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NASA NTRS2018

Inverse Determination of Aeroheating and Charring Ablator Response

The Mars Science Laboratory (MSL) was protected during its Mars atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA). PICA is a lightweight carbon fiber/polymeric resin material that offers excellent performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of atmospheric entry and material response. MEDLI recorded, among others, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). These measurements have been widely used in the literature as a validation benchmark for state-of-the-art ablation codes. The objective of this work is to perform an inverse estimate of the MSL heatshield material properties and aerothermal environment during Mars entry from the MISP flight data.

Aeroheating↗

NASA NTRS2007

Comparisons of Instantaneous TRMM Ground Validation and Satellite Rain Rate Estimates at Different Spatial Scales

This study provides a comprehensive inter-comparison of instantaneous rain rates observed by the two rain sensors aboard the TRMM satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM microwave imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard Level I1 rain products are generated from operational applications of the TMI, PR and Combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.25 x 0.25 instantaneous rain rates obtained from the TRMM 3668 product were analyzed and compared to instantaneous GV rain rates gridded at a scale of 0.5deg x 0.5. In the second part of the study, TMI, PR, COM and GV rain rates were spatio-temporally matched and averaged at the scale of TMI footprint (- 150 sq km). This study covered a six-year period 1999-2004 and consisted of over 50,000 footprints for each GV site. In the first analysis our results showed that all of the respective rain rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm/hr over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical-global ocean areas as well.

Wolff, David B.↗

NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

DOE OSTI2025

Robust A-Optimal Experimental Design for Sensor Placement in Bayesian Linear Inverse Problems

Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian inversion communities. An optimal design maximizes a predefined utility function that is formulated in terms of the elements of an inverse problem, an example being optimal sensor placement for parameter identification. The state-of-the-art algorithmic approaches following this simple formulation generally overlook misspecification of the elements of the inverse problem, such as the prior or the measurement uncertainties. This work presents an efficient algorithmic approach for designing optimal experimental design schemes for Bayesian linear inverse problems such that the optimal design is robust to misspecification of elements of the inverse problem. Specifically, we consider a worst-case scenario approach for the uncertain or misspecified parameters, formulate robust objectives, and propose an algorithmic approach for optimizing such objectives. Furthermore, both relaxation and stochastic solution approaches are discussed with detailed analysis and insight into the interpretation of the problem and the proposed algorithmic approach. Extensive numerical experiments to validate and analyze the proposed approach are carried out for sensor placement in a parameter identification problem.

Bayesian inverse problems↗

NASA NTRS2003

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Fargion, Giulietta S.↗

DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2019

Laboratory-Based Thermal Shock Investigation of Heat Flux Sensors for the Mars 2020 Backshell

Miller, R. A.↗

NASA NTRS2019

Laboratory-Based Thermal Shock Investigation of Heat Flux Sensors for the Mars 2020 Backshell

In 2012 during the entry, descent, and landing of the Mars Science Laboratory (MSL), the MSL Entry, Descent, and Landing Instrumentation (MEDLI) sensor suite was collecting in-flight heatshield pressure and temperature data. The data collected by the MEDLI instruments has since been used for reconstruction of vehicle aerodynamics, atmospheric conditions, aerothermal heating, and Thermal Protection System (TPS) performance as well as material response model validation and refinement. The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite for the Mars 2020 heatshield and backshell is being designed to expand on the measurements and knowledge gained from MEDLI. Similar to MEDLI, MEDLI2 will measure the pressure and temperature of the heatshield. MEDLI2 will additionally measure the temperature, pressure, total heat flux, and radiative heat flux on the backshell.Since the backshell instrumentation is new to MEDLI2, Do No Harm (DNH) testing was conducted on instrumented backshell TPS (SLA-561V) panels. The panels consisted of four pressure port holes, one Mars Entry Atmospheric Data System (MEADS) pressure port plug, one MEDLI2 Integrated Sensor Plug (MISP) thermal plug, and one heat flux sensor. DNH testing was conducted to ensure the performance of the TPS was not degraded due to sensor integration and to characterize any TPS performance changes. The testing consisted of environmental testingâ€” vibration, shock, thermal vacuum (TVAC) cyclingâ€” and bounding aerothermal (arc jet) testing. During arc jet testing, the heat flux sensors embedded in the SLA-561V panels exhibited an unexpected temporary reduction in the heat flux sensor temperature and response. After review of the test results, it was determined that this unexpected response was confined to the two heat flux sensors that experienced the greatest thermal shock condition. This condition consisted of a liquid nitrogen (LN2) bath that induced temperatures of approximately -190Â°C, and then a transition (thermal shock) to an arc jet test at a heat rate of approximately 21 W/cm2. Both heat flux sensors that were exposed to this thermal shock experienced a blister in the thermal coating during the arc jet test.Two heat flux sensor thermal shock test series were performed to investigate the cause of the blistering and subsequent energy release. In these tests, the heat flux sensor was first cold soaked in either a dry ice or LN2 bath to induce temperatures of approximately -78Â°C or -190Â°C, respectively. Then the sensors were thermally shocked using two propane torches with a heat rate of either approximately 8 W/cm2 or 21 W/cm2. The key findings indicated that there is a correlation between thermal shock and the blistering observed in the DNH test series, and that the cause appeared to be rooted in the heat flux sensor epoxy that encapsulates the sensor thermopile.Since the heat flux sensors are required to measure heat fluxes up to 15 W/cm2 during the Mars 2020 entry, a third test series was designed to determine if blistering is an issue at this maximum expected flight heat flux. Results from all three thermal shock test series and a discussion about whether or not blistering of the heat flux sensor thermal coating could be an issue for the Mars 2020 mission will be presented.

