Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “soiling”

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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Spacecraft Environmental Testing SMAP (Soil, Moisture, Active, Passive)

Testing a complete full up spacecraft to verify it will survive the environment, in which it will be exposed to during its mission, is a formidable task in itself. However, the ''test like you fly'' philosophy sometimes gets compromised because of cost, design and or time. This paper describes the thermal-vacuum and mass properties testing of the Soil Moisture Active Passive (SMAP) earth orbiting satellite. SMAP will provide global observations of soil moisture and freeze/thaw state (the hydrosphere state). SMAP hydrosphere state measurements will be used to enhance understanding of processes that link the water, energy, and carbon cycles, and to extend the capabilities of weather and climate prediction models. It will explain the problems encountered, and the solutions developed, which minimized the risk typically associated with such an arduous process. Also discussed, the future of testing on expensive long lead-time spacecraft. Will we ever reach the ''build and shoot" scenario with minimal or no verification testing?

thermal↗
NASA NTRS2016

Soil Moisture Active Passive (SMAP) Radiometer Subband Calibration and Calibration Drift

The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007). The observatory was launched on Jan 31, 2015. The goal of the SMAP is to measure the global soil moisture and freeze/thaw from space. The L-band radiometer is the passive portion of the spaceborne instrument. It measures all four Stokes antenna temperatures and outputs counts. The Level 1B Brightness Temperature (L1B_TB) science algorithm converts radiometer counts to the Earths surface brightness temperature. The results are reported in the radiometer level 1B data product together with the calibrated antenna temperature (TA) and all of the corrections to the unwanted sources contribution. The calibrated L1B data product are required to satisfy the overall radiometer error budget of 1.3 K needed to meet the soil moisture requirement of 0.04 volumetric fraction uncertainty and the calibration drift requirement of no larger than 0.4 K per month.

Peng, Jinzheng↗
NASA NTRS2016

Soil Moisture Active/Passive (SMAP) Radiometer Subband Calibration and Calibration Drift

The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007)]. The observatory was launched on Jan 31, 2015. The goal of the SMAP is to measure the global soil moisture and freeze/thaw from space. The L-band radiometer is the passive portion of the spaceborne instrument. It measures all four Stokes antenna temperatures and outputs counts. The Level 1B Brightness Temperature (L1B_TB) science algorithm converts radiometer counts to the Earths surface brightness temperature. The results are reported in the radiometer level 1B data product together with the calibrated antenna temperature (TA) and all of the corrections to the unwanted sources contribution. The calibrated L1B data product are required to satisfy the overall radiometer error budget of 1.3 K needed to meet the soil moisture requirement of 0.04 volumetric fraction uncertainty and the calibration drift requirement of no larger than 0.4 K per month.

Peng, Jinzheng↗
NASA NTRS2017

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗
NASA NTRS2015

Assessing Wetland Hydroperiod and Soil Moisture With Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.

Brooks, Colin↗
NASA NTRS2016

Launch Vehicle Selection and the Implementation of the Soil Moisture Active Passive Mission

Soil Moisture Active Passive (SMAP) is a NASA-developed Earth science satellite currently mapping the soil moisture content and freeze/thaw state of Earth's land mass from a 685km, near-polar, sun-synchronous orbit. It was launched on January 31, 2015 from Vandenberg AFB upon a Delta II 7320 launch vehicle. Due to external considerations, SMAP's launch vehicle selection remained an open item until Project Critical Design Review (CDR). Thus, certain key aspects of the spacecraft design had to accommodate a diverse range of candidate launch vehicle environments, performance envelopes, interfaces and operational scenarios. Engineering challenges stemmed from two distinct scenarios: decisions that had to be made prior to launch vehicle selection to accommodate all possible outcomes, and post-selection changes constrained by schedule and the existing spacecraft configuration. The effects of the timing of launch vehicle selection reached virtually every aspect of the Observatory's design and development. Physical environments, mass allocations, material selections, propulsion system performance, dynamic response, launch phase and mission planning, overall size and configuration, and of course all interfaces to the launch vehicle were heavily dependent on this outcome. This paper will discuss the resolution of these technical challenges.

