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NASA NTRS2016

PLANT: Polarimetric-Interferometric Lab and Analysis Tools for Ecosystem and Land-Cover Science and Applications

PLANT (Polarimetric-interferometric Lab and Analysis Tools) is a new collection of software tools developed at the Jet Propulsion Laboratory to support processing and analysis of Synthetic Aperture Radar (SAR) data for ecosystem and land-cover/land-use change science and applications. PLANT inherits code components from the Interferometric Scientific Computing Environment (ISCE) to generate highresolution, coregistered polarimetric-interferometric SLC stacks from Level-0/1 data for a variety of airborne and spaceborne sensors. The goal is to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g.,maps of above-ground biomass and forest disturbance). In this paper we introduce the capabilities of PLANT and report first results obtained with the tools developed up to date.

Lavalle, Marco↗

DOE OSTI2021

Cyber-Attack Detection for Photovoltaic Farms Based on Power-Electronics-Enabled Harmonic State Space Modeling

Here in this paper, a physics-data-based detection method is proposed to detect a variety of cyber-attacks in Photovoltaic (PV) farms using the power electronics-enabled harmonic state space (HSS) models, which, to our knowledge, is original. At the device level, HSS-based detection is developed to monitor harmonic vectors of individual PV converter with minimum sensor measurements, thus improving accuracy and robustness compared to Kalman Filter-based detection. At the system level that involves multiple PV converters, a clustering approach is developed to investigate attack propagation and accurately locate attack sources within a PV farm. The proposed approach is one of the first attempts to address PV security through interaction between the device and system, maximizing the accuracy and robustness at different levels. To verify the feasibility, a comprehensive attacks model is built, including single attack, coordinated attacks, and replay attacks. Besides, the impacts of irradiance changes are taken into consideration in the test scenarios. With the real-time data acquisition and hardware-in-the-loop testbed, comprehensive test results are provided to verify the feasibility of the proposed detection methodology.

42 ENGINEERING↗

DOE OSTI2023

ADP enhances the allosteric activation of eukaryotic elongation factor 2 kinase by calmodulin

Protein translation, one of the most energy-consumptive processes in a eukaryotic cell, requires robust regulation, especially under energy-deprived conditions. A critical component of this regulation is the suppression of translational elongation through reduced ribosome association of the GTPase eukaryotic elongation factor 2 (eEF-2) resulting from its specific phosphorylation by the calmodulin (CaM)-activated α–kinase eEF-2 kinase (eEF-2K). It has been suggested that the eEF-2K response to reduced cellular energy levels is indirect and mediated by the universal energy sensor AMP-activated protein kinase (AMPK) through direct stimulatory phosphorylation and/or downregulation of the eEF-2K-inhibitory nutrient-sensing mTOR pathway. Here, we provide structural, biochemical, and cell-biological evidence of a direct energy-sensing role of eEF-2K through its stimulation by ADP. A crystal structure of the nucleotide-bound complex between CaM and the functional core of eEF-2K phosphorylated at its primary stimulatory site (T348) reveals ADP bound at a unique pocket located on the face opposite that housing the kinase active site. Within this basic pocket (BP), created at the CaM/eEF-2K interface upon complex formation, ADP is stabilized through numerous interactions with both interacting partners. Biochemical analyses using wild-type eEF-2K and specific BP mutants indicate that ADP stabilizes CaM within the active complex, increasing the sensitivity of the kinase to CaM. Induction of energy stress through glycolysis inhibition results in significantly reduced enhancement of phosphorylated eEF-2 levels in cells expressing ADP-binding compromised BP mutants compared to cells expressing wild-type eEF-2K. These results suggest a direct energy-sensing role for eEF-2K through its cooperative interaction with CaM and ADP.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Using CTX Image Features to Predict HiRISE-Equivalent Rock Density

Methods have been developed to quantitatively assess rock hazards at candidate landing sites with the aid of images from the HiRISE camera onboard NASA s Mars Reconnaissance Orbiter. HiRISE is able to resolve rocks as small as 1-m in diameter. Some sites of interest do not have adequate coverage with the highest resolution sensors and there is a need to infer relevant information (like site safety or underlying geomorphology). The proposed approach would make it possible to obtain rock density estimates at a level close to or equal to those obtained from high-resolution sensors where individual rocks are discernable.

