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DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Longitudinal Phase Space Tomography for the Booster Synchrotron

Efforts in the study of the longitudinal behavior of charged particles in the Fermilab Booster can be catalyzed with an image of the two-dimensional phase space distribution. In the past, tomography has been extensively employed in the reconstruction of the phase space in accelerators such as the Recycler at Fermilab and the Proton Synchrotron Booster at CERN. However, such a capability had yet to realize for the Fermilab Booster synchrotron. In this work, the first successful tomographic phase space reconstruction of a low-energy Booster bunch is presented along with validation metrics. A numerical turn-by-turn model of the longitudinal particle dynamics in the Booster has been implemented, which utilizes a fast, map-based particle transport algorithm. Using a sinogram generated from the Wall Current Monitor, the iterative reconstruction algorithm recovers a discretized image of the original phase space distribution at variable resolution. The reconstruction result shows low root-mean-square error and a rapid convergence toward the solution, providing strong evidence of accuracy. Future and ongoing work includes modeling high-energy bunches above transition and using tomography to infer certain machine parameters such as synchronous phase, peak gap voltage, and synchronous energy in addition to the phase space distribution.

Ebeid, Safi [Unlisted]↗

DOE OSTI2026

Longitudinal Phase Space Tomography for the Booster Synchrotron (Abstract Only)

Ebeid, Safi [Unlisted, US]↗

DOE OSTI2014

Comparison of the Accuracy and Speed of Transient Mobile A/C System Simulation Models: Preprint

The operation of air conditioning (A/C) systems is a significant contributor to the total amount of fuel used by light- and heavy-duty vehicles. Therefore, continued improvement of the efficiency of these mobile A/C systems is important. Numerical simulation has been used to reduce the system development time and to improve the electronic controls, but numerical models that include highly detailed physics run slower than desired for carrying out vehicle-focused drive cycle-based system optimization. Therefore, faster models are needed even if some accuracy is sacrificed. In this study, a validated model with highly detailed physics, the 'Fully-Detailed' model, and two models with different levels of simplification, the 'Quasi-Transient' and the 'Mapped- Component' models, are compared. The Quasi-Transient model applies some simplifications compared to the Fully-Detailed model to allow faster model execution speeds. The Mapped-Component model is similar to the Quasi-Transient model except instead of detailed flow and heat transfer calculations in the heat exchangers, it uses lookup tables created with the Quasi-Transient model. All three models are set up to represent the same physical A/C system and the same electronic controls. Speed and results of the three model versions are compared for steady state and transient operation. Steady state simulated data are also compared to measured data. The results show that the Quasi-Transient and Mapped-Component models ran much faster than the Fully-Detailed model, on the order of 10- and 100-fold, respectively. They also adequately approach the results of the Fully-Detailed model for steady-state operation, and for drive cycle-based efficiency predictions

02 PETROLEUM↗

DOE OSTI2016

Evaluation of regional isoprene emission factors and modeled fluxes in California

Accurately modeled biogenic volatile organic compound (BVOC) emissions are a vital input to atmospheric chemistry simulations of ozone and particle formation. BVOC emission models rely on basal emission factor (BEF) distribution maps based on emission measurements and vegetation land-cover data but these critical input components of the models as well as model simulations lack validation by regional scale measurements. We directly assess isoprene emission-factor distribution databases for BVOC emission models by deriving BEFs from direct airborne eddy covariance (AEC) fluxes (Misztal et al., 2014) scaled to the surface and normalized by the activity factor of the Guenther et al. (2006) algorithm. The available airborne BEF data from approx. 10 000 km of flight tracks over California were averaged spatially over 48 defined ecological zones called ecoregions. Consistently, BEFs used by three different emission models were averaged over the same ecoregions for quantitative evaluation. Ecoregion-averaged BEFs from the most current land cover used by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v.2.1 resulted in the best agreement among the tested land covers and agreed within 10 % with BEFs inferred from measurement. However, the correlation was sensitive to a few discrepancies (either overestimation or underestimation) in those ecoregions where land-cover BEFs are less accurate or less representative for the flight track. The two other land covers demonstrated similar agreement (within 30 % of measurements) for total average BEF across all tested ecoregions but there were a larger number of specific ecoregions that had poor agreement with the observations. Independently, we performed evaluation of the new California Air Resources Board (CARB) hybrid model by directly comparing its simulated isoprene area emissions averaged for the same flight times and flux footprints as actual measured area emissions. The model simulation and the observed surface area emissions agreed on average within 20 %. We demonstrate that the choice of model land-cover input data has the most critical influence on model-measurement agreement and the uncertainty in meteorology inputs has a lesser impact at scales relevant to regional air quality modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1977