Sherman, Sarah↗
NASA NTRS2016

A GNC Perspective of the Launch and Commissioning of NASA's SMAP (Soil Moisture Active Passive) Spacecraft

The NASA Soil Moisture Active Passive (SMAP) spacecraft was designed to use radar and radiometer measurements to produce global soil moisture measurements every 2-3 days. The SMAP spacecraft is a complicated dual-spinning design with a large 6 meter deployable mesh reflector mounted on a platform that spins at 14.6 rpm while the Guidance Navigation and Control algorithms maintain precise nadir pointing for the de-spun portion of the spacecraft. After launching in early 2015, the Guidance Navigation and Control software and hardware aboard the SMAP spacecraft underwent an intensive spacecraft checkout and commissioning period. This paper describes the activities performed by the Guidance Navigation and Control team to confirm the health and phasing of subsystem hardware and the functionality of the guidance and control modes and algorithms. The operations tasks performed, as well as anomalies that were encountered during the commissioning, are explained and results are summarized.

Brown, Todd S.↗
NASA NTRS2017

Extraction of Volatiles from Regolith or Soil on Mars, the Moon, and Asteroids

NASA's Advanced Exploration Systems ISRU Technology Project is evaluating concepts to extract water from all resource types Near-term objectives: Produce high-fidelity mass, power, and volume estimates for mining and processing systems Identify critical challenges for development focus Begin demonstration of component and subsystem technologies in relevant environment Several processor types: Closed processors either partially or completely sealed during processing Open air processors operates at Mars ambient conditions In-situ processors Extract product directly without excavation of raw resource Design features Elimination of sweep gas reduces dust particles in water condensate Pressure maintained by height of soil in hopper Model developed to evaluate key design parameters Geometry: conveyor diameter, screw diameter, shaft diameter, flight spacing and pitch Operational: screw speed vs. screw length (residence time) Thermal: Heat flux, heat transfer to soil Testing to demonstrate feasibility and performance Agglomeration, clogging Pressure rise forced flow to condenser.

Extration↗
NASA NTRS2018

The Composition of Amorphous Phases in Soils and Sediments on Earth and Mars

Amorphous phases are major components (~15-70 wt%) of all rock and soil samples measured thus far by the CheMin X-ray diffractometer (XRD) instrument on the MSL rover in Gale crater, Mars. The nature of these phases is not well understood and could be any combination of primary (e.g., glass) and secondary (e.g., silica, errihydrite) phases. Secondary amorphous phases are frequently found as weathering products in soils on Earth, but these materials remain poorly characterized, and it is not certain how properties like composition and structure change with formation environment.

Smith, R. J.↗
NASA NTRS2018

Soil Water Content Effects on Net Ecosystem CO2 Exchange and Actual Evapotranspiration in a Mediterranean Semiarid Savanna of Central Chile

Biosphere-atmosphere water and carbon fluxes depend on ecosystem structure, and their magnitudes and seasonal behavior are driven by environmental and biological factors. We studied the seasonal behavior of net ecosystem CO2 exchange (NEE), Gross Primary Productivity (GPP), Ecosystem Respiration (RE), and actual evapotranspiration (ETa) obtained by eddy covariance measurements during two years in a Mediterranean Acacia savanna ecosystem (Acacia caven) in Central Chile. The annual carbon balance was −53 g C/sq. m in 2011 and −111 g C/sq. m in 2012, showing that the ecosystem acts as a net sink of CO2, notwithstanding water limitations on photosynthesis observed in this particularly dry period. Total annual ETa was of 128 mm in 2011 and 139 mm in 2012. Both NEE and ETa exhibited strong seasonality with peak values recorded in the winter season (July to September), as a result of ecosystem phenology, soil water content and rainfall occurrence. Consequently, the maximum carbon assimilation rate occurred in wintertime. Results show that soil water content is a major driver of GPP and RE, defining their seasonal patterns and the annual carbon assimilation capacity of the ecosystem, and also modulating the effect that solar radiation and air temperature have on NEE components at shorter time scales.

