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At least 1,783 records · Page 99

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗

Progress Toward Fast Decay Energy Spectroscopy for Actinide Analysis

Decay energy spectroscopy (DES) is an increasingly popular technique for measuring isotopic composition of actinide samples for nuclear safeguards applications. Current approaches for actinide DES utilize milligram-scale external gold absorbers (> 0.1 nJ/K) that are integrated with actinide samples through mechanical kneading and are thermally connected to microcalorimeters using indium or gold wire bonds. This leads to relatively slow sensor rise time and, consequently, limits counting speed to a few counts per second. We are developing faster metallic magnetic calorimeter-based DES by integrating actinide samples with magnetic sensor materials. This reduces signal rise time and enables high counting speed while maintaining the ability to knead the radioactive source with the absorber. We have measured signal rise time of 0.7 μs with a 1.5 mg external gold absorber using this approach. Here, we also demonstrated online DES operation using an Ortec DSPEC 50, a commercially available data acquisition system developed for semiconductor detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗

Correlation tracking for a Planetary Pointing and Tracking System

The Planetary Pointing and Tracking System (PPTS) is being developed to provide precision pointing for science platforms on future autonomous planetary spacecraft. The PPTS design approach using a CCD optical sensor for closed-loop control with respect to the target body, a gyro for inertial stabilization, and brushless dc torque motors for smooth and continuous platform articulation is essential for high resolution planetary imaging and automated science execution. An integral part of PPTS is the correlation tracker which has the potential to revolutionize autonomous guidance.

Assefi, T.↗

Paving the way for space gardens

The Ecological Life Support System, a plant growth experiment now in its third year of closed chamber production at the NASA Kennedy Space Center, is discussed. Possible spin-off applications of hydrophonics experiments are noted. It is projected that long-term goals will include the integration of this garden system into the process of waste recycling for fertilization, air refreshment, and potable water recovery in a closed environment. The Biomass Production Chamber, a two-story bubble-shape steel biosphere modified from a Mercury/Gemini program attitude chamber provides a usable volume of 7.3 m x 3.6 m in diameter containing growing racks, piping for nutrient solutions, specialized lighting and sensors that provide information to the computers controlling the chamber and its functions. Computer programs provide highly sensitive monitoring and regulation of the system. Crops successfully harvested to date include dwarf wheat, lettuce, and soybeans.

Phillips, Patricia↗

Fiber-optic thermometer using Fourier transform spectroscopy

An integrated-optic Mach-Zender interferometer is used as a Fourier transform spectrometer to analyze the input and output spectra of a temperature-sensing thin-film etalon. This configuration provides a high degree of immunity to the effects of changes in the source spectrum, and it readily permits the interrogation of a number of different sensors using a single spectrometer. In addition, this system has a potentially low cost because it uses optical communications hardware that may in the future be manufactured in large quantities.

Beheim, Glenn↗

Propellant Feed System Leak Detection: Lessons Learned From the Linear Aerospike SR-71 Experiment (LASRE)

This paper presents pertinent results and assessment of propellant feed system leak detection as applied to the Linear Aerospike SR-71 Experiment (LASRE) program flown at the NASA Dryden Flight Research Center, Edwards, California. The LASRE was a flight test of an aerospike rocket engine using liquid oxygen and high-pressure gaseous hydrogen as propellants. The flight safety of the crew and the experiment demanded proven technologies and techniques that could detect leaks and assess the integrity of hazardous propellant feed systems. Point source detection and systematic detection were used. Point source detection was adequate for catching gross leakage from components of the propellant feed systems, but insufficient for clearing LASRE to levels of acceptability. Systematic detection, which used high-resolution instrumentation to evaluate the health of the system within a closed volume, provided a better means for assessing leak hazards. Oxygen sensors detected a leak rate of approximately 0.04 cubic inches per second of liquid oxygen. Pressure sensor data revealed speculated cryogenic boiloff through the fittings of the oxygen system, but location of the source(s) was indeterminable. Ultimately, LASRE was cancelled because leak detection techniques were unable to verify that oxygen levels could be maintained below flammability limits.