A moving window parameter adaptive control system for the F8-DFBW aircraft

This paper describes the moving window parameter adaptive control system developed for the NASA F8-DFBW aircraft. The control system employs a parameter identification process that, iteratively, adjusts parameters of a model of the aircraft motions in a batch-processing manner so that responses generated from the model fit the outputs of sensors stored in a finite record referred to as the moving window. Tests are made on the validity of the parameter estimates before using the parameters in an on-line design process. The on-line design process is an algebraic mapping of the parameters of the model into primary control system feedback and feedforward gains. The mapping was selected to satisfy specific flying quality characteristics over the range of parameter variations expected. Results are presented from simulation studies on the identification algorithm made during the development of the system.

Dunn, H. J.↗

NASA NTRS1988

Effects of joints in truss structures

The response of truss-type structures for future space applications, such as Large Deployable Reflector (LDR), will be directly affected by joint performance. Some of the objectives of research at BAC were to characterize structural joints, establish analytical approaches that incorporate joint characteristics, and experimentally establish the validity of the analytical approaches. The test approach to characterize joints for both erectable and deployable-type structures was based upon a Force State Mapping Technique. The approach pictorially shows how the nonlinear joint results can be used for equivalent linear analysis. Testing of the Space Station joints developed at LaRC (a hinged joint at 2 Hz and a clevis joint at 2 Hz) successfully revealed the nonlinear characteristics of the joints. The Space Station joints were effectively linear when loaded to plus or minus 500 pounds with a corresponding displacement of about plus or minus 0.0015 inch. It was indicated that good linear joints exist which are compatible with errected structures, but that difficulty may be encountered if nonlinear-type joints are incorporated in the structure.

Ikegami, R.↗

NASA NTRS2005

Coherent Anti-Stokes Raman Spectroscopy (CARS) Measurements in Supersonic Combustors at NASA Langley Research Center

This paper describes the recent use of coherent anti-Stokes Raman spectroscopy (CARS) to study supersonic combustion at NASA Langley Research Center. CARS is a nonlinear optical measurement technique used to measure temperature and species mole fractions remotely in harsh environments. A CARS system has been applied to two different combustor geometries at NASA Langley. Both experiments used the same vitiated wind-tunnel facility to create an air flow that simulates flight at Mach numbers of 6 and 7 for the combustor inlet and both experiments used hydrogen fuel. In the first experiment, the hydrogen was injected supersonically at a 30-degree angle with respect to the incoming flow. In the second experiment, the hydrogen was injected sonically at normal incidence. While these injection schemes produced significantly different flow features, the CARS method provided mean temperature, N2, O2 and H2 maps at multiple downstream locations for both. The primary aim of these measurements was to provide detailed flowfield information for computational fluid dynamics (CFD) code validation.

Danehy, Paul M.↗

NASA NTRS2014

Analysis and Prediction of Weather Impacted Ground Stop Operations

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Analysis↗

NASA NTRSDate not supplied

Towards A National-Scale Automated Landslide Mapping System for Nepal

The mountains of Nepal are among the most hazardous environments in the world, with frequent landslides causing loss of lives and substantial damage to infrastructure every year. Landslide mapping is vital for characterizing impacts in the days after extreme triggering events, as well as for advancing landslide hazard models through robust calibration and validation. Conventionally, landslide inventories are produced by field surveys and/or manual interpretation of aerial photos and satellite images. This process is very subjective and time consuming.

Pukar Amatya↗

DOE OSTI2014

Structural Analysis of Novel Lignin-derived Carbon Composite Anodes

The development of novel lignin-based carbon composite anodes consisting of nanocrystalline and amorphous domains motivates the understanding of a relationship of the structural properties characterizing these materials, such as crystallite size, intracrystallite dspacing, crystalline volume fraction and composite density, with their pair distribution functions (PDF), obtained from both molecular dynamics simulation and neutron scattering. A model for these composite materials is developed as a function of experimentally measurable parameters and realized in fifteen composite systems, three of which directly match all parameters of their experimental counterparts. The accurate reproduction of the experimental PDFs using the model systems validates the model. The decomposition of the simulated PDFs provides an understanding of each feature in the PDF and allows for the development of a mapping between the defining characteristics of the PDF and the material properties of interest.

