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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.

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At least 739 records · Page 41

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NASA NTRS2004

Test Bed Doppler Wind Lidar and Intercomparison Facility At NASA Langley Research Center

State of the art 2-micron lasers and other lidar components under development by NASA are being demonstrated and validated in a mobile test bed Doppler wind lidar. A lidar intercomparison facility has been developed to ensure parallel alignment of up to 4 Doppler lidar systems while measuring wind. Investigations of the new components; their operation in a complete system; systematic and random errors; the hybrid (joint coherent and direct detection) approach to global wind measurement; and atmospheric wind behavior are planned. Future uses of the VALIDAR (VALIDation LIDAR) mobile lidar may include comparison with the data from an airborne Doppler wind lidar in preparation for validation by the airborne system of an earth orbiting Doppler wind lidar sensor.

Kavaya, Michael J.↗

NASA NTRS2007

Ultra-Wideband Radar Measurements of Thickness of Snow Over Sea Ice

An accurate knowledge of snow thickness and its variability over sea ice is crucial for determining the overall polar heat and freshwater budget, which influences the global climate. Recently, algorithms have been developed to extract snow thicknesses from passive microwave satellite data. However, validation of these data over the large footprint of the passive microwave sensor has been a challenge. The only method used thus far has been with meter sticks during ship cruises. To address this problem, we developed an ultra wideband frequency-modulated continuous-wave (FM-CW) radar to measure snow thickness over sea ice. We made snow-thickness measurements over Antarctic sea ice by operating the radar from a sled during September and October, 2003. We performed radar measurements over 11 stations with varying snow thickness between 4 and 85 cm. We observed excellent agreement between radar estimates of snow thickness with physical measurements, achieving a correlation coefficient of 0.95 and a vertical resolution of about 3 cm.

Kanagaratnam, P.↗

NASA NTRS2009

Terminal Descent Sensor Simulation

Sulcata software simulates the operation of the Mars Science Laboratory (MSL) radar terminal descent sensor (TDS). The program models TDS radar antennas, RF hardware, and digital processing, as well as the physics of scattering from a coherent ground surface. This application is specific to this sensor and is flexible enough to handle end-to-end design validation. Sulcata is a high-fidelity simulation and is used for performance evaluation, anomaly resolution, and design validation. Within the trajectory frame, almost all internal vectors are represented in whatever coordinate system is used to represent platform position. The trajectory frame must be planet-fixed. The platform body frame is specified relative to arbitrary reference points relative to the platform (spacecraft or test vehicle). Its rotation is a function of time from the trajectory coordinate system specified via dynamics input (file for open loop, callback for closed loop). Orientation of the frame relative to the body is arbitrary, but constant over time. The TDS frame must have a constant rotation and translation from the platform body frame specified at run time. The DEM frame has an arbitrary, but time-constant, rotation and translation with respect to the simulation frame specified at run time. It has the same orientation as sigma0 frame, but is possibly translated. Surface sigma0 has the same arbitrary rotation and translation as DEM frame.

Chen, Curtis W.↗

NASA NTRS2012

Dynamic Load Measurement of Ballistic Gelatin Impact Using an Instrumented Tube

Bird strikes are a common problem for the aerospace industry and can cause serious damage to an aircraft. Ballistic gelatin is frequently used as a surrogate for actual bird carcasses in bird strike tests. Numerical simulations of these tests are used to supplement experimental data, therefore it is necessary to use numerical modeling techniques that can accurately capture the dynamic response of ballistic gelatin. An experimental technique is introduced to validate these modeling techniques. A ballistic gelatin projectile is fired into a strike plate attached to a 36 in. long sensor tube. Dynamic load is measured at two locations relative to the strike plate using strain gages configured in a full Wheatstone bridge. Data from these experiments are used to validate a gelatin constitutive model. Simulations of the apparatus are analyzed to investigate its performance.

Seidt, J. D.↗

NASA NTRS2016

Zernike Wavefront Sensor (ZWFS) Development for Low Order Wavefront Sensing (LOWFS)

ZWFS is known to be photon noise optimal for measuring low order aberrations. Recently, ZWFS was selected as the baseline LOWFS technology on WFIRST for its sensitivity, accuracy, and its ease of integration with the starlight rejection mask. In this paper, we present the development of ZWFS sensor, including the algorithm description, sensitivity analysis, and some early experimental model validation results from a fabricated ZWFS phase mask on a stand-alone LOWFS testbed.

Zernike phase contrast↗

NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗

NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Galante, Joseph M.↗

NASA NTRSDate not supplied

Exosuit Prototypic Knee: EPK

Resistive/aerobic exercises are invaluable countermeasures to musculoskeletal/sensorimotor/cognitive deconditioning resulting from spaceflight (i.e., microgravity). In preparation for human exploration to the moon and beyond, exercise countermeasures face new mass/volume constraints, rendering current on-orbit systems infeasible. Further, effective exercise systems are critical for maintaining crew performance/health levels necessary for Lunar extravehicular activities (EVAs) and transit. Exosuits are the pinnacle of wearable and adaptable technology set to provide a lightweight, compact, innovative solution to exploration-constrained exercise. However, reliable wearable kinematic sensors integrated with softgoods have not been demonstrated in (operational) spaceflight applications. To address this gap, the project team developed a prototype exosuit knee-joint, replete with relevant sensors for determination of joint angles, and corresponding laboratory testing bench to validate the exosuit sensing performance. This technology advancement is a pre-cursor to a more expansive multi-purpose exosuit concept that provides metrology, exercise, rehabilitation, and/or augmentation.

