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NASA NTRS2015

Automated Segmentation and Classification of Coral Using Fluid Lensing from Unmanned Airborne Platforms

In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the worlds coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

algorithms segments classifications↗

NASA NTRS2017

Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER)

Abstract: NASA is currently investigating methods to reduce the boil-off rate on large cryogenic upper stages. Two such methods to reduce the total heat load on existing upper stages are vapor cooling of the cryogenic tank support structure and integration of thick multilayer insulation systems to the upper stage of a launch vehicle. Previous efforts have flown a 2-layer MLI blanket and shown an improved thermal performance, and other efforts have ground-tested blankets up to 70 layers thick on tanks with diameters between 2 3 meters. However, thick multilayer insulation installation and testing in both thermal and structural modes has not been completed on a large scale tank. Similarly, multiple vapor cooled shields are common place on science payload helium dewars; however, minimal effort has gone into using boil-off to intercept heat on large structural surfaces associated with rocket stages. A majority of the vapor cooling effort focuses on metallic cylinders called skirts, which are the most common structural components for launch vehicles. In order to provide test data for comparison with analytical models, a 4 meter diameter test tank and assembly is currently being designed to include skirt structural systems with integral vapor cooling. In order to give a more representative result for actual applications, the technologies will be designed for an 8.4 m and scaled down to a 4 meter tank. In order to prove that the insulation system and vapor cooling attachment methods are structurally sound, acoustic testing will also be performed on the system. The test tank with insulation and vapor cooled shield installed will be tested thermally in the B2 test facility at NASAs Plum Brook Station both before and after being vibration tested at Plum Brooks Space Power Facility.

Johnson, Wesley↗

NASA NTRS2019

Kestrel Results at Liftoff Conditions for a Space Launch System Configuration in Proximity to the Launch Tower

Aerodynamic data books for Space Launch System vehicles require databases for the integrated forces and moments and section loads during liftoff and transition to the ascent phase of flight. While the force and moment database can be generated from wind tunnel results, computational analyses are necessary to provide the extensive surface information required to generate proper lineloads. Of the two flight regimes, the liftoff problem is the more costly and complex situation to simulate, as it requires modeling of the vehicle in proximity to the launch tower. The effects of massive separation on the leeward pressure fields of both the tower and vehicle are not well captured with RANS methods, necessitating the use of more advanced methods, such as Delayed Detached Eddy Simulation, in conjunction with computational grids sufficiently refined to resolve the wakes. Details on the computational setup for employing the Kestrel flow solver to address the liftoff problem are presented. The methodology involves the use of independent unstructured near-body grids for the vehicle and the tower, overset by a solution adaptive Cartesian off-body grid. Results from the simulations are compared to experimental results from a test in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel.

Computational fluid dynamics↗

NASA NTRSDate not supplied

Comparison of Two Community Noise Models Applied to a NASA Urban Air Mobility Concept Vehicle

Predictions of community noise exposure from a NASA urban air mobility (UAM) concept vehicle have been conducted for representative operations using the FAA Aviation Environmental Design Tool (AEDT) in order to demonstrate modeling tool interoperability and assess applicability, capabilities and limitations of integrated noise modeling tools. To both quantify limitations and highlight other capabilities, a comparative analysis is performed using a time-domain simulation method, in particular, using the Volpe Advanced Acoustic Model (AAM). Using the same source noise model, the 3D directivity of a UAM concept vehicle is predicted in terms of aeroacoustic pressure time histories at a sphere of observer positions near the vehicle. In addition to distilling those data to a set of noise-power-distance data for input to AEDT, the data are processed preserving spectral directivity, into one-third and one-twelfth octave bands for input to AAM. Results from AEDT and AAM modeling are provided for a variety of metrics to demonstrate the effect that source noise directivity and propagation modeling fidelity have on predicted results at receptors over a study area.

urban air mobility↗

NASA NTRSDate not supplied

DRF: A Software Architecture for a Data Marketplace to Support Advanced Air Mobility

Advanced Air Mobility is a new aviation vision, where unmanned aerial systems will trans- port passengers and cargo across urban and rural areas. Critical to the realization of this vision is the development of a digital marketplace, which allows service providers and consumers operating in the airspace ecosystem to securely exchange data and reasoning insights. In this paper, we present the architecture of a decentralized data marketplace that connects data and reasoning service providers to vehicles and other service consumers along the cloud-to-edge continuum. We also present two example use cases to demonstrate the value of our approach.