Hass, Neal↗

Saving Space and Time: The Tractor That Einstein Built

In 1984, NASA initiated the Gravity Probe B (GP-B) program to test two unverified predictions of Albert Einstein s theory of general relativity, hypotheses about the ways space, time, light, and gravity relate to each other. To test these predictions, the Space Agency and researchers at Stanford University developed an experiment that would check, with extreme precision, tiny changes in the spin direction of four gyroscopes contained in an Earth satellite orbiting at a 400-mile altitude directly over the Earth s poles. When the program first began, the researchers assessed using Global Positioning System (GPS) technology to control the attitude of the GP-B spacecraft accurately. At that time, the best GPS receivers could only provide accuracy to nearly 1 meter, but the GP-B spacecraft required a system 100 times more accurate. To address this concern, researchers at Stanford designed high-performance, attitude-determining hardware that used GPS signals, perfecting a high-precision form of GPS called Carrier-Phase Differential GPS that could provide continuous real-time position, velocity, time, and attitude sensor information for all axes of a vehicle. The researchers came to the realization that controlling the GP-B spacecraft with this new system was essentially no different than controlling an airplane. Their thinking took a new direction: If this technology proved successful, the airlines and the Federal Aviation Administration (FAA) were ready commercial markets. They set out to test the new technology, the "Integrity Beacon Landing System," using it to automatically land a commercial Boeing 737 over 100 times successfully through Real-Time Kinematic (RTK) GPS technology. The thinking of the researchers shifted again, from automatically landing aircraft, to automating precision farming and construction equipment.

Source record↗

Design and Testing of an Ultra-Light Weight Perching System for Sloped or Vertical Rough Surfaces on Mars

In this paper, we present the design, characterization, and functional demonstration of a perching system that enables a flying vehicle to land on rough sloped or vertical surfaces. Steep slopes are of particular scientific interest since they are often associated with geologically interesting features including sites of active modification (e.g. landslides/avalanches, slope streaks), exposed bedrock and/or ice, and as-yet unmodified young features (e.g. walls of fresh craters or polar pits that are actively expanding). However the steep nature of these sites makes access with traditional field robots difficult: ground vehicles are unable to traverse the steep terrain and aerial vehicles are limited by their flight time and an ability to operate near terrain. We propose to address these limitation by enabling the UAV to reliably perch on steep terrain to perform in situ measurements and collect samples. Perching also enables a solar powered UAV to traverse large terrain features such as the Valles Marineris that could not be covered in a single flight by repeatedly perching and recharging its batteries. The proposed perching system that is being developed consists of a microspine gripper, a compliant gripper to vehicle interface, and a flying vehicle equipped with an autonomy sensor suite. The system also includes perception and control algorithms that identify perching targets and execute the required perching maneuver. To date, the majority of the effort has focused on developing and characterizing the microspine gripper. The initial prototype weighs 100 g, is capable of securely grasping a range of natural surfaces, and successful grasps support loads of over 10 N. Refinement of the gripper, integrating and testing it on a UAV, measuring aerodynamic distrubances from wall effects, and developing the required perception and control algorithms is ongoing. This paper describes the overall architecture of our proposed system, the design of the gripper, and its performance during initial testing.

Backus, Spencer↗

MELDI2 Do No Harm Test Series

Mars 2020 will fly the Mars Entry, Descent, and Landing Instrumentation II (MEDLI2) sensor suite consisting of a total of seventeen instrumented thermal sensor plugs, eight pressure transducers, two heat flux sensors, and one radiometer embedded in the thermal protection system (TPS). Of the MEDLI2 instrumentation, eleven instrumented thermal plugs and seven pressure transducers will be installed on the heatshield of the Mars 2020 vehicle while the rest will be installed on the backshell. The goal of the MEDLI2 instrumentation is to directly inform the large performance uncertainties that contribute to the design and validation of a Mars entry system. A better understanding of the entry environment and TPS performance could lead to reduced design margins enabling a greater payload mass-fraction and smaller landing ellipses. To prove that the MEDLI2 system will not degrade the performance of the Mars 2020 TPS, an Aerothermal Do No Harm (DNH) test series was designed and conducted. Like Mars 2020's predecessor, Mars Science Laboratory (MSL), the heatshield material will be Phenolic Impregnated Carbon Ablator (PICA); the Mars 2020 entry conditions are enveloped by the MSL design environments, therefore the development and qualification testing performed during MEDLI is sufficient to show that the similar MEDLI2 heatshield instrumentation will not degrade PICA performance. However, given that MEDLI did not include any backshell instrumentation, the MEDLI2 team was required to design and execute a DNH test series utilizing the backshell TPS material (SLA-561V) with the intended flight sensor suite. To meet the requirements handed down from Mars 2020, the MEDLI2 DNH test series emphasized the interaction between the MEDLI2 sensors and sensing locations with the surrounding backshell TPS and substrucutre. These interactions were characterized by performing environmental testing of four 12" by 12" test panels, which mimicked the construction of the backshell TPS and the integration of the MEDLI2 sensors as seen in Figure 1. The testing included thermal vacuum/ cycling, random vibration, shock, and arc jet testing. The test panels were fabricated by Lockheed Martin, establishing techniques that will be utilized during the Mars 2020 vehicle installation. Each test panel included one thermal sensor plug (two embedded thermocouples), one heat flux sensor, and multiple pressure port holes for evaluation. This presentation will discuss the planning and execution of the MEDLI2 DNH test series. Selected highlights and results of each environmental test will be presented, and lessons learned will be addressed that will feed forward into the planning for the MEDLI2 flight system certification testing.