Serrano, Navid↗

NASA NTRS2009

Commercial Sensor Survey Fiscal Year 2009 master compendium radiation test report

The NASA Electronic Parts and Packaging (NEPP) Program Sensor Technology Commercial Sensor Survey task is geared toward benefiting future NASA space missions with low-cost, short-duty-cycle, visible-wavelength imaging needs. Such applications could include imaging for educational outreach purposes or short surveys of spacecraft, planetary, or lunar surfaces. Under the task, inexpensive, low-power, commercial grade CMOS sensors were surveyed in fiscal year 2007 (FY07), and three sensors were selected and tested for total ionizing dose (TID) and displacement damage dose (DDD) tolerance in fiscal year 2008 (FY08). The selected sensors had to meet selection criteria chosen to support small, low-mass cameras that produce good resolution color images. The commercial CMOS sensors tested under the task in FY08 showed very promising response to typical outreach and survey camera TID and DDD levels. In fiscal year 2009 (FY09), the survey was broadened to include two additional, similar sensor products. This compendium provides results for all radiation testing performed on the Micron and OmniVision sensors that were selected for radiation tolerance testing in FY08 and FY09.

Thorbourn, Dennis O.↗

NASA NTRS2010

Closed Brayton Cycle Power Conversion Unit for Fission Surface Power Phase I Final Report

A Closed Brayton cycle power conversion system has been developed to support the NASA fission surface power program. The goal is to provide electricity from a small nuclear reactor heat source for surface power production for lunar and Mars environments. The selected media for a heat source is NaK 78 with water as a cooling source. The closed Brayton cycle power was selected to be 12 kWe output from the generator terminals. A heat source NaK temperature of 850 K plus or minus 25 K was selected. The cold source water was selected at 375 K plus or minus 25 K. A vacuum radiation environment of 200 K is specified for environmental operation. The major components of the system are the power converter, the power controller, and the top level data acquisition and control unit. The power converter with associated sensors resides in the vacuum radiation environment. The power controller and data acquisition system reside in an ambient laboratory environment. Signals and power are supplied across the pressure boundary electrically with hermetic connectors installed on the vacuum vessel. System level analyses were performed on working fluids, cycle design parameters, heater and cooling temperatures, and heat exchanger options that best meet the needs of the power converter specification. The goal is to provide a cost effective system that has high thermal-to-electric efficiency in a compact, lightweight package.

Fuller, Robert L.↗

NASA NTRS2001

Virtual Instrumentation for a Fiber-Optics-Based Artificial Nerve

A LabView-based computer interface for fiber-optic artificial nerves has been devised as a Masters thesis project. This project involves the use of outputs from wavelength multiplexed optical fiber sensors (artificial nerves), which are capable of producing dense optical data outputs for physical measurements. The potential advantages of using optical fiber sensors for sensory function restoration is the fact that well defined WDM-modulated signals can be transmitted to and from the sensing region allowing networked units to replace low-level nerve functions for persons desirous of "intelligent artificial limbs." Various FO sensors can be designed with high sensitivity and the ability to be interfaced with a wide range of devices including miniature shielded electrical conversion units. Our Virtual Instrument (VI) interface software package was developed using LabView's "Laboratory Virtual Instrument Engineering Workbench" package. The virtual instrument has been configured to arrange and encode the data to develop an intelligent response in the form of encoded digitized signal outputs. The architectural layout of our nervous system is such that different touch stimuli from different artificial fiber-optic nerve points correspond to gratings of a distinct resonant wavelength and physical location along the optical fiber. Thus, when an automated, tunable diode laser sends scans, the wavelength spectrum of the artificial nerve, it triggers responses that are encoded with different touch stimuli by way wavelength shifts in the reflected Bragg resonances. The reflected light is detected and a resulting analog signal is fed into ADC1 board and DAQ card. Finally, the software has been written such that the experimenter is able to set the response range during data acquisition.