Autonomy↗

NASA NTRSDate not supplied

Comparison of Two Community Noise Models Applied to a NASA Urban Air Mobility Concept Vehicle

urban air mobility↗

NASA NTRS2021

Time-Resolved Observations of Precipitation Structure and Storm Intensity with a Constellation of Smallsats: Level-1 Radiance Algorithm Theoretical Basis Document

This Algorithm Theoretical Basis Document (ATBD) describes the theoretical background of the TROPICS native radiance calibration algorithms. It also includes TROPICS payload characteristics and the algorithm’s ancillary data (i.e., data coming from sources other than the TROPICS Space Vehicle). Details of the native radiance (i.e., Level-1a antenna temperatures and Level-1b brightness temperatures) data product format can be found in the TROPICS Data User’s Guide. This ATBD information on the pre-launch testing completed to verify the algorithm. The TROPICS Data User’s Guide will contain the post-launch radiance validation.

TROPICS↗

NASA NTRSDate not supplied

Evaluation of Heave Disturbance Rejection and Control Response Criteria on the Handling Qualities Evaluation of Urban Air Mobility (UAM) eVTOL Quadrotors Using the Vertical Motion Simulator

The first piloted handling qualities study of an urban air mobility (UAM) vehicle leveraging the Vertical Motion Simulator (VMS) at NASA Ames Research Center was conducted in Spring 2021. The VMS provides a unique capability to reduce risk by assessing and iterating control designs. Minimal sources currently exist to provide performance and handling qualities data for large, rotor speed-controlled vehicles outside of the software environment. The study compares multiple handling qualities performance configurations for rotor speed and blade pitch-controlled variants of a six-passenger quadrotor conceptual design model developed by the NASA Revolutionary Vertical Lift Technology (RVLT) Project. Additionally, both ADS-33 and a tailored set of performance standards (notionally representing the agility required of a UAM mission) are examined under conditions with and without light turbulence. Preliminary results did show significant variation in ratings based on the set of standards utilized, controller tuning to either Level 1 or boundary Level 1/ Level 2 conditions, and presence or lack of turbulence. A custom approach and landing maneuver was also designed to bring these evaluation tasks together in a more comprehensive application.

Handling Qualities↗

NASA NTRS2022

Using Trajectory Smoothness Metrics to Identify Drones in Radar Track Data

The identification of unmanned aircraft systems (UAS) using trajectory data is considered. Specifically, a number of smoothness metrics are proposed, which can be used to distinguish UAS from other aerial objects even when they are engaged in accelerative maneuvers (non-constant-velocity flight). The metrics are evaluated on a data set from a UAS sense-and-avoid field test, which contains track data of aerial objects recorded by a vehicle-board radar system during a flight test. The metrics are found to effectively differentiate UAS from other objects such as birds for this data set. In addition, an initial statistical performance analysis of one of the smoothness metrics is undertaken, using 15 data sets deriving from multiple flight tests. The smoothness metric is shown to identify the target UAS with 95% accuracy (95% true positive rate), while achieving a false positive rate of less than 9%.

Sandip Roy↗

NASA NTRS2022

A Rideshare Tensegrity Rover Concept to Explore Titan’s Lands and Oceans

The Tension Adjustable Network for Deploying Entry Membrane (TANDEM) concept is a phase II NASA Innovative Advanced Concepts (NIAC) project. One of the goals for this project was to extend the application of tensegrity-based rovers to a rideshare concept for a Titan mission. This report provides preliminary details of the TANDEM concept for Titan. System analyses of the entry vehicle were performed and compared to data from the Huygens mission to Titan. The entry aeroshell was based on Huygens and Stardust aeroshells. Modeling, simulation and design of the tensegrity deployment were performed using a nonlinear optimization form-finding algorithm. Lastly, a neuroevolution-based machine learning control strategy was applied, which produced efficient rolling locomotion gaits.

