Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensor Depth”

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.

At least 433 records · Page 24

Satellite sensor estimates of Northern Hemisphere snow volume

In the Northern Hemisphere the mean monthly snow-covered area ranges from about 7 percent of the land area in summer to over 40 percent in winter, thus making snow one of the most rapidly varying natural surface features. The mean monthly snow volume ranges from about 1.5 x 10 to the 16th g in summer to about 3.0 x 10 to the 18th g in winter. Currently several algorithms utilizing passive microwave brightness temperatures are available to estimate snow cover and depth. The algorithm presented here uses the difference between the 37-GHz channel and the 18-GHz channel of the SMMR on the Nimbus-7 satellite to derive estimates of snow volume. Even though satellite sensor snow records are currently too short to reveal trends, continued monitoring over about the next 10 years should make it possible to establish whether incipient or current trends are significant in the context of global climate change.

Chang, A. T. C.↗

The Design and Implementation of Instruments for Low-Frequency Electromagnetic Sounding of the Martian Subsurface

Low-frequency electromagnetic soundings of the subsurface can identify liquid water at depths ranging from hundreds of meters to approx. 10 km in an environment such as Mars. Among the tools necessary to perform these soundings are low-frequency electric and magnetic field sensors capable of being deployed from a lander or rover such that horizontal and vertical components of the fields can be measured free of structural or electrical interference. Under a NASA Planetary Instrument Definition and Development Program (PIDDP), we are currently engaged in the prototype stages of low frequency sensor implementations that will enable this technique to be performed autonomously within the constraints of a lander platform. Once developed, this technique will represent both a complementary and alternative method to orbital radar sounding investigations, as the latter may not be able to identify subsurface water without significant ambiguities. Low frequency EM methods can play a crucial role as a ground truth measurement, performing deep soundings at sites identified as high priority areas by orbital radars. Alternatively, the penetration depth and conductivity discrimination of low-frequency methods may enable detection of subsurface water in areas that render radar methods ineffective. In either case, the sensitivity and depth of penetration inherent in low frequency EM exploration makes this tool a compelling candidate method to identify subsurface liquid water from a landed platform on Mars or other targets of interest.

G T Delory↗

Calibration of AIS Data Using Ground-based Spectral Reflectance Measurements

Present methods of correcting airborne imaging spectrometer (AIS) data for instrumental and atmospheric effects include the flat- or curved-field correction and a deviation-from-the-average adjustment performed on a line-by-line basis throughout the image. Both methods eliminate the atmospheric absorptions, but remove the possibility of studying the atmosphere for its own sake, or of using the atmospheric information present as a possible basis for theoretical modeling. The method discussed here relies on use of ground-based measurements of the surface spectral reflectance in comparison with scanner data to fix in a least-squares sense parameters in a simplified model of the atmosphere on a wavelength-by-wavelength basis. The model parameters (for optically thin conditions) are interpretable in terms of optical depth and scattering phase function, and thus, in principle, provide an approximate description of the atmosphere as a homogeneous body intervening between the sensor and the ground.

Conel, J. E.↗

Imaging Spectrometer on a Chip

A proposed visible-light imaging spectrometer on a chip would be based on the concept of a heterostructure comprising multiple layers of silicon-based photodetectors interspersed with long-wavelength-pass optical filters. In a typical application, this heterostructure would be replicated in each pixel of an image-detecting integrated circuit of the active-pixel-sensor type (see figure). The design of the heterostructure would exploit the fact that within the visible portion of the spectrum, the characteristic depth of penetration of photons increases with wavelength. Proceeding from the front toward the back, each successive long-wavelength-pass filter would have a longer cutoff wavelength, and each successive photodetector would be made thicker to enable it to absorb a greater proportion of incident longer-wavelength photons. Incident light would pass through the first photodetector and encounter the first filter, which would reflect light having wavelengths shorter than its cutoff wavelength and pass light of longer wavelengths. A large portion of the incident and reflected shorter-wavelength light would be absorbed in the first photodetector. The light that had passed through the first photodetector/filter pair of layers would pass through the second photodetector and encounter the second filter, which would reflect light having wavelengths shorter than its cutoff wavelength while passing light of longer wavelengths. Thus, most of the light reflected by the second filter would lie in the wavelength band between the cutoff wavelengths of the first and second filters. Thus, further, most of the light absorbed in the second photodetector would lie in this wavelength band. In a similar manner, each successive photodetector would detect, predominantly, light in a successively longer wavelength band bounded by the shorter cutoff wavelength of the preceding filter and the longer cutoff wavelength of the following filter.