Miller, R. A.↗

NASA NTRS2015

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

NASA's Global Hawk aircraft (AV1)has two microwave sensors: the passive Hurricane Imaging Radiometer (HIRAD), and the active High-altitude Imaging Wind and Rain Airborne Profiler(HIWRAP). Results are presented for a rain measurement validation opportunity that occurred in 2013, when the AV1 flew over a tropical squall-line that was simultaneously observed by the Tampa NEXRAD radar. During this experiment, Global Hawk made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD performed volume scans every 5 minutes. In this poster, the three-way inter-comparison of HIRAD Tb (base temperature), HIWRAP dbZ (decibels relative to equivalent reflectivity) and NEXRAD rain rate imagery are presented. Also, observed HIRAD Tbs are compared with theoretical radiative transfer model results using HIWRAP Rain Rates.

Retrieval↗

NASA NTRS2015

Radiation Budget Instrument (RBI) for JPSS-2

Radiation Budget Instrument (RBI) will be one of five instruments flying aboard the JPSS-2 spacecraft, a polar-orbiting sun-synchronous satellite in Low Earth Orbit. RBI is a passive remote sensing instrument that will follow the successful legacy of the Clouds and Earth's Radiant Energy System (CERES) instruments to make measurement of Earth's short and longwave radiation budget. The goal of RBI is to provide an independent measurement of the broadband reflected solar radiance and Earth's emitted thermal radiance by using three spectral bands (Shortwave, Longwave, and Total) that will have the same overlapped point spread function (PSF) footprint on Earth. To ensure precise NIST-traceable calibration in space the RBI sensor is designed to use a visible calibration target (VCT), a solar calibration target (SCT), and an infrared calibration target (ICT) containing phase change cells (PCC) to enable on-board temperature calibration. The VCT is a thermally controlled integrating sphere with space grade Spectralon covering the inner surface. Two sides of the sphere will have fiber-coupled laser diodes in the UV to IR wavelength region. An electrical substitution radiometer on the integrating sphere will monitor the long term stability of the sources and the possible degradation of the Spectralon in space. In addition the radiometric calibration operations will use the Spectralon diffusers of the SCT to provide accurate measurements of Solar degradation. All those stable on-orbit references will ensure that calibration stability is maintained over the RBI sensor lifetime. For the preflight calibration the RBI will view five calibration sources - two integrating spheres and three CrIS (Cross-track Infrared Sounder ) -like blackbodies whose outputs will be validated with NIST calibration approach. Thermopile are the selected detectors for the RBI. The sensor has a requirement to perform lunar calibration in addition to solar calibration in space in a way similar to CERES instruments approach. To monitor climate change and to get stable and traceable results, it is critical to assure stable calibration over instrument lifetime.