Lyons, Donald R.↗

DOE OSTI2022

WIRE-21 Sensor Irradiation Experiment Ready for HFIR Insertion

The ability to deploy new nuclear fuels for current or future reactor concepts requires a wealth of data regarding fuel performance during normal operation, anticipated operational occurrences, and design-basis accidents. Most of these data have historically been collected during experiments in materials test reactors, ideally with online instrumentation to collect as much data as possible. However, advanced instrumentation could also allow for in situ monitoring of fuel operating conditions during commercial reactor operation to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator understanding of limiting peaking factors. The latter approach would complicate fuel handling, particularly during refueling, unless the instrumentation could be placed inside the fuel rods and transmitted wirelessly to a receiver located outside the fuel’s primary pressure boundary. To this end, Westinghouse Electric Company (WEC) developed wireless sensors based on inductive coupling that can transmit information regarding fuel centerline temperatures and rod internal pressures wirelessly from within a fuel rod to a nearby instrument thimble. After testing these sensors in lower-power university research reactors, the next step is to perform high neutron fluence testing to characterize the performance of these wireless sensors under conditions that are more representative of the intended application—in this case, light-water reactors (LWRs). The removable Be (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) provide the neutron flux, experiment volume, and access to instrument leads required to achieve these sensor testing goals. This report summarizes the design, analysis, and assembly of the Wireless Instrumented RB Experiment 2021 (WIRE-21). This is the most highly instrumented irradiation experiment ever performed in HFIR. The experiment will use seven different sensing techniques to measure temperature, pressure, neutron flux, and neutron fluence during reactor operation. In addition to WEC’s wireless temperature and pressure sensors, WIRE-21 includes an array of thermocouples, self-powered neutron detectors, spatially distributed fiber optic temperature sensors, passive SiC temperature monitors, and flux wires. The design of WIRE-21 and the cabling that was installed in HFIR also provide the infrastructure to enable accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting component temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) that would be expected in the plenum region of LWR fuels, except for the active sensing region of the wireless temperature sensor, which is targeting LWR fuel centerline temperatures (~800–1,100°C). WIRE-21 was successfully assembled, passed all nondestructive examination, and was delivered to HFIR for insertion during upcoming cycle 498 (April 2022).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1992

Active member vibration control for a 4 meter primary reflector support structure

The design and testing of a new low voltage piezoelectric active member with integrated load cell and displacement sensor is described. This active member is intended for micron level vibration and structural shape control of the Precision Segmented Reflector test-bed. The test-bed is an erectable 4 meter diameter backup support truss for a 2.4 meter focal length parabolic reflector. Active damping of the test-bed is then demonstrated using the newly developed active members. The control technique used is referred to as bridge feedback. With this technique the internal sensors are used in a local feedback loop to match the active member's input impedance to the structure's load impedance, which then maximizes vibrational energy dissipation. The active damping effectiveness is then evaluated from closed loop frequency responses.

Umland, J. W.↗

NASA NTRS1999

Insulation Testing Using Cryostat Apparatus with Sleeve

The method and equipment of testing continuously rolled insulation materials is presented in this paper. Testing of blanket and molded products is also facilitated. Materials are installed around a cylindrical copper sleeve using a wrapping machine. The sleeve is slid onto the vertical cold mass of the cryostat. The gap between the cold mass and the sleeve measures less than 1 mm. The cryostat apparatus is a liquid nitrogen boiloff calorimeter system that enables direct measurement of the apparent thermal conductivity (k-value) of the insulation system at any vacuum level between 5 x 10(exp -5) and 760 torr. Sensors are placed between layers of the insulation to provide complete temperature-thickness profiles. The temperatures of the cold mass (maintained at 77.8 kelvin (K)), the sleeve (cold boundary temperature (CBT)), the insulation outer surface (warm boundary temperature (WBT)), and the vacuum can (maintained at 313 K by a thermal shroud) are measured. Plots of CBT, WBT, and layer temperature profiles as functions of vacuum level show the transitions between the three dominant heat transfer modes. For this cryostat apparatus, the measureable heat gain is from 0.2 to 20 watts. The steady-state measurement of k-value is made when all temperatures and the boiloff rate are stable.

