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DOE OSTI2022

Landfill Emissions of Methane Inferred from Unmanned Aerial Vehicle and Mobile Ground Measurements

Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions.

Olaguer, Eduardo P.↗

DOE OSTI2025

Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data

This research study utilized artificial intelligence (AI) to detect natural disasters from aerial images. Flooding and desertification were two natural disasters taken into consideration. The Climate Change Dataset was created by compiling various open-access data sources. This dataset contains 6334 aerial images from UAV (unmanned aerial vehicles) images and satellite images. The Climate Change Dataset was then used to train Deep Learning (DL) models to identify natural disasters. Four different Machine Learning (ML) models were used: convolutional neural network (CNN), DenseNet201, VGG16, and ResNet50. These ML models were trained on our Climate Change Dataset so that their performance could be compared. DenseNet201 was chosen for optimization. All four ML models performed well. DenseNet201 and ResNet50 achieved the highest testing accuracies of 99.37% and 99.21%, respectively. This research project demonstrates the potential of AI to address environmental challenges, such as climate change-related natural disasters. This study’s approach is novel by creating a new dataset, optimizing an ML model, cross-validating, and presenting desertification as one of our natural disasters for DL detection. Three categories were used (Flooded, Desert, Neither). Our study relates to AI for Climate Change and Environmental Sustainability. Drone emergency response would be a practical application for our research project.

AI↗

DOE OSTI2020

Vegetation Detection Using Deep Learning and Conventional Methods

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.

58 GEOSCIENCES↗

DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

A new aerial approach for quantifying and attributing methane emissions: implementation and validation

Methane (CH 4 ) is a powerful greenhouse gas that is produced by a diverse set of natural and anthropogenic emission sources. Biogenic methane sources generally involve anaerobic decay processes such as those occurring in wetlands, melting permafrost, or the digestion of organic matter in the guts of ruminant animals. Thermogenic CH 4 sources originate from the breakdown of organic material at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C 2 H 6 ). Here, we present the development and deployment of an uncrewed aerial system (UAS) that employs a fast (1 Hz) and sensitive (1–0.5 ppb s -1 ) CH 4 and C 2 H 6 sensor and ultrasonic anemometer. The UAS platform is a vertical-takeoff, hexarotor drone (DJI Matrice 600 Pro, M600P) capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. Simultaneous measurements of CH 4 and C 2 H 6 concentrations, vector winds, and positional data allow for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The system has been used for direct quantification of methane point sources, such as orphan wells, and distributed emitters, such as landfills and wastewater treatment facilities. With detectable source rates as low as 0.04 and up to ~1500 kg h -1 , this UAS offers a direct and repeatable method of horizontal and vertical profiling of emission plumes at scales that are complementary to regional aerial surveys and localized ground-based monitoring.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

UAS remote sensing (DJI Phantom 4 RTK platform): RGB orthomosaic, digital surface and canopy height models, plant functional type map, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using a DJI Phantom 4 RTK unoccupied aerial system (UAS) ? operated by the University of Maine Wheatland Geospatial Lab (https://wheatlandlab.org/). This package includes data from 17 flights flown over the NGEE-Arctic Council, Kougarok, Kougarok Mile80, Teller, and Teller Mile32 sites in July 2019. The Phantom 4 RTK is a drone platform that collects very high spatial resolution optical red/green/blue (RGB) imagery. Derived image products include point cloud, ortho-mosaiced RGB, a digital surface model (DSM) using the structure from motion (SfM) technique, and a canopy height model (CHM). Unprocessed and processed data products (1,000+ files) are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *hdr,), ENVI image file (*.dat), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. 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↗

