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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Numerical studies of collinear laser-assisted injection from a foil for plasma wakefield accelerators

We present a laser-assisted electron injection scheme for beam-driven plasma wakefield acceleration. The laser is collinear with the driver and triggers the injection of hot electrons into the plasma wake by interaction with a thin solid target. We present a baseline case using the AWAKE Run 2 parameters and then perform variations on key parameters to explore the scheme. It is found that the trapped witness electron charge may be tuned by altering laser parameters, with a strong dependence on the phase of the wake upon injection. Normalized emittance settles at the order of micrometres and varies with witness charge. The scheme is robust to misalignment, with a 1/10th plasma skin-depth offset ( 20 μ m for the AWAKE case) having a negligible effect on the final beam. The final beam quality is better than similar existing schemes, and several avenues for further optimization are indicated. The constraints on the AWAKE experiment are very specific, but the general principles of this mechanism can be applied to future beam-driven plasma wakefield accelerator experiments. Published by the American Physical Society 2024

Physics↗

Conflict Detection in Open RAN with Recurrent Neural Networks Using Geometric Manifolds

Allowing third-party applications on Radio Access Network (RAN) Intelligent Controllers (RICs) within the OpenRAN (O-RAN) framework introduces conflicting interactions that are often difficult to detect in advance. These conflicts, occurring between third-party applications in the Near RealTime RIC (Near-RT RIC), known as xApps, can lead to performance degradation and instability in O-RAN if not identified early. Existing conflict detection and mitigation solutions in the literature assume that the conflicts are known beforehand, which is not always accurate due to the complex and often hidden relationships between control parameters and Key Performance Indicators (KPIs). In this paper, we propose a novel Recurrent Neural Network (RNN) to detect both known and unknown conflicts in O-RAN xApps as specified in the O-RAN standards. We model the xApps, control parameters, and KPIs with nodes and edges to create graph structures and use the hidden nonEuclidean geometric properties of the Riemannian manifold to train the RNN model. The performance of this proposed model is validated using evaluation metrics and compared with benchmarks. Results demonstrate that the proposed RNN model, leveraging Riemannian geometric properties, can achieve 100% of the F1-score provided by an optimal solution in just 20 iterations.

5G↗

Conflict Detection in Open RAN with Recurrent Neural Networks Using Geometric Manifolds

Allowing third-party applications on Radio Access Network (RAN) Intelligent Controllers (RICs) within the OpenRAN (O-RAN) framework introduces conflicting interactions that are often difficult to detect in advance. These conflicts, occurring between third-party applications in the Near RealTime RIC (Near-RT RIC), known as xApps, can lead to performance degradation and instability in O-RAN if not identified early. Existing conflict detection and mitigation solutions in the literature assume that the conflicts are known beforehand, which is not always accurate due to the complex and often hidden relationships between control parameters and Key Performance Indicators (KPIs). In this paper, we propose a novel Recurrent Neural Network (RNN) to detect both known and unknown conflicts in O-RAN xApps as specified in the O-RAN standards. We model the xApps, control parameters, and KPIs with nodes and edges to create graph structures and use the hidden nonEuclidean geometric properties of the Riemannian manifold to train the RNN model. The performance of this proposed model is validated using evaluation metrics and compared with benchmarks. Results demonstrate that the proposed RNN model, leveraging Riemannian geometric properties, can achieve 100% of the F1-score provided by an optimal solution in just 20 iterations.

5G↗

The CCD/Transit Instrument (CTI) data-analysis system

The automated software system for archiving, analyzing, and interrogating data from the CCD/Transit Instrument (CTI) is described. The CTI collects up to 450 Mbytes of image-data each clear night in the form of a narrow strip of sky observed in two colors. The large data-volumes and the scientific aims of the project make it imperative that the data are analyzed within the 24-hour period following the observations. To this end a fully automatic and self evaluating software system has been developed. The data are collected from the telescope in real-time and then transported to Tucson for analysis. Verification is performed by visual inspection of random subsets of the data and obvious cosmic rays are detected and removed before permanent archival is made to the optical disc. The analysis phase is performed by a pair of linked algorithms, one operating on the absolute pixel-values and the other on the spatial derivative of the data. In this way both isolated and merged images are reliably detected in a single pass. In order to isolate the latter algorithm from the effects of noise spikes a 3x3 Hanning filter is applied to the raw data before the analysis is run. The algorithms reduce the input pixel-data to a database of measured parameters for each image which has been found. A contrast filter is applied in order to assign a detection-probability to each image and then x-y calibration and intensity calibration are performed using known reference stars in the strip. These are added to as necessary by secondary standards boot-strapped from the CTI data itself. The final stages involve merging the new data into the CTI Master-list and History-list and the automatic comparison of each new detection with a set of pre-defined templates in parameter-space to find interesting objects such as supernovae, quasars and variable stars. Each stage of the processing from verification to interesting image selection is performed under a data-logging system which both controls the pipe-lining of data through the system and records key performance monitor parameters which are built into the software. Furthermore, the data from each stage are stored in databases to facilitate evaluation, and all stages offer the facility to enter keyword-indexed free-format text into the data-logging system. In this way a large measure of certification is built into the system to provide the necessary confidence in the end results.