Fesmire, J. E.↗

DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

NASA NTRS2007

Increasing Linear Dynamic Range of a CMOS Image Sensor

A generic design and a corresponding operating sequence have been developed for increasing the linear-response dynamic range of a complementary metal oxide/semiconductor (CMOS) image sensor. The design provides for linear calibrated dual-gain pixels that operate at high gain at a low signal level and at low gain at a signal level above a preset threshold. Unlike most prior designs for increasing dynamic range of an image sensor, this design does not entail any increase in noise (including fixed-pattern noise), decrease in responsivity or linearity, or degradation of photometric calibration. The figure is a simplified schematic diagram showing the circuit of one pixel and pertinent parts of its column readout circuitry. The conventional part of the pixel circuit includes a photodiode having a small capacitance, CD. The unconventional part includes an additional larger capacitance, CL, that can be connected to the photodiode via a transfer gate controlled in part by a latch. In the high-gain mode, the signal labeled TSR in the figure is held low through the latch, which also helps to adapt the gain on a pixel-by-pixel basis. Light must be coupled to the pixel through a microlens or by back illumination in order to obtain a high effective fill factor; this is necessary to ensure high quantum efficiency, a loss of which would minimize the efficacy of the dynamic- range-enhancement scheme. Once the level of illumination of the pixel exceeds the threshold, TSR is turned on, causing the transfer gate to conduct, thereby adding CL to the pixel capacitance. The added capacitance reduces the conversion gain, and increases the pixel electron-handling capacity, thereby providing an extension of the dynamic range. By use of an array of comparators also at the bottom of the column, photocharge voltages on sampling capacitors in each column are compared with a reference voltage to determine whether it is necessary to switch from the high-gain to the low-gain mode. Depending upon the built-in offset in each pixel and in each comparator, the point at which the gain change occurs will be different, adding gain-dependent fixed pattern noise in each pixel. The offset, and hence the fixed pattern noise, is eliminated by sampling the pixel readout charge four times by use of four capacitors (instead of two such capacitors as in conventional design) connected to the bottom of the column via electronic switches SHS1, SHR1, SHS2, and SHR2, respectively, corresponding to high and low values of the signals TSR and RST. The samples are combined in an appropriate fashion to cancel offset-induced errors, and provide spurious-free imaging with extended dynamic range.

Pain, Bedabrata↗

DOE OSTI2020

NDE Technology Engineering Program for Hanford DST Non-Visual Volumetric Inspection Technology: Phase II RAVIS Radiation Tolerance Test Report

This test report provides the results of radiation tolerance robustness testing that was performed on samples of robotic components and an ultrasonic guided wave air-slot sensor that represent components/sub-systems of the Robotic Air-slot Volumetric Inspection System (RAVIS) that has been engineered for volumetric inspection of Hanford tank bottom plates via under-tank refractory pad air-slots. The specific components tested for 1) functionality during active irradiation and 2) tolerance to cumulative radiation dose (until failure or upon reaching a cumulative dose test limit) were: • four samples each of a printed circuit board (PCB) and direct current (DC) motor, which are robotic components, and • 26 ultrasonic piezoelectric elements (samples) inside an air-slot sensor. The robotic components are part of the RAVIS air-slot inspection crawler drive control system that is responsible for remote communication with and actuation of the air-slot inspection crawler. The failure of either of these components during under-tank deployment would require manual retrieval via the crawler’s tether, which risks damage to the robot/refractory/tank. Preemptive replacement of the components at appropriately conservative dose/time intervals informed by failure dose would reduce the likelihood of under-tank failure. The components were included in radiation tolerance testing to quantify their failure doses to inform replacement intervals. The air-slot sensor is responsible for collecting ultrasonic inspection data (scan images) for the tank bottom plates during under-tank deployment. Compromised signal quality due to elevated noise levels caused by gamma radiation would compromise inspection performance. The air-slot sensor was included in radiation tolerance testing to quantify the impact of active irradiation on sensor signal quality. The irradiation and in-situ functional tests of the PCBs, DC motors and air-slot sensor took place in June and July 2020 at the Pacific Northwest National Laboratory. Testing was performed at a gamma dose rate near 300 rad/hr., which, in the absence of under-tank dose rate data, has been conservatively estimated to be the upper-bound dose rate beneath the primary tanks at Hanford. Irradiation took place at elevated temperatures of 150-200°F to determine failure doses that reflect the compounding effects of gamma radiation and heat. The test results revealed: • The DC motors can tolerate being actively irradiated at the high dose rate at 200°F and can tolerate a cumulative dose of 300,000 rad, that which would be incurred after 5 years of service at the 300 rad/hr dose rate. The component therefore meets minimum and preferred radiation tolerance and lifecycle requirements for robotic components. • The air-slot sensor can tolerate being actively irradiated at the high dose rate at 150°F and can tolerate a cumulative dose of 60,000 rad, that which would be incurred after 1 year of service at the 300 rad/hr dose rate. The sensor therefore meets minimum radiation tolerance and lifecycle requirements. • The PCB can tolerate being actively irradiated at the high dose rate, but can only tolerate a cumulative dose of 19,000 rad at 150-200°F. The PCB does not meet minimum radiation tolerance and lifecycle requirements; however, because the component is considered replaceable, it can be replaced before a cumulative dose of 19,000 rad is reached, determined through either monitoring with a dosimeter or scheduled time intervals that are calculated based on conservative estimates of under-tank dose rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1978

System considerations for an earth radiation budget scanning radiometer

Error sources that might affect the earth radiation budget (ERBSI) scanner radiometer are discussed. Effects of sensor time response, spatial averaging by the field of view, onboard processing, and level III averaging are examined, coverage of grid regions is considered, and an analysis procedure for a scanning radiometer is derived. ERBSI consists of a scanning radiometer, sensors, and a solar radiometer, and it is suggested that ERBSI be included in the instrument complement of NOAA operational spacecraft.