tensegrity↗

NASA NTRSDate not supplied

Ab Initio Electronic Structure Calculations of CNN for CN Excitation Studies

The CN molecule is an important contributor to radiative heat flux in shock layers around vehicles entering Titan’s atmosphere. Current data for heavy particle (de)excitation rate coefficients of CN leads to uncertainties in the population of CN in its first and second excited states. This in turn leads to uncertainties in the radiative heat flux predicted by Computational Fluid Dynamics (CFD) simulations of Titan atmospheric entry. This work performs ab initio electronic structure calculations of the CNN complex to create Potential Energy Surfaces (PESs) that correlate to the ground and first and second excited states of CN. Specifically, the state combinations of CN(X,A,B) + N(4S𝑜) correlate to six states of CNN (three Quintet A” and three Triplet A”). Initial calculations of these states suggest that heavy particle (de)excitation of CN by N atoms is likely to proceed through collinear geometries on triplet surfaces. Complete PESs will show all of the reaction pathways in detail, and will be used in nonadiabatic dynamics calculations to evaluate improved rate coefficients and reduce uncertainty in the radiative heat flux during Titan entry.

Eric C Geistfeld↗

NASA NTRSDate not supplied

Ab Initio Electronic Structure Calculations of CNN for CN Excitation Studies

Eric Geistfeld↗

DOE OSTI2020

2018 Renewable Energy Data Book

The 2018 Renewable Energy Data Book provides facts and figures on energy and electricity use, renewable electricity in the United States, global renewable energy development, wind power, solar power, geothermal power, biopower, hydropower, marine and hydrokinetic power, battery storage, hydrogen, renewable fuels, voluntary procurement and clean energy investment.

2018 data↗

DOE OSTI2020

Automated Vehicle Detection in a Nuclear Facility Using Low-Frequency Acoustic Sensors

This article presents an analysis of the method of construction and results for a classifier intended to identify vehicles using low-frequency acoustic data collected by a dis-tributed sensor network. This data is collected as part of a venture intended to explore data analytics and multisensor fusion techniques for the monitoring of activities at a test bed nuclear facility located at Oak Ridge National Laboratory in Oak Ridge, Tennessee. We describe the associated target signature and design a classifier based on a multilayer perceptron, followed by an analysis of its results. We discuss how overall accuracy is not the only consideration in constructing this classifier, and how for this application, it is actually desirable to operate at a lower level of accuracy in exchange for a reduction in the false alarm rate, as well as how this relates to the actual deployment of the classifier in practical use.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

NASA NTRS2011

Ground Processing Affordability for Space Vehicles

Launch vehicles and most of their payloads spend the majority of their time on the ground. The cost of ground operations is very high. So, why so often is so little attention given to ground processing during development? The current global space industry and economic environment are driving more need for efficiencies to save time and money. Affordability and sustainability are more important now than ever. We can not continue to treat space vehicles as mere science projects. More RLV's (Reusable Launch Vehicles) are being developed for the gains of reusability which are not available for ELV's (Expendable Launch Vehicles). More human-rated vehicles are being developed, with the retirement of the Space Shuttles, and for a new global space race, yet these cost more than the many unmanned vehicles of today. We can learn many lessons on affordability from RLV's. DFO (Design for Operations) considers ground operations during design, development, and manufacturing-before the first flight. This is often minimized for space vehicles, but is very important. Vehicles are designed for launch and mission operations. You will not be able to do it again if it is too slow or costly to get there. Many times, technology changes faster than space products such that what is launched includes outdated features, thus reducing competitiveness. Ground operations must be considered for the full product Lifecycle, from concept to retirement. Once manufactured, launch vehicles along with their payloads and launch systems require a long path of processing before launch. Initial assembly and testing always discover problems to address. A solid integration program is essential to minimize these impacts, as was seen in the Constellation Ares I-X test rocket. For RLV's, landing/recovery and post-flight turnaround activities are performed. Multi-use vehicles require reconfiguration. MRO (Maintenance, Repair, and Overhaul) must be well-planned--- even for the unplanned problems. Defect limits and standard repairs need to be in-place as well as easily added. Many routine inspections and maintenance can be like an aircraft overhaul. Modifications and technology upgrades should be expected. Another factor affecting ground operations efficiency is trending. It is essential for RLV's, and also useful for ELV's which fly the same or similar models again. Good data analysis of technical and processing performance will determine fixes and improvements needed for safety, design, and future processing. Collecting such data on new or low-frequency vehicles is a challenge. Lessons can be learned from the Space Shuttle, or even the Concorde aircraft. For all of the above topics, efficient business systems must be established for comprehensive program management and good throughput. Drawings, specifications, and manuals for an entire launch vehicle are often in different formats from multiple vendors, plus they have proprietary constraints. Nonetheless, the integration team must ensure that all data needed is compatible and visible to each appropriate team member. Ground processing systems for scheduling, tracking, problem resolution, etc. must be well laid-out. The balance between COTS (commercial off the shelf) and custom software is difficult. Multiple customers, vendors, launch sites, and landing sites add to the complexity of efficient IT (Information Technology) tools.