Georgieva, Elena↗

NASA NTRSDate not supplied

The Radiometric Scaling of the MODIS and VIIRS Imagers to a Common Reference and Stability Analysis for the Next Edition of CERES Products

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert Terra, Aqua, NPP, and NOAA-20 CERES footprint radiance observations into fluxes. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The CERES imager and GEO calibration team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to the Aqua-MODIS calibration reference. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The team will rely primarily on deep convective clouds to monitor the imager channel calibration stability and to correct for short term calibration drifts. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. The excellent radiometric stability of EPIC allows the use of EPIC observations as a stable reference to validate both the short term drift corrections of the imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗

NASA NTRS2004

The Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) Experiment

NASA has developed an Earth Observing System (EOS) consisting of a series of satellites designed to study global change from space. The EOS flagship is the EOS TERRA satellite, launched in December 1999, equipped with five unique sensors to monitor and study the Earth s heat budget and many of the key controlling variables governing the Earth's climate system. CLAMS, the Chesapeake Lighthouse and Aircraft Measurements for Satellites field campaign was conducted from NASA Wallops Flight Facility and successfully executed over the middle Atlantic eastern seaboard from July 10 August 2, 2001. CLAMS is primarily a shortwave closure experiment designed to validate and improve EOS TERRA satellite data products being derived from three sensors: CERES (Clouds and Earth's Radiant Energy System), MISR (Multi-angle Imaging Spectro-Radiometer) and MODIS (MODerate Resolution Imaging Spectroradiometer). CLAMS is jointly sponsored by the CERES, MISR and MODIS instrument teams and the NASA GEWEX Global Aerosol Climatology Project (GACP). CLAMS primary objectives are to validate satellite-based retrievals of aerosol properties and vertical profiles of radiative flux, temperature and water vapor. Central to CLAMS measurement strategy is the Chesapeake Lighthouse, a stable sea platform located in the Atlantic Ocean, 13 miles east of Virginia Beach near the mouth of the Chesapeake Bay and the site of an ongoing CERES Ocean Validation Experiment (COVE). Six research aircraft were deployed to make detailed measurements of the atmosphere and ocean surface in the vicinity of COVE, over the surrounding ocean, over nearby NOAA buoys and over a few land sites. The measurements are used to validate and provide ground truth for simultaneous products being derived from TERRA data, a key step toward an improved understanding and ability to predict changes in the Earth's climate. One of the two CERES instruments on-board TERRA was programmed for Rotating Azimuth Plane Scans (RAPS) during CLAMS, increasing the CERES coverage over COVE by a factor of 10. Nine coordinated aircraft missions and numerous additional sorties were flown under a variety of atmospheric conditions and aerosol loadings. On one golden day, July 17, all six aircraft flew coordinated patterns, vertically stacked between 100 ft and 65,000 ft over the COVE site as the TERRA satellite orbited overhead. A summary of CLAMS measurement campaign and a description of the platforms and measurements is given.

Smith, William L., Jr.↗

NASA NTRS2000

Validation of Ocean Color Remote Sensing Data using a Moored Databuoy

NASA's Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) aims to measure global ocean color from space to within 5% to provide insights into fundamental ocean processes. SeaWiFS must be backed by comprehensive calibration and validation programs if the mission is to achieve this. In situ measurements of normalized water-leaving radiance (L(sub wn)) made simultaneously with satellite measurements can complement on-orbit methods of tracking changes in the calibration of the satellite radiometer and allow end-to-end vicarious validation of the remotely-sensed data. A moored optical databuoy was developed at Plymouth Marine Laboratory, UK to measure L(sub wn) in the western English Channel. Tests indicate that the buoy is capable of measuring spectral incident irradiance with less than 10% error and water-leaving radiance with less than 20% error; these errors are reduced by averaging and show no bias. There were 24 match-ups with good quality SeaWiFS data at the buoy site during the ten months of deployment within the period May 1997 and September 1998. The differences between the buoy and SeaWiFS measurements of L(sub wn) were found to be variable and often large. The root-mean-square (RMS) differences varied from 102% at 412 nm to 50% at 555 nm. The RMS differences in measurements of L(sub wn) could be reduced to less than 18% by a combination of increasing the calibration coefficients of SeaWiFS by between 0.2 and 4.3% in the visible bands and by tuning the extrapolation of aerosol radiances from the near infrared to the visible wavelengths. These results imply that the monitoring of the absolute calibration of the SeaWiFS bands is imperfect and errors remain in the extrapolation of aerosol radiances for atmospheric correction.