Smith, G. L.↗

DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 3: Toward a national land use information system

It is recommended that a national land use information system be established by an agency of the Federal Government. This recommendation comes at a time of increasing demand for scientific information in support of environmentally relevant land use planning and management at all levels of government. It is also a time when new airborne and spaceborne remote sensors, tested in cooperation with the National Aeronautics and Space Administration (NASA) and the Earth Resources Observation Systems (EROS) Program of the Department of the Interior, make possible the gathering of land use information rapidly and on an unprecedented scale. Furthermore, information handling technology is developing toward a capability to receive, store, and disseminate the huge quantities of data that would be involved. The recommendation for the national land use information system is based upon careful analysis of the results of remote sensing experiments funded by NASA, EROS, and the Geography Program of the Geological Survey, with specific examples drawn from the demonstration project known as the Central Atlantic Regional Ecological Test Site (CARETS). CARETS is cast in the framework of a regional land use information system, channeling the flow bf information generated in response to users' declaration of their needs, through stages dealing with remote sensing data gathering systems, data processing and land mensuration, calibration in-terms of environmental impact, and evaluation with feedback from users. The proposed system would develop and implement a unified approach to the description and interpretation of the changing uses of the nation's land resources, building upon the base of interagency and intergovernmental cooperation already achieved in the experimental work to date. The land use data base that is being derived from high-altitude aerial color infrared photography would be the initial component of the recommended system. High-altitude photographic coverage would immediately be extended to as much of the nation as possible as technological developments and economic considerations permit. The system would later expand to include multiple-sensor, multiple-platform data sources. Six system characteristics are recommended: (1) High capacity storage of data available for quick retrieval, inexpensive processing, and update, (2) provision of accuracy appropriate to the scale of survey or to the level of detail dictated by different types of management and decision requirements; (3) permanent, publicly accessible sensor records for historical interpretation; (4) compatibility of the recording, storage, and retrieval system with all types of inputs, from ground observer to satellite; (5) products of diverse formats and scales, responsive to user feedback; (6) and standardization of formats, scales, and storage inputs to permit nationwide comparability.

Land use mapping↗

NASA NTRSDate not supplied

GOES-T Goddard Magnetometer Sensor Unit Flight Thermal Predictions and On-Orbit Thermal Performance

The GOES-T Goddard Magnetometer (GMAG) sensor unit (SU) thermal design was validated by SU level thermal balance (TB) testing. The correlated SU thermal model was integrated to the observatory thermal model to predict the outboard SU temperatures and operating heater duty cycles in the worst cold case and worst hot case orbits. An orbit with the highest solar beta angle (23.5°) and an orbit with the lowest solar beta angle (0°) were run for each case. A comparison in the SU temperature predictions and heater duty cycles were made. The Autumnal Equinox (AE) cold case orbit is slightly colder than the Winter Solstice (WS) cold case orbit. The WS hot case orbit is slightly warmer than the March Equinox (VE) hot case orbit. Additionally, the lunar eclipse cold case orbit was run. It is the coldest environment. Using a 23°C set point for the SU cover heater controller, there is positive heater control for all the orbits. The heater duty cycle predictions for the AE worst cold case orbit and WS worst hot case orbit were 44.4% and 33% respectively. During the lunar eclipse, the heater cycle increases to 68.8% at the end of the eclipse. The temperature predictions for the bobbins are in the 21.9°C to 22.8°C range in the AE worst cold case orbit and in the 21.8°C to 23.0°C range in the WS worst hot case orbit. The SU temperatures during nominal operation on orbit were expected to be within the design goal, despite seasonal variations in solar beta angle and solar irradiance, and no solar flux in a lunar eclipse. The maximum operating SU cover flight heater duty cycle was expected to comply with GOLD Rule 4.25. The SU thermal design is now flight proven based on its long-term (>1 year) thermal performance on orbit.

GOES-T↗