities as well as dependencies on assumptions inherent in the atmospheric models.
A system study of the potential of space technology to monitor climate changes and improve the understanding of the coupling beteen CO2 and cloud cover is summarized. The basis for the study is scientific data requirements pertinent to the U.S. Department of Energy's CO2 Research Program. The capabilities of space-based sensor systems are matched to meet these requirements. New sensor system concepts are identified, including a Space Shuttle-launched recalibration package to provide for continuity of measurement and recalibration between satellites, a high-orbit radiation budget satellite, or parallax sensor to measure cloud altitude, a passive method for the direct measurements of CO2 and a high-altitude powered platform to monitor select regional parameters. Space-based sensor systems that could be the development focus for the time frames of 0-5, 5-10 and 10-20 years are recommended.
The H-02 constructed wetland is a free water surface wetland to remove copper (Cu) and zinc (Zn) from the industrial wastewater. In this study, we evaluated the performance of the wetland from 2018 to 2019 and coupled the diffusive gradients in thin films (DGTs) and biotic ligand model (BLM) to explore metal speciation and bioavailability in wetland waters. Surface water samples were collected and piston DGTs were deployed in different sites of the wetland. The H-02 wetland functioned well during the sampling period with high removal efficiencies (Cu: 73.8 ± 1.2% and Zn: 75.2 ± 16.0%). In our study, with the assumption that the combination of BLM predicted inorganic metals species, BLM Cu(II) and BLM Zn(II), were the bioavailable and toxic species, DGT-Cu did not correlate to BLM Cu(II) (P = 0.47), but DGT-Zn positively correlated to BLM Zn(II) (R 2 = 0.35, P < 0.001). Compared to the modeling results of BLM, DGT-indicated labile and/or bioavailable Cu included not only free Cu ions and inorganic Cu complexes but also a high percentage of Cu-labile organic matter complexes. DGT-indicated Zn included free Zn ion, inorganic Zn, and only a low percentage of Zn-labile organic matter complexes. Our findings illustrated the appropriate use of passive sampling techniques and geological modeling when biomonitoring could be substituted. Furthermore, the close monitoring of metal concentrations, speciation, and bioavailability helps us understand metal biogeochemistry and metal removal processes and ensure the long-term sustainability of the constructed wetland.
The Comprehensive Test Ban Treaty (CTBT) bans nuclear weapons testing and establishes the International Monitoring System (IMS) for the purpose of treaty verification. IMS is a detector network that confirms that global nuclear activity is peaceful in nature. These detector systems use β-γcoincidence measurements to characterize atmospheric samples containing radioxenon isotopes. The goal of this work is to use the system consisting of two sodium iodide detectors and two PIPSbox detectors to characterize isotopically pure samples of 131m Xe, 133m Xe, 133 Xe, and 135 Xe via β, γ, and β-γ coincidence measurements.
Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.