Lavender, Samantha↗

NASA NTRSDate not supplied

TPSAS-NF1676L-32020-DND

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. The DSCOVR EPIC team released the version 2 dataset last year which included many enhancements, such as improved navigation, stray-light correction, and flat-fielding. Since there is no on-board calibration for EPIC, its 10 spectral channels must be calibrated using other methods, such as inter-calibrating with sensors with on-board calibration hardware. VIIRS is a well-calibrated instrument with similar spectral channels as EPIC. Spectral band induced radiance differences between VIIRS and EPIC are mitigated using Spectral Band Adjustment Factor (SBAF). We will extend the previous calibrations from prior studies to include more recent data by ray-matching EPIC with VIIRS over all-sky tropical ocean (ATO) and deep convective cloud (DCC) conditions. In addition to ATO and DCC ray-matching, we will validate these results by utilizing DCC as invariant targets to monitor sensor degradation. DCC behave as solar diffusers in the tropics and when collectively analyzed can be used to monitor the degradation of the EPIC sensor. Improvement to our dynamic navigation adjustment algorithm, as well as exploring the view angle response of the EPIC CCD array, will be examined for their effectiveness and presented at the conference.

C O Haney↗

NASA NTRS2003

Functional Flight Test Report for Positive Systems' ADAR System 5500 Sensor SN8 Linear

This report describes results of the functional flight test conducted with the Positive Systems' ADAR 5500 sensor system (serial number 8, linear configuration) near Winslow, Arizona on June 30 and July 1, 1999. The in-flight test is one component of the NASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. It allows to measure characteristics of the entire sensor system affected by both performance of the sensor during a flight and post-flight image processing. The following characteristics were analyzed: changes of dark digital numbers (DN's), radiometric linearity, signal-to-noise ratio (SNR), spatial resolution, and geolocation accuracy. The measured characteristics were compared with the image product specifications defined in the Positive Systems' SDP contract. Dependence of the dark DN's on several factors was analyzed, but no significant correlation was found. However, the observed changes in dark DN's were relatively small, which justifies usage of a constant value in the dark DN subtraction procedure during post-processing. Dependence of measured at-sensor, in-band radiance (in arbitrary units) on measured in-band ground reflectance is very well described by a linear function - The sensor fulfills the linearity requirement. Measured SNR values lower than the contract specifications, but accuracy of that test was possibly affected by non-uniformity of the employed gray-scale panels. The SNR values are generally sufficiently high for most applications. SNR can also be improved during standard flights by using longer exposure times. Full width at half maximum (FWHM) of an edge response derived line spread function was used as a measure of spatial resolution. FWHM was generally smaller than twice the ground sample distance (GSD), in agreement with the contract specifications. Accuracy of the geolocation information, which is provided for the particular images in a metadata file, was found to meet contract requirements as well.

Stanley, Tom↗

NASA NTRS2001

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

Monitoring the health of US coastal waters is an important goal of the National Oceanic and Atmospheric Administration (NOAA). Satellite sensors are capable of providing daily synoptic data of large expanses of the US coast. Ocean color sensors, in particular, can be used to monitor the water quality of coastal waters on an operational basis. To appraise the validity of satellite-derived measurements, such as chlorophyll concentration, the bio-optical algorithms used to derive them must be evaluated in coastal environments. Towards this purpose, over 21 cruises in diverse US coastal waters have been conducted. Of these 21 cruises, 12 have been performed in conjunction with and under the auspices of the NASA/Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project. The primary goal of these cruises has been to obtain in-situ measurements of downwelling irradiance, upwelling radiance, and chlorophyll concentrations in order to evaluate bio-optical algorithms that estimate chlorophyll concentration. In this Technical Memorandum, we evaluate the ability of five bio-optical algorithms, including the current Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithm, to estimate chlorophyll concentration in surface waters of the South Atlantic Bight (SAB). The SAB consists of a variety of environments including coastal and continental shelf regimes, Gulf Stream waters, and the Sargasso Sea. The biological and optical characteristics of the region is complicated by temporal and spatial variability in phytoplankton composition, primary productivity, and the concentrations of colored dissolved organic matter (CDOM) and suspended sediment. As such, the SAB is an ideal location to test the robustness of algorithms for coastal use.

Brown, Christopher W.↗

NASA NTRS1973

Control law synthesis and sensor design for active flutter suppression.

Methods are presented for representing unsteady aerodynamic loadings, valid for arbitrary motion, for the two-dimensional typical section with a trailing-edge control surface in incompressible flow and a three-dimensional lifting surface with leading- or trailing-edge control surfaces in subsonic compressible flow. Loads for the two-dimensional incompressible case are obtained via analytic continuation of the Theodorsen function into the complex plane, with guidance from a time-domain approximation of the Wagner indicial function. For the three-dimensional case, it is proposed that oscillatory generalized aerodynamic forces be approximated by Pade fractions, thereby permitting an obvious continuation into the complex plane. A theoretical justification for this procedure is briefly outlined, and some practical aspects of its implementation are discussed.

Lyons, M. G.↗