Wang, Yu↗

Development of Field Excavator with Embedded Force Measurement

A semi-intelligent excavation mechanism was developed for use with the NASA-built Centaur 2 rover prototype. The excavator features a continuously rotatable large bucket supported between two parallel arms, both of which share a single pivot axis near the excavator base attached to the rover. The excavator is designed to simulate the collection of regolith, such as on the Moon, and to dump the collected soil into a hopper up to one meter tall for processing to extract oxygen. Because the vehicle can be autonomous and the terrain is generally unknown, there is risk of damaging equipment or using excessive power when attempting to extract soil from dense or rocky terrain. To minimize these risks, it is critical for the rover to sense the digging forces and adjust accordingly. It is also important to understand the digging capabilities and limitations of the excavator. This paper discusses the implementation of multiple strain gages as an embedded force measurement system in the excavator's arms. These strain gages can accurately measure and resolve multi-axial forces on the excavator. In order to validate these sensors and characterize the load capabilities, a series of controlled excavation tests were performed at Glenn Research Center with the excavator at various depths and cut angles while supported by a six axis load cell. The results of these tests are both compared to a force estimation model and used for calibration of the embedded strain gages. In addition, excavation forces generated using two different types of bucket edge (straight vs. with teeth) were compared.

Soils↗

Mars Science Laboratory Heatshield Flight Data Analysis

NASA Mars Science Laboratory (MSL), which landed the Curiosity rover on the surface of Mars on August 5th, 2012, was the largest and heaviest Mars entry vehicle representing a significant advancement in planetary entry, descent and landing capability. Hypersonic flight performance data was collected using MSLs on-board sensors called Mars Entry, Descent and Landing Instrumentation (MEDLI). This talk will give an overview of MSL entry and a description of MEDLI sensors. Observations from flight data will be examined followed by a discussion of analysis efforts to reconstruct surface heating from heatshields in-depth temperature measurements. Finally, a brief overview of MEDLI2 instrumentation, which will fly on NASAs Mars2020 mission, will be presented with a discussion on how lessons learned from MEDLI data affected the design of MEDLI2 instrumentation.

Mars↗

Implementing CubeSat Avionics Components to Full-Scale Capsule Return Missions

Returning samples from Low Earth Orbit (LEO) is no simple task. Whether the samples are scientific experiments or surveillance footage, engineers must overcome many challenges to achieve mission success. In August of 1960 the first payload recovered from LEO, the Corona capsule, carried “more photographic coverage of the Soviet Union than all previous U-2 missions”. The Corona program proved that re-turning surveillance footage from LEO is possible, the program is still referenced today when designing new sample return missions. Although there are many crucial subsystems that make up a sample return capsule, the avionics subsystem demands the most attention. This paper will discuss how current CubeSat avionics components can be applied to large sample return missions. One advantage of using CubeSat avionics components is that they can fit into a 1.5 U (10x10x15 cm) compartment, leaving more room for the payload. This paper is broken down as follows. First, the reader is introduced to the history of sample return projects. The major design strengths of previous projects are analyzed and applied to the current capsule design. Next, the typical trajectory of a capsule is presented along with mission requirements and operations. During the re-entry phase, the avionics subsystem is responsible for commanding the deployment of the parachute, back shell, and the heat shield. Next, the power subsystem is discussed in detail including a trade study on batteries and voltage regulators. Next, the interface between the Ground Support Equipment (GSE) and the avionics components is discussed. It is important that the capsule is able to provide avionics system state of health to ensure proper functionality before the capsule is launched. Next, an in-depth analysis of current TechEdSat avionics components, with proven flight history, are presented. The various avionics components including the radios, GPS, IMU, temperature sensors, altitude sensors, and ejectors are discussed. The application of cur-rent avionics components to a sample return projects are analyzed. After, the wiring diagram is presented along with a discussion of the design. Next, a summary of how the avionics components are tested and validated is pro-vided. Finally, this article will present current sample return missions TechEdSat avionics components are being applied to. CubeSat Avionics can be applied to almost all sample return missions due to their compact configuration and proven space flight heritage. The TechEdSat team is currently making great progress in returning samples from the International Space Station (ISS) and is excited to present how their avionics components can be applied to a full-scale sample return mission.