Cawson, M. G. M.↗

Ball Bearing Analysis with the ORBIS Tool

Ball bearing design is critical to the success of aerospace mechanisms. Key bearing performance parameters, such as load capability, stiffness, torque, and life all depend on accurate determination of the internal load distribution. Hence, a good analytical bearing tool that provides both comprehensive capabilities and reliable results becomes a significant asset to the engineer. This paper introduces the ORBIS bearing tool. A discussion of key modeling assumptions and a technical overview is provided. Numerous validation studies and case studies using the ORBIS tool are presented. All results suggest the ORBIS code closely correlates to predictions on bearing internal load distributions, stiffness, deflection and stresses.

Halpin, Jacob D.↗

Effect of Landsat Thematic Mapper sensor parameters on land cover classification

Selected sensor parameter differences between TM and MSS were assessed through classification performance of a suburban/regional test site. Overall classification accuracy of a seven-band Landsat TM scene in comparison to MSS yielded an improvement in accuracy from 74.8 percent to 83.2 percent. To study the possible causes for the difference in classification performance, key sensor parameter differences between MSS and TM, including: (1) spatial resolution (30 m for TM versus 80 m for MSS), (2) quantization level (256 levels for TM versus 64 for MSS), and (3) spectral regions (seven bands in four major spectral regions for TM versus four bands in two regions for MSS), were evaluated. Landsat TM data were processed to stimulate all possible combinations of these MSS and TM parameters, yielding a three-factor design with two levels per factor. The results indicated that the added spectral regions (TM 1, TM 5, and TM 7) and to a lesser degree the increase in quantization level to eight bits produced the improved TM classification accuracy. However, in this study, the higher 30 m spatial resolution of TM contributed to a reduced classification accuracy from increased within-field variability or class heterogeneity.

Toll, D. L.↗

Comparative Study for Pressure Gain Combustion-Gas Turbine System Performance in NGCC Configurations

The Department of Energy (DOE) has a goal to increase natural gas combined cycle (NGCC) plant efficiency to greater than 70 percent on a lower heating value (LHV) basis. Improvement in gas turbine (GT) efficiency is key achieving this goal. While many of the traditional improvement methods (higher firing temperature, advanced materials, improved cooling methods, etc.) may increase current GT and NGCC efficiencies incrementally, combining these traditional advancements with breakthrough technologies such as pressure gain combustion (PGC) may provide significant system efficiency gains. PGC is a combustion process that results in a net pressure increase across the combustor (up to pressure ratio of 2.2) rather than the traditional (<5%) pressure drop. There are multiple PGC technologies being developed that create the pressure rise phenomena, including resonant pulse combustors (RPCs), pulse detonation engines (PDEs), wave rotor combustor (WRC) engines and rotating detonation engines (RDEs). In this study, scoping analyses of PGC concepts applied to NGCC power plants were performed by combining simplified analytical models for the RPC, PDE, WRC, and RDE types of pressure gain processes with a GT model to evaluate impacts of using each of the PGC technologies on key GT performance parameters. Sensitivity analyses were also performed. Ultimately, the PGC technologies were found to have the potential to increase simple cycle efficiency by 4–6 percent (absolute) and NGCC efficiency by 2–3 percent (absolute) based on the results of the current study.

03 NATURAL GAS↗

Simple Heat Transfer Model for Film Cooling Applications

This report describes the development of a simple engineering model for film cooling. This model is used to derive a relationship between local wall temperature variations and key cooling performance parameters like local heat transfer coefficients and film effectiveness. This relation and method new and different from previously published models. The scope of this report includes the derivation of regression model equations for a flat plate with and without film cooling. The model equation for a flat plate without film cooling can be used to estimate local heat transfer coefficients using surface temperatures measured from infrared thermography. The model equation for the flat plate with film cooling can be used to estimate film cooling effectiveness, $η_f$, and heat transfer augmentation from the film cooling jet(s).