Ingalls, John↗

DOE OSTI2022

Trajectory prediction dimensionality reduction for low-cost connected automated vehicle systems

Here, to facilitate low-cost connected automated vehicle (CAV) system development, this study proposes two interpretable dimensionality reduction techniques in vehicle trajectory prediction, i.e., the piecewise Taylor series approximation (PTA) and the piecewise Fourier series approximation (PFA), to lower computation complexity, reduce device investment, and decrease computation energy consumption. Two benchmarks are developed, the long short-term memory (LSTM)-based model without dimensionality reduction and the LSTM-based model with encoder-decoder (a widely used dimensionality reduction technique). Results show that the four predictions have similar accuracy, and the training time (proportional to computation energy consumption) of models with dimensionality reduction techniques is greatly reduced. The reduction is even more significant when PTA/PFA is used. Sensitivity analysis advises PFA/PTA parameter selections to reduce computation complexity without significant loss of prediction accuracy. Further, the robustness of the LSTM PTA/PFA is proven by the investigation of data noises.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

HIFiRE Flight 2 Unstart Reliability Analysis

The objective of this work was to assess the unstart reliability of the HIFiRE Flight 2 system. To do this, a quantification of margins and uncertainties framework was used for comparing model predictions of the predicted combustion induced shock location to the predicted last stable shock location within the isolator. Uncertainty sources included parametric uncertainty in the flight conditions, the heat release model, and turbulence modeling, as well as model verification errors. Additionally, an estimate of model-form uncertainty was established by comparing the model to measured ground test data. A computationally efficient non-intrusive polynomial chaos approach was used to propagate parametric uncertainty through the computational flu-ids dynamics models of both the ground test configuration and the flight vehicle. Compared to direct-connect ground test data, computational fluid dynamics predictions yielded about two duct heights of model-form uncertainty. This was applied to a prediction of flight vehicle unstart margin at the Mach 6.5 flight condition. Building up all of the computational model uncertainty, including parametric uncertainty, verification errors, and the determined model-form uncertainty, a 95% probability level based confidence ratio, or a ratio of total uncertainty to a statistical margin measure, was found to be 0.31 for the flight system.

Thomas K West↗

DOE OSTI2025

Topography, surface water distribution and subsurface structure in 2023 across an Arctic coastal tundra site near Utqiagvik, Alaska

Subsurface electrical resistivity tomography (ERT), active layer thickness measurements, photogrammetry, and topographic data were collected in September 2023 along a 475 m long, 20 m wide corridor that traverses various polygon types within the Barrow Environmental Observatory (BEO) on the Alaskan Arctic Coastal Plain, approximately 4 miles from the Beaufort Sea near Utqiaġvik, Alaska. These measurements were designed to assess decadal changes in surface water distribution, topography, and subsurface structure across this dynamic landscape. This archive contains the datasets acquired in 2023 and references to the datasets acquired previously at the same location. The ERT survey was conducted along the 475 m transect using 0.5 m electrode spacing and a roll-along acquisition strategy. Thaw layer thicknesses were measured with a tile probe along the same transect. Photogrammetry data were acquired using an unoccupied aerial vehicle (UAV) and were used to generate a digital elevation model and an RGB mosaic. A real-time kinematic (RTK) GPS was used to survey the ERT electrodes and the ground control points for the aerial imagery. The dataset contains 5 *.csv data files, 6 *.csv metadata files, and 6 *.tif files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