Meza, Francisco J.↗
NASA NTRS2019

Uncertainty in Soil Moisture Retrievals: an Ensemble Approach Using SMOS L-Band Microwave Data

The uncertainty of soil moisture (SM) retrievals from satellite brightness temperature (TB) observations depends primarily on the choice of radiative transfer model (RTM) parameters, prior SM information and TB inputs. This paper studies the sensitivity of several (quasi-)operational and experimental SM retrieval products from the Soil Moisture Ocean Salinity (SMOS) mission to these choices at 11 reference sites, located in 7 watersheds across the United States (US). Different literature-based RTM parameter sets cause large biases between retrievals. Whereas typical RTM parameter sets are calibrated for SM retrievals, it is shown that a parameter set carefully optimized for TB forward modeling can also be used for retrieving SM. It is also shown that the inclusion of dynamic prior SM estimates in a Bayesian retrieval scheme can strongly improve SM retrievals, regardless of the choice of RTM parameters, and that the use of multi-angular and multi-polarization TB does not necessarily lead to superior retrievals compared to retrievals based on TB data at a single incidence angle and polarization. The second part of this paper evaluates ensemble uncertainty metrics for SM retrievals obtained by propagating a wide range of RTM parameters through the RTM. As expected for bounded variables, the spread in the ensemble SM retrievals is smallest for wet and dry SM values and highest for intermediate SM values. After removal of the strong long-term mean bias associated with the RTM parameter values for individual ensemble members, the remaining anomaly ensemble SM spread of 0.037 cu m/cu m approximates the actual time series unbiased root-mean-square-difference of 0.042 cu m/cu m between ensemble mean retrievals and in situ reference data across the reference sites. However, the temporal variability in the anomaly ensemble spread reveals higher-order biases in the retrieval error, which should be accounted for when characterizing retrieval error.

Jan Quets↗
NASA NTRS2016

Soil Moisture Active Passive Mission Mass Properties Optimization and Analysis

The Soil Moisture Active Passive (SMAP) mission creates global soil moisture measurements every 2-3 days by spinning a lightweight, ~6 meter diameter deployable mesh reflector. This represents the largest spinning antenna ever to be used on a NASA satellite. The paper discusses the mass properties challenges that were overcome in implementing the mission, including the definition of a combined imbalance term called the Effective Product of Inertia, the selection of an optimum Spun Instrument focal length and edge offset that fostered a reduced mass properties sensitivity, the inclusion of late game Spun Instrument configuration flexibility, the use of balance mass locations that leveraged the large moment arm provided by the reflector, and a subassembly measurement campaign that reduced mass properties uncertainties on testable components.

Hendry, Morgan L., IV↗
NASA NTRSDate not supplied

Geotechnical Review of Existing Mars Soil Simulants for Surface Mobility

The purpose of this paper is to provide a thorough review of the currently available Mars soil simulants and to determine those with geotechnical properties most appropriate for vehicle mobility studies. Sourcing and processing are considered since full-scale studies require bulk quantities of material on the order of tens of tons. This review identifies the top three simulants with the highest fidelity to Mars wind drift soils. These areM90, ES-2, and ES-1. In addition, recommendations to guide the development of future Mars simulants are made.