42 ENGINEERING↗

Abstract for CRADA between NETL and Rivalia Chemical Co

The National Energy Technology Laboratory (NETL) will assist Rivalia Chemical Co (Participant) with system analyses to aid the Participant with setting priorities and securing funding. The Participant is an early-stage startup pioneering new chemical extraction technology to solve two important problems: critical mineral scarcity and coal ash waste management. The U.S. generates coal fly ash from coal combustion for power generation and has amassed over two billion metric tons of ash, which contains valuable rare earth elements. The ash is often stored in unlined ponds and frequently contaminates the local environment. The Participant’s patent-pending process harvests rare earths from ash, then transforms the residual ash for use in green concrete, providing an economic pathway for utilities to empty and remediate the ash ponds. Founder Laura Stoy created the company in July 2022 after developing the core intellectual property during her Ph.D. at the Georgia Institute of Technology. Stoy is currently participating in the Chain Reactions Innovations (CRI) program at the U.S. Department of Energy (DOE) Argonne National Laboratory (ANL) where she will be optimizing the core technology and scaling from bench scale to demonstration scale. The technology has been validated at bench scale (TRL3); the goal is to approach TRL5 by the conclusion of the CRI program and prepare to raise capital investment for a pilot facility. NETL and the Participant will develop an updated technoeconomic analysis (TEA) and identify key sustainability performance parameters to inform ’s research and development priorities and de-risk the technology. NETL will also provide the Participant with guidance to prepare a more detailed life cycle assessment (LCA), and a narrative on the Participant’s product markets. These tools will aid the Participant with the next steps of commercialization.

01 COAL, LIGNITE, AND PEAT↗

Preliminary measurements of very low dark currents in MLA/SWIR HgCdTe/DRO arrays

In infrared astronomy observations, one of the key detector performance parameters is the dark current which, together with the optics, establishes the fundamental limit of a space-based instrument. This technical note summarizes an effort to measure dark current performance of the MLA/Short Wave Infrared photovoltaic HgCdTe array (2.5 micron cutoff) at temperatures from 65 to 120 K. The preliminary results indicate that dark current decreased systematically to 100 K, then the value became measurement-limited at about 3.0 E-18 A/pixel, or 19 electrons/sec/pixel.

Yang, B. T.↗

Progress in Validation of Wind-US for Ramjet/Scramjet Combustion

Validation of the Wind-US flow solver against two sets of experimental data involving high-speed combustion is attempted. First, the well-known Burrows- Kurkov supersonic hydrogen-air combustion test case is simulated, and the sensitively of ignition location and combustion performance to key parameters is explored. Second, a numerical model is developed for simulation of an X-43B candidate, full-scale, JP-7-fueled, internal flowpath operating in ramjet mode. Numerical results using an ethylene-air chemical kinetics model are directly compared against previously existing pressure-distribution data along the entire flowpath, obtained in direct-connect testing conducted at NASA Langley Research Center. Comparison to derived quantities such as burn efficiency and thermal throat location are also made. Reasonable to excellent agreement with experimental data is demonstrated for key parameters in both simulation efforts. Additional Wind-US feature needed to improve simulation efforts are described herein, including maintaining stagnation conditions at inflow boundaries for multi-species flow. An open issue regarding the sensitivity of isolator unstart to key model parameters is briefly discussed.

Engblom, William A.↗

On-Orbit Noise Characterization for MODIS Reflective Solar Bands

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) has operated successfully on-board the NASA Earth Observing System (EOS) Terra and EOS Aqua spacecraft. MODIS is a passive cross-track scanning radiometer that makes observations in 36 spectral bands with spectral wavelengths from visible (VIS) to long-wave infrared. MODIS bands 1-19 and 26 are the reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers. They are calibrated on-orbit using an on-board solar diffuser (SD) and a SD stability monitor (SDSM) system. For MODIS RSB, the level 1B calibration algorithm produces top of the atmosphere reflectance factors and radiances for every pixel of the Earth view. The sensor radiometric calibration accuracy, specified at each spectral band's typical scene radiance, is 2% for the RSB reflectance factors and 5% for the RSB radiances. Also specified at the typical scene radiance is the detector signal-to-noise ratio (SNR), a key sensor performance parameter that directly impacts its radiometric calibration accuracy and stability, as well as the image quality. This paper describes an on-orbit SNR characterization approach developed to evaluate and track MODIS RSB detector performance. In order to perform on-orbit SNR characterization, MODIS RSB detector responses to the solar illumination reflected from the SD panel must be corrected for factors due to variations of the solar angles and the SD bi-directional reflectance factor. This approach enables RSB SNR characterization to be performed at different response levels for each detector. On-orbit results show that both Terra and Aqua MODIS RSB detectors have performed well since launch. Except for a few noisy or inoperable detectors which were identified pre-launch, most RSB detectors continue to meet the SNR design requirements and are able to maintain satisfactory short-term stability. A comparison of on-orbit noise characterization results with results derived from pre-launch calibration and characterization are also provided.

Xiong, X.↗

The Hydrosphere State (Hydros) Satellite Mission: An Earth System Pathfinder for Global Mapping of Soil Moisture and Land Freeze/Thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earth's soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39 with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.