Hughes, Z. M.↗

Aerosol optical depth retrievals over the Konza Prairie

The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.

Bruegge, Carol J.↗

Hyporheic Oxygen Dynamics in the East River, Colorado: Insights From an In–Situ, High Frequency Time Series During Two Distinct Flow Seasons

Dissolved oxygen (DO) is critical for aquatic ecosystems, however, few studies have focused on the long-term DO dynamics in hyporheic zones, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. We explore the dynamics of temperature and DO at 10, 20, and 35 cm depth beneath the East River, Colorado, from July–October 2017 (relatively normal water year) and April to October 2018 (comparatively low flow year), enabled by distinctive, in-situ, high frequency (Δt = 5 min) sensors that provided continuous time-series from the undisturbed study site over 14 months. We expect that hyporheic DO, which has a regular daily fluctuation pattern, is supplied by the surface water (at all times we estimate downwelling) and that diurnal hyporheic DO temporal patterns should be aligned with diurnal hyporheic temperature patterns. However, this was not found to be the case. Hyporheic DO becomes depleted briefly at 20 and 35 cm depths in 2017, and at all three hyporheic depths for extended periods in 2018. Whereas diurnal temperature fluctuations have consistent timings of maxima and minima, hyporheic DO rarely has as regular a pattern, and daily ranges are inconsistent. Rainfall events caused some of these changes to diurnal hyporheic DO patterns without repeatable effects. Antecedent snowpack conditions influence streamflow dynamics and therefore hyporheic DO dynamics in this alpine river. These results also point to the strong and variable influence of hyporheic microbial communities regulating hyporheic DO.

54 ENVIRONMENTAL SCIENCES↗

March 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign

An overview of the March 2003 coordinated sea ice field campaign in the Alaskan Arctic is presented with reference to the papers in this special section. This campaign is part of the program to validate the Aqua Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice products. Standard AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The validation program consists of three elements, namely: 1) satellite data comparisons; 2) coordinated satellite/aircraft surface measurements; and 3) modeling and sensitivity analyses. Landsat-7 and RADARSAT observations were used in comparative studies with the retrieved AMSR-E sea ice concentrations. The aircraft sensors provided high-resolution microwave imagery of the surface, atmospheric profiles of temperature and humidity, and digital records of sea ice conditions. When combined with in situ measurements, aircraft data were used to validate the AMSR-E sea ice temperature and snow-depth products. The modeling studies helped interpret the field-data comparisons, provided insight on the limitations of the AMSR-E sea ice algorithms, and suggested potential improvements to the AMSR-E retrieval algorithms.

Cavalieri, Donald J.↗

Geothermal Heat Pump System Showcase: Short-Term Validation of Borehole Heat Exchanger Performance from Field Data to Numerical Modeling: Preprint

Since 2011, a geothermal heat pump (GHP) system has been operating to provide space heating and cooling for the Solar Radiation and Research Laboratory building at the National Laboratory of the Rockies (NLR) in Golden, Colorado. The system consists of 23 vertical boreholes, each extending to a depth of 300 ft (91 m), connected to 11 water-to-air heat pump units and four circulation pumps. Between fiscal years 2023 and 2025, additional power meters and temperature sensors were retrofitted to support detailed system performance assessment and model development. This study presents preliminary monitoring results and the development of an initial numerical model of the borehole heat exchanger field. The model incorporated site-specific geometry, ground thermal properties derived from thermal response tests, and ambient temperatures, and simulated system behavior over a representative operating day in September. Model predictions of outlet temperatures were compared against corresponding field measurements. Results showed that modeling initialized with a simplified linear subsurface temperature gradient presents systematic discrepancies in outlet temperature, whereas incorporating depth-resolved borehole temperature measurements for initialization yields substantially improved agreement with observations. The findings highlight the sensitivity of short-term predictive modeling to the representation of initial subsurface thermal conditions and underscore the value of high-resolution field measurements for model calibration and validation. These preliminary results inform ongoing efforts to extend the modeling framework to longer time horizons and to refine monitoring and modeling strategies that support the design guidance and operational optimization of GHP systems in research and commercial buildings.