DOE OSTI2026

Energy Storage Technologies and U.S. Department of War Requirements

This report offers an overarching primer the energy storage market and assessment of each technology’s suitability for U.S. Department of War applications. We find that battery energy storage is the most promising technology for energy storage applications in terms of energy density and cost. While commercial and advanced Li-ion can satisfy certain electric mobility (e.g., cars, midsized vehicles) and electric flight application (e.g. drones) needs of DoW, next generation technologies like Li metal solid-state batteries, and conversion chemistries (Li-air, Li-CFx) are needed for heavy duty applications like armored vehicles, tanks, airplanes, jets. Batteries should also be supplemented with technologies such as supercapacitors and next-generation flywheels to provide short bursts of high energy for high power needs. Thermal energy storage solutions (sensible and latent heat) and fuel cells (PEMFC and SOFC) are good alternatives for supporting energy storage applications in terms of energy density and cost. Gravity-based energy storage promises the least energy density with high cost and should only be used for niche DoW applications. Of the different gravity energy storage technologies reviewed, pumped-hydro, flywheel, and compressed air energy storage are promising, while solid gravity energy storage appears the least attractive. Military facilities requiring 14 days of energy storage can benefit from flow batteries, especially commercial VFRBs and next generation iron-air systems. While VFRBs are expensive, iron-air batteries have the coupled benefits of low cost and good energy density promising 100+ hours of storage.

25 ENERGY STORAGE↗

NASA NTRS1976

FLEXSTAB analysis

The wing differential pressure distributions of two vehicles are predicted using FLEXSTAB. Three space shuttle configurations were investigated. Comparisons were made of wind tunnel and analytical data for a selected range of angle of attack, angle of sideslip, and Mach number. A drone-type vehicle was investigated and comparisons were made between flight and analytical data of wing pressure distributions and static longitudinal stability derivatives.

Lowder, H. E., Jr.↗

NASA NTRS1976

Clear air convective behavior revealed by radar chaff

A simple experiment is described in which chaff was injected into the updraft region of individual clear-air convective cells in order to clarify characteristics of such convective elements. The chaff was dispensed automatically by a small radio-controlled drone aircraft and also by hand from the ground. It is found that clear-air convective cells are roughly spherical in form, that rapid mixing occurs within a cell, and that little mixing occurs between adjacent cells. Some suggestions are offered for future work in the tracing of air motions arising from the ground.

Rowland, J. R.↗

NASA NTRS1976

The design and fabrication of microstrip omnidirectional array antennas for aerospace applications

A microstrip antenna design concept was developed that will provide quasi-omnidirectional radiation pattern characteristics about cylindrical and conical aerospace structures. L-band and S-band antenna arrays were designed, fabricated, and, in some cases, flight tested for rocket, satellite, and aircraft drone applications. Each type of array design is discussed along with a thermal cover design that was required for the sounding rocket applications.

Campbell, T. G.↗

NASA NTRS1978

Development and application of an optimization procedure for flutter suppression using the aerodynamic energy concept

An optimization procedure is developed based on the responses of a system to continuous gust inputs. The procedure uses control law transfer functions which have been partially determined by using the relaxed aerodynamic energy approach. The optimization procedure yields a flutter suppression system which minimizes control surface activity in a gust environment. The procedure is applied to wing flutter of a drone aircraft to demonstrate a 44 percent increase in the basic wing flutter dynamic pressure. It is shown that a trailing edge control system suppresses the flutter instability over a wide range of subsonic mach numbers and flight altitudes. Results of this study confirm the effectiveness of the relaxed energy approach.

Nissim, E.↗

NASA NTRS1979

The development of the DAST I remotely piloted research vehicle for flight testing an active flutter suppression control system

The development of the DAST I (drones for aerodynamic and structural testing) remotely piloted research vehicle is described. The DAST I is a highly modified BQM-34E/F Firebee II Supersonic Aerial Target incorporating a swept supercritical wing designed to flutter within the vehicle's flight envelope. The predicted flutter and rigid body characteristics are presented. A description of the analysis and design of an active flutter suppression control system (FSS) designed to increase the flutter boundary of the DAST wing (ARW-1) by a factor of 20% is given. The design and development of the digital remotely augmented primary flight control system and on-board analog backup control system is presented. An evaluation of the near real-time flight flutter testing methods is made by comparing results of five flutter testing techniques on simulated DAST I flutter data. The development of the DAST ARW-1 state variable model used to generate time histories of simulated accelerometer responses is presented. This model uses control surface commands and a Dryden model gust as inputs. The feasibility of the concept of extracting open loop flutter characteristics from closed loop FSS responses was examined. It was shown that open loop characteristics can be determined very well from closed loop subcritical responses.