Heatshield↗

Post-Flight Assessment of Avcoat Thermal Protection System for the Exploration Flight Test-1

On December 5, 2014 NASA conducted the first flight test of its next generation human-class Orion spacecraft. The flight was called the Exploration Flight Test -1 (EFT-1) which lasted for 4 hours and culminated into a re-entry trajectory at 9 km/s. This flight test of the 5-meter Orion Crew Module demonstrated various sub-systems including the Avcoat ablative thermal protection system (TPS) on the heat shield. The Avcoat TPS had been developed from the Apollo-era recipe with a few key modifications. The engineering for thermal sizing was supported by modeling, analysis, and ground tests in arc jet facilities. This paper will describe a postlfight analysis plan and present results from post-recovery inspections, data analysis from embedded sensors, TPS sample extraction and characterization in the laboratory. After the recovery of the vehicle, a full photographic survey and surface scans of the TPS were performed. The recovered vehicle showed physical evidence of flow disturbances, varying degrees of surface roughness, and excessive recession downstream of compression pads. The TPS recession was measured at more than 200 locations of interest on the Avcoat surface. The heat shield was then processed for sample extraction prior to TPS removal using the 7-Axis Milling machine at Marshall Space Flight Center. Around 182 rectangular TPS samples were extracted for subsequent analysis and investigation. The final paper will also present results of sample analysis. The planned investigation includes sidewall imaging, followed by image analysis to characterize TPS response by quantifying different layers in the char and pyrolysis zones. A full postmortem of the instrumentation and sensor ports will also be performed to confirm no adverse effects due to the sensors themselves. A subset of the samples will undergo structural testing and perform detailed characterization of any cracks and integrity of gore seams. Finally, the material will be characterized with layer-by-layer density measurements and SEM investigations to evaluate material morphology at microstructural level including identification of elements and compounds.

Aerothermodynamics↗

Equation‐Free Surrogate Modeling of Geophysical Flows at the Intersection of Machine Learning and Data Assimilation

Abstract There is a growing interest in developing data‐driven reduced‐order models for atmospheric and oceanic flows that are trained on data obtained either from high‐resolution simulations or satellite observations. The data‐driven models are non‐intrusive in nature and offer significant computational savings compared to large‐scale numerical models. These low‐dimensional models can be utilized to reduce the computational burden of generating forecasts and estimating model uncertainty without losing the key information needed for data assimilation (DA) to produce accurate state estimates. This paper aims at exploring an equation‐free surrogate modeling approach at the intersection of machine learning and DA in Earth system modeling. With this objective, we introduce an end‐to‐end non‐intrusive reduced‐order modeling (NIROM) framework equipped with contributions in modal decomposition, time series prediction, optimal sensor placement, and sequential DA. Specifically, we use proper orthogonal decomposition (POD) to identify the dominant structures of the flow, and a long short‐term memory network to model the dynamics of the POD modes. The NIROM is integrated within the deterministic ensemble Kalman filter (DEnKF) to incorporate sparse and noisy observations at optimal sensor locations obtained through QR pivoting. The feasibility and the benefit of the proposed framework are demonstrated for the NOAA Optimum Interpolation Sea Surface Temperature (SST) V2 data set. Our results indicate that the NIROM is stable for long‐term forecasting and can model dynamics of SST with a reasonable level of accuracy. Furthermore, the prediction accuracy of the NIROM gets improved by almost one order of magnitude by the DEnKF algorithm.

Pawar, Suraj↗

Test Flights of NOAA Ozone Photometer for Uncrewed Aerial Systems (UAS)/Balloon-Based Studies (OPUS) during TRACER (Field Campaign Report)

We proposed to integrate and fly the National Oceanic and Atmospheric Administration (NOAA) Ozone Photometer for Uncrewed Aerial Systems (UAS)/Balloon-Based Studies (OPUS) on the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s tethered balloon system (TBS) during the second phase (August 1-15) of the 2022 Tracking Aerosol Convection Interactions Experiment (TRACER) in southwest Houston, Texas. The two main goals were: 1) Test fly the sensor to discover and address any potential problems such as interface and communication with other instruments, interferences with other instruments and radio, and 2) If OPUS performs well, then inter-compare OPUS with the EN-SCI ozonesondes that will also be flown on the TBS. The collaborating institutions are DOE Sandia National Laboratories TBS team, the University of Houston, and St. Edward's University.