McNutt, Nicholas W↗

DOE OSTI2026

Longitudinal Phase Space Tomography for the Booster Synchrotron

Efforts in the study of the longitudinal behavior of charged particles in the Fermilab Booster can be catalyzed with an image of the two-dimensional phase space distribution. In the past, tomography had been employed in the reconstruction of the phase space in accelerators such as the Recycler at Fermilab and the Proton Synchrotron Booster at CERN. However, such a capability had yet to realize for the Fermilab Booster synchrotron. In this work, the first successful tomographic phase space reconstruction of a low-energy Booster bunch is presented along with validation metrics. A numerical turn-by-turn model of the longitudinal particle dynamics in the Booster has been implemented, which utilizes a fast, map-based particle transport algorithm. Using a sinogram generated from the Wall Current Monitor signal, the iterative reconstruction algorithm recovers a discretized image of the original phase space distribution at variable resolution. The reconstruction result shows low root-mean-square error and a rapid convergence toward the solution, providing strong evidence of accuracy. Future and ongoing work includes modeling high-energy bunches above transition and using tomography to infer certain machine parameters such as synchronous phase, peak gap voltage, and synchronous energy in addition to the phase space distribution.

Ebeid, Safi [Unlisted; Fermilab]↗

DOE OSTI2016

Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods

Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month. These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Validation of 2D Te and ne measurements made with Helium imaging spectroscopy in the volume of the TCV divertor

Abstract Multi-spectral imaging of helium atomic emission (HeMSI) has been used to create 2D poloidal maps of T e and n e in TCV’s divertor. To achieve these measurements, TCV’s MANTIS multispectral cameras (Perek et al 2019 Rev. Sci. Instrum. 90 123514) simultaneously imaged four He I lines (two singlet and two triplet) and a He II line (468 nm) from passively present He and He + . The images, which were absolutely calibrated and covered the whole divertor region, were inverted through the assumption of toroidal symmetry to create emissivity profiles and, consequently, line-ratio profiles. A collisional-radiative model (CRM) was applied to the line-ratio profiles to produce 2D poloidal maps of T e and n e . The collisional-radiative modeling was accomplished with the Goto helium CRM code (Zholobenko et al 2018 Nucl. Fusion 58 126006, Zholobenko et al 2018 Technical Report , Goto 2003 J. Quant. Spectrosc. Radiat. Transfer 76 331–44) which accounts for electron-impact excitation (EIE) and deexcitation, and electron–ion recombination (EIR) with He + . The HeMSI T e and n e measurements were compared with co-local Thomson scattering measurements. The two sets of measurements exhibited good agreement for ionizing plasmas: ( 5 eV ⩽ T e ⩽ 60 eV , and 2 × 10 18 m − 3 ⩽ n e ⩽ 3 × 10 19 m − 3 ) in the case of majority helium plasmas, and ( 10 eV ⩽ T e ⩽ 40 eV , 2 × 10 18 m − 3 ⩽ n e ⩽ 3 × 10 19 m − 3 ) in the case of majority deuterium plasmas. However, there were instances where HeMSI measurements diverged from Thomson scattering. When T e ⩽ 10 eV in majority deuterium plasmas, HeMSI deduced inaccurately high values of T e . This disagreement cannot be rectified within the CRM’s EIE and EIR framework. Second, on sporadic occasions within the private flux region, HeMSI produced erroneously high measurements of n e . Multi-spectral imaging of Helium emission has been demonstrated to produce accurate 2D poloidal maps of T e and n e within the divertor of a tokamak for plasma conditions relevant to contemporary divertor studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1992

Airborne lidar mapping of vertical ozone distributions in support of the 1990 Clean Air Act Amendments

The 1990 Clean Air Act Amendments mandated attainment of the ozone standard established by the U.S. Environmental Protection Agency. Improved photochemical models validated by experimental data are needed to develop strategies for reducing near surface ozone concentrations downwind of urban and industrial centers. For more than 10 years, lidar has been used on large aircraft to provide unique information on ozone distributions in the atmosphere. However, compact airborne lidar systems are needed for operation on small aircraft of the type typically used on regional air quality investigations to collect data with which to develop and validate air quality models. Data presented in this paper will consist of a comparison between airborne differential absorption lidar (DIAL) and airborne in-situ ozone measurements. Also discussed are future plans to improve the airborne ultraviolet-DIAL for ozone and other gas observations and addition of a Fourier Transform Infrared (FTIR) emission spectrometer to investigate the effects of other gas species on vertical ozone distribution.