Fiber optics↗

NASA NTRSDate not supplied

Development of Buffet Forcing Functions Using Frequency-Dependent Coherence Factors

The current accepted approach to modeling launch vehicle transonic buffet environments is to acquire time-correlated unsteady pressure measurements at discrete locations on a model-scale wind-tunnel model and use these measurements to develop buffet forcing functions (BFFs).Part of the BFF development process is the application of coherence factors to account for the discrete nature of the pressure measurement used in the development of the BFFs. Presently, the Space Launch System (SLS) program divides the launch vehicle into distinct aerodynamic regions, within which, the coherence lengths are assumed to be constant. The coherence factors are computed by averaging the coherence function between sensors within the region over a specified frequency range. The present work validates and examines the impact of two proposed changes to the development of longitudinal coherence factors used in the development of launch vehicle BFFs. One change is to employ frequency-dependent coherence factors instead of coherence factors based on the mean of the coherence function. The second proposed change replaces the aerodynamic regions with a moving-segment approach that varies the calculated coherence lengths as a function of longitudinal location of the transducers. The impact of these approaches is examined using data from two rigid buffet model wind-tunnel tests: (1)a notional launch vehicle geometry through the comparison of discrete measurement-basedBFFs to loads developed by continuous integration of unsteady pressure sensitive paint data and (2) the SLS Block 1 Cargo vehicle configuration for which BFFs have been previously developed using less-mature methods. The trends from this examination of updated coherence factor approaches ultimately result in more intuitive results than currently-accepted coherence methods.

buffet, unsteady aerodynamics, launch vehicle, win↗

NASA NTRSDate not supplied

Development of Buffet Forcing Functions Using Frequency-Dependent Coherence Factors

The current accepted approach to modeling launch vehicle transonic buffet environments is to acquire time-correlated unsteady pressure measurements at discrete locations on a model-scale wind-tunnel model and use these measurements to develop buffet forcing functions (BFFs). Part of the BFF development process is the application of coherence factors to account for the discrete nature of the pressure measurement used in the development of the BFFs. Presently, the Space Launch System (SLS) program divides the launch vehicle into distinct aerodynamic regions, within which, the coherence lengths are assumed to be constant. The coherence factors are computed by averaging the coherence function between sensors within the region over a specified frequency range. The present work validates and examines the impact of two proposed changes to the development of longitudinal coherence factors used in the development of launch vehicle BFFs. One change is to employ frequency-dependent coherence factors instead of coherence factors based on the mean of the coherence function. The second proposed change replaces the aerodynamic regions with a moving-segment approach that varies the calculated coherence lengths as a function of longitudinal location of the transducers. The impact of these approaches is examined using data from two rigid buffet model wind-tunnel tests: (1) a notional launch vehicle geometry through the comparison of discrete measurement-based BFFs to loads developed by continuous integration of unsteady pressure sensitive paint data and (2) the SLS Block 1 Cargo vehicle configuration for which BFFs have been previously developed using less-mature methods. The trends from this examination of updated coherence factor approaches ultimately result in more intuitive results than currently-accepted coherence methods.

buffet↗

NASA NTRS1994

Approaches and Analysis for On-Focal-Plane Analog-to-Digital Conversion

This paper presents approaches for on-focal-plane analog-to-digital conversion (ADC). Common approaches and architectures for ADC and their utility for on-focal-plane integration are discussed. Candidate approaches are analyzed with respect to required amplifier gain, bandwidth, capacitance matching, noise and offsets as a function of ADC resolution. A column-parallel ADC architecture appears to be an effective compromise of chip area, power, circuit speed and ADC resolution. The discussion is valid for both infrared focal-plane arrays (FPAs) and visible image sensors.

analog-to-digital↗

NASA NTRSDate not supplied

Joint Polar Satellite System (JPSS)-3 VIIRS Prelaunch Geometric Calibration and Characterization Status

The NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument in the JPSS missions (SNPP, JPSS-1-4). Being part of the calibration and validation process, JPSS-3 VIIRS prelaunch geometric performance assessment focuses on the sensor’s spatial response, band-to-band co-registration (BBR), and pointing knowledge. In general, JPSS-3 VIIRS’ prelaunch geometric performance is very good, and consistent with SNPP and JPSS-1-2 VIIRS sensors. This paper highlights some specific key findings from the JPSS-3 VIIRS’ prelaunch tests. We first show that with timing adjustments, JPSS-3 VIIRS scan BBR error between VisNIR and S/M/LWIR bands has been reduced from 0.12/0.03 M sampling intervals to 0.005/0.002 M sampling intervals, respectively. Focal Plane Assembly (FPA) rotations have been changed from 0.1 degree to 0.04 degree in VisVIR, from 0.18 degree to 0.09 degree in S/MWIR, and 0.16 degree to 0.08 degree in LWIR. Another finding from the prelaunch test is that JPSS-3 VIIRS has relatively large band-to-band co-registration errors between VisNIR and S/M/LWIR bands in the track direction. This BBR mis-registration increases when aft‐optics assembly (AOA) temperature decreases. The BBR mis-registration is about 0.10 M sampling intervals between VisNIR and S/MWIR bands, and 0.08 M sampling intervals between VisNIR and LWIR bands. By comparison, the track BBR offset in JPSS-2 is less than 0.02 M sampling intervals between VisNIR and S/M/LWIR bands. We also notice that the unsymmetrical Day Night Band (DNB) scan-direction Line Spread Function (LSF) of JPSS-2 VIIRS at different gain stages and aggregation modes have been corrected in J3 VIIRS.

VIIRS↗

NASA NTRS2022

Entry, Descent, and Landing Instrumentation

Overview of sensors used in EDL instrumentation suites. For spaceflight missions involving atmospheric entry, the environment experienced by a spacecraft cannot be fully replicated on the ground. Taking measurements in the flight environment is the “gold standard” for: Validating predictive modeling tools Reducing risk on future EDL missions EDL Instrumentation can consist of in-situ sensors embedded within the aeroshell, or remote observations. Focus of this presentation is on NASA in-situ sensors.

EDL↗

NASA NTRS2024

Airborne lidar measurements of atmospheric CO 2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign

We measured the column-averaged atmospheric CO 2 mixing ratio (XCO 2 ) to a variety of cloud tops with an airborne pulsed multi-wavelength integrated path differential absorption (IPDA) lidar during NASA's 2017 ASCENDS/ABoVE airborne campaign. Measurements of height-resolved atmospheric backscatter profiles allow this lidar to retrieve XCO 2 to cloud tops, as well as to the ground, with accurate knowledge of the photon path length. We validated these measurements with those from an onboard in situ CO 2 sensor during spiral-down maneuvers. These lidar measurements were 2–3 times better than those from previous airborne campaigns due to our using a wavelength step-locked laser transmitter and a high-efficiency detector for this campaign. Precisions of 0.6 parts per million (ppm) were achieved for 10 s average measurements to mid-level clouds and 0.9 ppm to low-level clouds at the top of the planetary boundary layer. This study demonstrates the lidar's capability to fill in XCO 2 measurement gaps in cloudy regions and to help resolve the vertical and horizontal distributions of atmospheric CO 2 . Future airborne campaigns and spaceborne missions with this capability can be used to improve atmospheric transport modeling, flux estimation and carbon data assimilation.

Jianping Mao↗

NASA NTRS2022

Europa Clipper Payload Verification and Validation: Test and Analysis Program Design

NASA’s Europa Clipper mission – which is planned to launch in the mid-2020s – is designed to investigate the habitability of the jovian moon Europa with a state-of-the-art suite of over 10 sensors and instruments. Now past its project critical design review, Europa Clipper is starting the execution of its verification and validation (V&V) program. The payload V&V function in particular is responsible for designing and coordinating a thorough test and analysis program that will confirm the proper functioning and performance of our payload instruments. Given the large number of instruments to manage, we have developed a suite of standardized tests and analyses that are designed to cover all of the common interfaces across instruments, while allowing for flexibility to support the unique needs of individual instruments. This suite of activities, coordinated and/or performed by the payload team, forms the bulk of our payload verification and validation campaign. This paper provides a detailed summary of the full set of V&V activities in that suite, covering the four categories of activities: analysis of lower-level evidence, analysis via simulation, testing in the system testbeds, and testing in assembly, test, and launch operations (ATLO). We will describe the purpose of each activity type, how the activities are developed, and the review process for each type of activity. We then define the complete list of activities written for each instrument and how subtleties specific to certain instruments are managed. The discussion will provide a comprehensive understanding of the activities in the payload V&V purview and how various interfaces with different levels of the project are managed. This paper also describes key metrics the payload team uses to track V&V progress and some insights into the teaming design and division of labor we use to ensure consistency and completeness across the entire payload suite. Finally, the paper will offer a snapshot of the status of the Payload V&V program prior to instrument delivery and offer insights into the upcoming phase of instrument delivery and the start of ATLO.

Lee, Dennis↗

DOE OSTI2022

Modeling Air Handling Units to Create a Diverse Fault Dataset for FDD Innovation: Lessons Learned and Recommendations

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault datasets for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling unit and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for the air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, two detailed AHU models, which included the single duct AHU and dual duct AHU developed in the Modelica language and HVACSIM+ were employed to carry out annual simulations of numerous common sensor faults, mechanical faults, and control sequence faults. The fault inclusive data were then validated by comparing fault effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. We report some lessons learnt during the efforts of validating the high volumes of the FDD data sets. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

DOE OSTI2016

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Finally, data from models and observations should be put on the same spatial and temporal scales before comparison.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