Entekhabi, D.↗

Deep Space Network Antenna Logic Controller

The Antenna Logic Controller (ALC) software controls and monitors the motion control equipment of the 4,000-metric-ton structure of the Deep Space Network 70-meter antenna. This program coordinates the control of 42 hydraulic pumps, while monitoring several interlocks for personnel and equipment safety. Remote operation of the ALC runs via the Antenna Monitor & Control (AMC) computer, which orchestrates the tracking functions of the entire antenna. This software provides a graphical user interface for local control, monitoring, and identification of faults as well as, at a high level, providing for the digital control of the axis brakes so that the servo of the AMC may control the motion of the antenna. Specific functions of the ALC also include routines for startup in cold weather, controlled shutdown for both normal and fault situations, and pump switching on failure. The increased monitoring, the ability to trend key performance characteristics, the improved fault detection and recovery, the centralization of all control at a single panel, and the simplification of the user interface have all reduced the required workforce to run 70-meter antennas. The ALC also increases the antenna availability by reducing the time required to start up the antenna, to diagnose faults, and by providing additional insight into the performance of key parameters that aid in preventive maintenance to avoid key element failure. The ALC User Display (AUD) is a graphical user interface with hierarchical display structure, which provides high-level status information to the operation of the ALC, as well as detailed information for virtually all aspects of the ALC via drill-down displays. The operational status of an item, be it a function or assembly, is shown in the higher-level display. By pressing the item on the display screen, a new screen opens to show more detail of the function/assembly. Navigation tools and the map button allow immediate access to all screens.

Ahlstrom, Harlow↗

MODIS On-orbit Calibration Uncertainty Assessment

MODIS has 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, MODIS was developed with very stringent calibration uncertainty requirements. As a result, MODIS was designed and built with a set of on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated. In terms of its calibration traceability, MODIS RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of MODIS calibration methodologies and an in-depth analysis of its on-orbit calibration uncertainties. Also discussed in this paper are uncertainty contributions from individual components and differences due to Terra and Aqua MODIS instrument characteristics and on-orbit performance.

Chiang, Vincent↗

MODIS Radiometric Calibration and Uncertainty Assessment

Since launch, Terra and Aqua MODIS have collected more than II and 9 years of datasets for comprehensive studies of the Earth's land, ocean, and atmospheric properties. MODIS observations are made in 36 spectral bands: 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB). Compared to its heritage sensors, MODIS was developed with very stringent calibration and uncertainty requirements. As a result, MODIS was designed and built with a set of state of the art on-board calibrators (OBC), which allow key sensor performance parameters and on-orbit calibration coefficients to be monitored and updated if necessary. In terms of its calibration traceability, MODIS RSB calibration is reflectance based using an on-board solar diffuser (SD) and the TEB calibration is radiance based using an on-board blackbody (BB). In addition to on-orbit calibration coefficients derived from its OBC, calibration parameters determined from sensor pre-launch calibration and characterization are used in both the RSB and TEB calibration and retrieval algorithms. This paper provides a brief description of MODIS calibration methodologies and discusses details of its on-orbit calibration uncertainties. It assesses uncertainty contributions from individual components and differences between Terra and Aqua MODIS due to their design characteristics and on-orbit periormance. Also discussed in this paper is the use of MODIS LIB uncertainty index CUI) product.

Xiong, Xiaoxiong↗

Sixteen Years of Terra MODIS On-Orbit Operation, Calibration, and Performance

Terra MODIS has successfully operated for more than 16 years since its launch in December 1999. From its observations, many science data products have been generated in support of a broad range of research activities and remote sensing applications. Terra MODIS has operated in a number of configurations and experienced a few anomalies, including spacecraft and instrument related events. MODIS collects data in 36 spectral bands that are calibrated regularly by a set of on-board calibrators for their radiometric, spectral, and spatial performance. Periodic lunar observations and long-term radiometric trending over well-characterized ground targets are also used to support sensor on-orbit calibration. Dedicated efforts made by the MODIS Characterization Support Team (MCST) and continuing support from the MODIS Science Team have contributed to the mission success, enabling well-calibrated data products to be continuously generated and routinely delivered to users worldwide. This paper presents an overview of Terra MODIS mission operations, calibration activities, and instrument performance of the past 16 years. It illustrates and describes the results of key sensor performance parameters derived from on-orbit calibration and characterization, such as signal-to-noise ratio (SNR), noise equivalent temperature difference (NEdT), solar diffuser (SD) degradation, changes in sensor responses, center wavelengths, and band-to-band registration (BBR). Also discussed in this paper are the calibration approaches and strategies developed and implemented in support of MODIS Level 1B data production and re-processing, major challenging issues, and lessons learned. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Xiong, X.↗

Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and Wind

Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.

uncertainty↗