Uthe, Edward E.↗

NASA NTRS2021

Very High-Resolution Satellite-Derived Bathymetry and Habitat Mapping Using Pleiades-1 and ICESat-2

Accurate and reliable bathymetric data are needed for a wide diversity of marine research and management applications. Satellite-derived bathymetry represents a time saving method to map large shallow waters of remote regions compared to the current costly in situ measurement techniques. This study aims to create very high-resolution (VHR) bathymetry and habitat mapping in Mayotte island waters (Indian Ocean) by fusing 0.5 m Pleiades-1 passive multispectral imagery and active ICESat-2 LiDAR bathymetry. ICESat-2 georeferenced photons were filtered to remove noise and corrected for water column refraction. The bathymetric point clouds were validated using the French naval hydrographic and oceanographic service Litto3D® dataset and then used to calibrate the multispectral image to produce a digital depth model (DDM). The latter enabled the creation of a digital albedo model used to classify benthic habitats. ICESat-2 provided bathymetry down to 15 m depth with a vertical accuracy of bathymetry estimates reaching 0.89 m. The benthic habitats map produced using the maximum likelihood supervised classification provided an overall accuracy of 96.62%. This study successfully produced a VHR DDM solely from satellite data. Digital models of higher accuracy were further discussed in the light of the recent and near-future launch of higher spectral and spatial resolution satellites.

Bathymetry↗

DOE OSTI2017

Lower-tropospheric CO 2 from near-infrared ACOS-GOSAT observations

We present two new products from near-infrared Greenhouse Gases Observing Satellite (GOSAT) observations: lowermost tropospheric (LMT, from 0 to 2.5 km) and upper tropospheric–stratospheric ( U , above 2.5 km) carbon dioxide partial column mixing ratios. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial column mixing ratios significantly improve upon the Atmospheric CO 2 Observations from Space (ACOS) and GOSAT (ACOS-GOSAT) initial guess and/or a priori, with distinct patterns in the LMT and U seasonal cycles that match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U , and X CO 2 ; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U , and X CO 2 . In the southern hemispheric biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and a CO–CO 2 emission factor comparable to published values. The difference of LMT and U , useful for evaluation of model transport error, has also been validated with a monthly average error of 0.8 (1.4) ppm for ocean (land). LMT is more locally influenced than U , meaning that local fluxes can now be better separated from CO 2 transported from far away.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Determination of fluorine distribution in shark teeth by laser-induced breakdown spectroscopy

Quantifying the chemical composition of fast-growing hard tissues in the environment can shed valuable information in terms of understanding ecosystems both prehistoric and current. Changes in chemical composition can be correlated with environmental conditions and can provide information about the organism's life. Sharks can lose 0.1 to 1.1 teeth/day, depending on species, which offers a unique opportunity to record environmental changes over a short duration of time. Shark teeth contain a biomineral phase that is made up of fluorapatite [Ca 5 (PO 4 ) 3 F], and the F distribution within the tooth can be correlated to tooth hardness. Typically, this is determined by bulk acid digestion, energy-dispersive X-ray spectroscopy (EDS), or wavelength-dispersive spectroscopy. Here we present laser-induced breakdown spectroscopy (LIBS) as an alternative and faster approach for determining F distribution within shark teeth. Using a two-volume laser ablation chamber (TwoVol3) with innovative embedded collection optics for LIBS, shark teeth were investigated from sand tiger (Carcharias Taurus), tiger (Galeocerdo Cuvier), and hammerhead sharks (Sphyrnidae). Fluorine distribution was mapped using the CaF 603 nm band (CaF, Β 2 Σ + → X 2 Σ + ) and quantified using apatite reference materials. In addition, F measurements were cross referenced with EDS analyses to validate the findings. Distributions of F (603 nm), Na (589 nm), and H (656 nm) within the tooth correlate well with the expected biomineral composition and expected tooth hardness. This rapid methodology could transform the current means of determining F distribution, particularly when large sample specimens (350 mm 2 , presented here) and large quantities of specimens are of interest.

36 MATERIALS SCIENCE↗