Mars↗
NASA NTRS2020

JSC-Rocknest: A Large-Scale Mojave Mars Simulant (MMS) Based Soil Simulant for In-Situ Resource Utilization Water-Extraction Studies

The Johnson Space Center-Rocknest (JSC-RN) simulant was developed in response to a need by NASA's Advanced Exploration Systems (AES) In-Situ Resource Utilization (ISRU) project for a simulant to be used in component and system testing for water extraction from Mars regolith. JSC-RN was designed to be chemically and mineralogically similar to material from the aeolian sand shadow named Rocknest in Gale Crater, particularly the 1-3 wt.% low temperature (<450 ºC) water release as measured by the Sample Analysis at Mars (SAM) instrument on the Curiosity rover. Sodium perchlorate, goethite, pyrite, ferric sulfate, regular and high capacity granular ferric oxide, and forsterite were added to a Mojave Mars Simulant (MMS) base in order to match the mineralogy, evolved gases, and elemental chemistry of Rocknest. Mineral and rock components were sent to the United States Geological Survey (USGS) in Denver for mixing. Approximately 800 kg of JSC-RN was sent back to NASA in 5 gallon buckets, which were subsampled and characterized. All samples of the USGS-produced simulants had similar evolved gas profiles as a small prototype batch of JSC-RN made in JSC laboratories, with the exception of HCl, and were similar in terms of mineralogy and total chemistry. Also, all JSC-RN subsamples were homogenous and had similar mineralogy, total chemistry, and low-temperature evolved gas profiles as the Rocknest aeolian sand shadow examined with Curiosity’s instrument suite on Mars. In particular, the low temperature water releases were similar and the amount of water evolved from JSC-RN at <450 ºC was similar to the water content of Rocknest based on SAM water peak integrations. Overall, JSC-RN is ideally suited for ISRU studies of water extraction of global martian soil due to its excellent agreement with measured properties of martian soils and its proven feasibility for large-scale production.

Simulant↗
NASA NTRSDate not supplied

The Added Value of SMAP Soil Moisture in Crop Yield Forecasting Over Argentina

Argentina is one of the major producers and exporter of soybeans, corn, and wheat to the world market; therefore, the accurate and timely forecasting of those crops yield is crucial to national crop management and global food security. Previous studies have mainly focused on developing forecasting models for a specific crop type and location using a single source of data (e.g., vegetation indices), thus providing little insight into the forecasting models' performance on different crop types and regions. Besides, these models are based on traditional statistical regression algorithms, while more advanced machine learning approaches have not been explored. This study investigated the estimation of crop yields of three major crops (corn, soybean, and winter wheat) using Multiple Linear Regression (MLR) and Support Vector Machine (SVM), over major growing provinces in Argentina. Our models were trained and evaluated on data from 2015 to 2020, where three remote sensing products (Normalized difference vegetation index (NDVI), SMAP soil moisture, and MODIS evapotranspiration) were used as predictors. Our results indicated that accurate crop yield forecasts using the developed regression models could be made one to two months before harvest. The MLR and SVM model performance varied among different crop types, where soybean and corn exhibited better predictability compare to the wheat. In most cases, the SVM outperformed the multiple linear regression model due to its ability to capture the nonlinear and complex features of the crop-production process. The forecasted model that combines data from multiple sources outperformed single-source satellite data. The highest accuracy was obtained when the three data sources were all considered in the model development. Results also indicated that the inclusion of SMAP soil moisture improved crop yield forecasting in most provinces, and the most significant improvements occurred in the drier region.

Nazmus Shams Sazib↗
NASA NTRS2013

Soil Moisture Active Passive (SMAP) observer power system architecture

The Soil Moisture Active and Passive (SMAP) observer is scheduled for launch in 2014. The primary science objective of SMAP is the high-resolution mapping of earth’s soil moisture. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. The SMAP orbit, sun-synchronous with an altitude of 680 km, was chosen to optimize the sampling characteristics of the instruments while ensuring that the resolution requirements are met. The combined active radar and passive radiometer measurement approach takes advantage of the spatial resolutions of the radar (3 km x 1000 km) and the radiometer (39 km x 47 km).

Carr, Gregory↗