47 OTHER INSTRUMENTATION↗

Comparing the Use of High- to Low-Cost Black Carbon and Carbon Dioxide Sensors for Characterizing On-Road Diesel Truck Emissions

The exhaust plume capture method is a commonly used approach to measure pollutants emitted by in-use heavy-duty diesel trucks. Lower cost sensors, if used in place of traditional research-grade analyzers, could enable wider application of this method, including use as a monitoring tool to identify high-emitting trucks that may warrant inspection and maintenance. However, low-cost sensors have for the most part only been evaluated under ambient conditions as opposed to source-influenced environments with rapidly changing pollutant concentrations. This study compared black carbon (BC) emission factors determined using different BC and carbon dioxide (CO 2 ) sensors that range in cost from $200 to $20,000. Controlled laboratory experiments show that traditional zero and span steady-state calibration checks are not robust indicators of sensor performance when sampling short duration concentration peaks. Fleet BC emission factor distributions measured at two locations at the Port of Oakland in California with 16 BC/CO 2 sensor pairs were similar, but unique sensor pairs identified different high-emitting trucks. At one location, the low-cost PP Systems SBA-5 agreed on the classification of 90% of the high emitters identified by the LI-COR LI-7000 when both were paired with the Magee Scientific AE33. Conversely, lower cost BC sensors when paired with the LI-7000 misclassified more than 50% of high emitters when compared to the AE33/LI-7000. Confidence in emission factor quantification and high-emitter identification improves with larger integrated peak areas of CO 2 and especially BC. This work highlights that sensor evaluation should be conducted under application-specific conditions, whether that be for ambient air monitoring or source characterization.

47 OTHER INSTRUMENTATION↗

Development of mining guidance and control systems

New fundamental interface sensor concepts were identified and investigated including tabulation of the physical and performance characteristics of two new interface detector concepts: - natural background radiation and magnetic spin resonance. Studies of guidance and control techniques for the longwall miner identified three basic systems for use in automated/remote controlled longwall mining. The following projects were initiated: system study which will more completely define the longwall guidance and control system design concepts; integration of the various control functions (vertical, yaw, and roll); and hardware technical requirements.

Source record↗

Wind tunnel balance

A flow-through balance is provided which includes a non-metric portion and a metric portion which form a fluid-conducting passage in fluid communication with an internal bore in the sting. The non-metric and metric portions of the balance are integrally connected together by a plurality of flexure beams such that the non-metric portion, the metric portion and the flexure beams form a one-piece construction which eliminates mechanical hysteresis between the non-metric and the metric portion. The system includes structures for preventing the effects of temperature, pressure and pressurized fluid from producing asymmetric loads on the flexure beams. A temperature sensor and a pressure sensor are located within the fluid-conducting passage of the balance. The system includes a longitudinal bellows member connected at two ends to one of the non-metric portion and the metric portion and at an intermediate portion thereof to the other of (1) and (2). A plurality of strain gages are mounted on the flexure beams to measure strain forces on the flexure beams. The flexure beams are disposed so as to enable symmetric forces on the flexure beams to cancel out so that only asymmetric forces are measured as deviations by the strain gages.

Horne, Warren L.↗

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗

Autonomous reconfigurable GPS/INS navigation and pointing system for rendezvous and docking

This paper describes the results of an integrated navigation and pointing system software development effort sponsored by the NASA MSFC through a SBIR Phase 2 Program. The integrated Global Positioning System (GPS)/Inertial Navigation System (INS) implements an autonomous navigation filter that is reconfigurable in real-time to accommodate mission contingencies. An onboard expert system monitors the spacecraft status and reconfigures the navigation filter accordingly, to optimize the system performance. The navigation filter is a multi-mode Kalman filter to estimate the spacecraft position, velocity, and attitude. Three different GPS-based attitude determination techniques, namely, velocity vector matching, attitude vector matching, and interferometric processing, are implemented to encompass different mission contingencies. The integrated GPS/INS navigation filter will use any of these techniques depending on the mission phase and the state of the sensors. The first technique, velocity vector matching, uses the GPS velocity measurement to estimate the INS velocity errors and exploits the correlation between INS velocity and attitude errors to estimate the attitude. The second technique, attitude vector matching, uses INS gyro measurements and GPS carrier phase (integrated Doppler) measurements during a spacecraft rotation maneuver to determine the attitude. Both of these techniques require only one GPS antenna onboard to determine the spacecraft attitude. The third technique, interferometric processing, requires use of multiple GPS antennae. In order to determine 3-axis body attitude, three GPS antennae (2 no-coplanor baselines) are required.

Upadhyay, Triveni N.↗