15 GEOTHERMAL ENERGY↗

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra- Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6C approach removed an additional negative decadal trend of Terra (Delta)NDVI approx.0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Terra and Aqua↗

Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination.

Dozier, Jeff↗

Microwave response of snow

Truck-mounted microwave sensors were used to acquire backscattering coefficient and apparent temperature data for snow-covered terrain at 19 frequencies between 1 and 18 GHz and at 35.6 GHz. Passive microwave measurements were made at 10.7, 37, and 94 GHz. The radar backscattering coefficient and radiometric emissivity were evaluated as a function of snow depth, wetness, surface roughness, and other snow parameters. It is shown that volume scattering makes the radar backscattering coefficient to increase and the radiometric emissivity to decrease with increasing snow depth until the snow layer appears electromagnetically semiinfinite in extent. The presence of liquid water in the snowpack results in increased attenuation and reduction in scattering which leads to less backscatter and more emission by the snow volume. It is concluded that microwave sensors have the potential capability for remotely monitoring both the snow equivalent and wetness of snowpacks.

Ulaby, F. T.↗

A High-Sensitivity Broad-Band Seismic Sensor for Shallow Seismic Sounding of the Lunar Regolith

The recently undertaken Space Exploration Initiative has prompted a renewed interest in techniques for characterizing the surface and shallow subsurface (0-10s of meters depth) of the Moon. There are several reasons for this: First, there is an intrinsic scientific interest in the subsurface structure. For example the stratigraphy, depth to bedrock, density/porosity, and block size distribution all have implications for the formation of, and geological processes affecting the surface, such as sequential crater ejecta deposition, impact gardening, and seismic settling. In some permanently shadowed craters there may be ice deposits just below the surface. Second, the geotechnical properties of the lunar surface layers are of keen interest to future mission planners. Regolith thickness, strength, density, grain size and compaction will affect construction of exploration infrastructure in terms of foundation strength and stability, ease of excavation, radiation shielding effectiveness, as well as raw material handling and processing techniques for resource extraction.

Pike, W. Thomas↗

Development of Compact, Modular Lunar Heat Flow Probes

Geothermal heat flow measurements are a high priority for the future lunar geophysical network missions recommended by the latest Decadal Survey and previously the International Lunar Network. Because the lander for such a mission will be relatively small, the heat flow instrumentation must be a low-mass and low-power system. The instrument needs to measure both thermal gradient and thermal conductivity of the regolith penetrated. It also needs to be capable of excavating a deep enough hole (approx. 3 m) to avoid the effect of potential long-term changes of the surface thermal environment. The recently developed pneumatic excavation system can largely meet the low-power, low-mass, and the depth requirements. The system utilizes a stem which winds out of a pneumatically driven reel and pushes its conical tip into the regolith. Simultaneously, gas jets, emitted from the cone tip, loosen and blow away the soil. The thermal sensors consist of resistance temperature detectors (RTDs) embedded on the stem and an insitu thermal conductivity probe attached to the cone tip. The thermal conductivity probe consists of a short 'needle' (2.4-mm diam. and 15- to 20-mm length) that contains a platinum RTD wrapped in a coil of heater wire. During a deployment, when the penetrating cone reaches a desired depth, it stops blowing gas, and the stem pushes the needle into the yet-to-be excavated, undisturbed bottom soil. Then, it begins heating and monitors the temperature. Thermal conductivity of the soil can determined from the rate of temperature increase with time. When the measurement is complete, the system resumes excavation until it reaches the next targeted depth.

Lunar↗

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗

Modular detector for deep underwater registration of muons and muon groups

Registration and identification of muons and muon groups penetrating into the ocean depth, can be performed using a modular multilayer detector with high resolution bidimensional readout - deep underwater calorimeter (project NADIR). Laboratory testing of a prototype sensor cell with liquid scintillator in light-tight casing, testifies to the practicability of the full-scale experiment within reasonable expences.

Demianov, A. I.↗