Grose, D. L.↗

NASA NTRS1981

The DAST-1 remotely piloted research vehicle development and initial flight testing

The development and initial flight testing of the DAST (drones for aerodynamic and structural testing) remotely piloted research vehicle, fitted with the first aeroelastic research wing ARW-I are presented. The ARW-I is a swept supercritical wing, designed to exhibit flutter within the vehicle's flight envelope. An active flutter suppression system (FSS) designed to increase the ARW-I flutter boundary speed by 20 percent is described. The development of the FSS was based on prediction techniques of structural and unsteady aerodynamic characteristics. A description of the supporting ground facilities and aircraft systems involved in the remotely piloted research vehicle (RPRV) flight test technique is given. The design, specification, and testing of the remotely augmented vehicle system are presented. A summary of the preflight and flight test procedures associated with the RPRV operation is given. An evaluation of the blue streak test flight and the first and second ARW-I test flights is presented.

Kotsabasis, A.↗

NASA NTRS1981

Advanced aerodynamics and active controls. Selected NASA research

Aerodynamic and active control concepts for application to commercial transport aircraft are discussed. Selected topics include in flight direct strike lightning research, triply redundant digital fly by wire control systems, tail configurations, winglets, and the drones for aerodynamic and structural testing (DAST) program.

Source record↗

NASA NTRS1981

Wake Vortex Attenuation Flight Tests: A Status Report

Flight tests were conducted to evaluate the magnitude of aerodynamic attenuation of the wake vortices of large transport aircraft that can be achieved through the use of static spoiler deflection and lateral control oscillation. These methods of attenuation were tested on Boeing B-747 and Lockheed L-1011 commercial transport aircraft. Evaluations were made using probe aircraft, photographic and visual observations, and ground based measurements of the vortex velocity profiles. The magnitude of attenuation resulting from static spoiler deflection was evaluated both in and out of ground effect. A remotely piloted QF-86 drone aircraft was used to probe the attenuated vortices in flight in and out of ground effect, and to make landings behind an attenuated B-747 airplane at reduced separation distances.

Barber, Marvin R.↗

NASA NTRS1981

Application of constrained optimization to active control of aeroelastic response

Active control of aeroelastic response is a complex in which the designer usually tries to satisfy many criteria which are often conflicting. To further complicate the design problem, the state space equations describing this type of control problem are usually of high order, involving a large number of states to represent the flexible structure and unsteady aerodynamics. Control laws based on the standard Linear-Quadratic-Gaussian (LQG) method are of the same high order as the aeroelastic plant. To overcome this disadvantage of the LQG mode, an approach developed for designing low order optimal control laws which uses a nonlinear programming algorithm to search for the values of the control law variables that minimize a composite performance index, was extended to the constrained optimization problem. The method involves searching for the values of the control law variables that minimize a basic performance index while satisfying several inequality constraints that describe the design criteria. The method is applied to gust load alleviation of a drone aircraft.

Newsom, J. R.↗

NASA NTRS1981

Some experiences with active control of aeroelastic response

Flight and wind tunnel tests were conducted and multidiscipline computer programs were developed as part of investigations of active control technology conducted at the NASA Langley Research Center. Unsteady aerodynamics approximation, optimal control theory, optimal controller design, and the Delta wing and DC-10 models are described. The drones for aerodynamics and structural testing (DAST program) for evaluating procedures for aerodynamic loads prediction and the design of active control systems on wings with significant aeroelastic effects is described as well as the DAST model used in the wind tunnel tests.

Newsom, J. R.↗

NASA NTRS1981

Flight test results of an active flutter suppression system installed on a remotely piloted research vehicle

Flight flutter test results of the first aeroelastic research wing of NASA's Drones for Aerodynamic and Structural Testing (DAST) program are presented. The implementation of the flutter suppression system and the flight test operation are described. The conduct of the flutter testing and the near-real time damping estimation algorithm are also described in detail. Flight data was obtained at Mach numbers up to 0.91 and was of high quality. Response to fast frequency sweep excitation provided reliable damping estimates and the open-loop flutter boundary was well defined. Evidence of angle-of-attack effects upon damping at high transonic Mach numbers is also presented. While the flutter suppression system provided augmented damping at speeds below the flutter boundary, an error in the implementation of the system gain caused the system to be less stable than predicted and the vehicle encountered system-on flutter on the third flight.

Edwards, J. W.↗