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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Feasibility Study of an All-Electric 150 Passenger Aircraft

Among the potential future technologies for low-carbon transport aircraft, all-electric concepts stand out environmentally, yet their feasibility and cost-effectiveness at scale remain uncertain. This paper examines the conceptual design of an all-electric 150-passenger aircraft with a range of 840 NM based on assumed future battery cell-level specific energy of1620Wh/kg. The tube and wing design is propelled by open rotors driven by four electric motors per nacelle and utilizes advanced structural materials for weight reduction. Powertrain technology gaps are identified. The conceptual design shows that all-electric aviation could supplant about 30% of current fossil fuel use by transport aircraft and potentially more with air-traffic-control modifications.

electric aircraft↗
NASA NTRS2024

Simulated Feasibility of 3D Lightning Mapping from Space

In addition to the awe it inspires, lightning can illuminate the microphysical processes hidden away within deep convection. The current generation of space-based lightning mapping uses mostly 2D optical imaging to connect overall flash characteristics to their parent storm dynamics, but are missing a dimension’s worth of information. With lightning now classified as an essential climate variable, future spaceborne mappers will need improved capabilities to take advantage of the 3D structure of lightning flashes to support meteorological and climate modeling. We report here on a study of the feasibility of implementing a radio frequency (RF)–based network of satellites for 3D lightning mapping in high resolution from low Earth orbit (LEO). Lightning sources are simulated using existing tools of the Lightning Mapping Array (LMA), modified for orbital detection, and spatially reconstructed using a Levenberg-Marquardt geolocation algorithm to assess sources of uncertainty in these solutions. We analyze the benefits and limitations of this approach compared to existing orbital and ground-based methods. Results of this study show that lightning can be mapped in 3D with a vertical location accuracy better than 2 km using as few as five satellites in LEO capable of measuring the time-of-arrival of impulsive RF signals in the very high frequency (VHF) band. The consequence of this study is that high-resolution, spaceborne 3D mapping of lightning is achievable across most of the globe, having crucial implications for our understanding of not only lightning, but also severe weather development, climate science, and more.

CubeSpark↗
NASA NTRSDate not supplied

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing↗
NASA NTRS2025

A Preliminary Study on the Feasibility of Large Language Models for Detecting Micro-Behaviors Among Team Members in Space Missions

Large-language models (LLMs) have been recently used for spoken language understanding (SLU) to infer meaning and semantics from speech in tasks such as speaker intent and sentiment classification. Due to being trained on large amounts of data, and their ability to understand context and relationships between words, LLMs are competent, enabling them to generalize across tasks without requiring many task-specific training samples. This research examines the feasibility of few-shot learning in LLMs for detecting subtle, brief, and possibly unconscious interactions between team members, called ``micro-behaviors," and provides insights into the appropriate design of LLMs for this task. Our data came from 5 teams participating in a 45-day mission at the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA). More specifically we used data collected from team interaction battery (TIB) tasks teams performed five times in-mission which comprise an average 1.5 hours of conversation data per day. Micro-behaviors were coded according to an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). We explore the ability of LLMs to detect the presence and intensity of micro-behaviors. We examine employing and fine-tuning readily available LLMs (i.e., RoBERTa, DistilBERT), as well as prompting state-of-the-art sequence classification models (i.e., Llama-2, Llama-3). In a total of 13,058 conversational turns (17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls), we compute the macro F1-score of the 3-way micro-behavior classification task (i.e., classifying among uplifting, discouraging, and neutral; 33% chance). Results indicate that the RoBERTa model achieves a F1-score of 36.2% (uplift: 43.3% precision (P), 15.1% recall (R); discourage: 20% P, 0.5% R). These results significantly improve when we augment the data via paraphrasing in the RoBERTa model, reaching a 41.2% macro F1-score (uplift: 37.7% P, 86.3% R; discourage: 3.5% P, 1.8% R). Finally, the Llama-2 model with 3-shot prompting yields 38% macro F1-score (uplift: 28.7% P, 20% R; discourage: 7.2% P, 18% R), which is slightly better compared to the RoBERTa model without data augmentation, highlighting the effectiveness of sequence classification models in detecting minority classes with a small sample size. Findings indicate that LLMs hold potential to detect subtle behaviors in conversations, which could be valuable in assessing team behavior in space exploration missions. Future studies will evaluate the performance of different LLM prompting strategies or fine-tuning methods.

Ankush Raut↗
NASA NTRSDate not supplied

Assessing the Feasibility of Using Various Earth Observations to Monitor Environmental Trends Associated with River Flow Impediments Near Energy Intake Structures

Grassing events, characterized by the release of river vegetation in large quantities, are often responsible for major flow impediments surrounding industrial water intake structures. These sudden flow impediments halt critical municipal functions, such as cooling at energy generating facilities, leading to widespread energy disruptions for surrounding communities. Because the origin and cause of grassing events in rivers are largely unknown, employees at these facilities can only reactively respond after they occur by pausing energy generation to manually remove the accumulation of aquatic vegetation. In 2023, the Dresden Generating Station, in collaboration with the United States Geological Survey, began looking into using remote sensing methodologies to locate floating aquatic vegetation surrounding their intake structure located along the Kankakee River in northern Illinois. This project contributed to this effort by conducting a case study that compared the performance, practicality, and feasibility of using various Earth observations (Landsat 9 OLI-2, Landsat 8 OLI, Sentinel-2 MSI, and DOVE PlanetScope) and vegetation indices (NDVI, EVI, SAVI, and GCI) to monitor aquatic vegetation in the Kankakee River. Additionally, this study incorporated several environmental metrics to identify potential triggers for grassing events. Results from this project found that while Landsat sensors provide a lower spatial resolution than commercial satellite Earth observations, areas of aquatic vegetation were similarly identified; therefore, it may not be necessary to acquire expensive, high-resolution datasets for continued monitoring. Finally, preliminary correlation analyses showed a potential negative relationship between the river discharge and the presence of aquatic vegetation (-0.875 correlation coefficient), suggesting that periods of low flow could lead to large releases in aquatic vegetation.

Marisa Smedsrud↗
DOE OSTI2020

Feasibility Study for a Proposed Subcritical Assembly at Oak Ridge National Laboratory

Nuclear Criticality Safety (NCS) staff use the guidelines in the ANSI/ANS-8.26 standard to establish and maintain their training and qualifications. Section 7.4 of the standard requires NCS staff to participate in hands-on experiments meant to “…demonstrate how varying the properties of a fissionable material system can affect neutron multiplication.” This training is performed to ensure NCS and operations staff are aware of the risks involved with conducting operations with fissionable materials outside reactors. A new, inherently safe, subcritical assembly, to be housed at Oak Ridge National Laboratory (ORNL) is being considered to augment the current training capabilities of the US Department of Energy/National Nuclear Security Administration (DOE/NNSA) Nuclear Criticality Safety Program (NCSP), which conducts hands-on subcritical and critical experiments to support the training and qualifications of NCS staff. This paper reports the results of a feasibility study performed by ORNL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Fast simultaneous feasibility testing and applications for electrical power grids

Fast simultaneous feasibility testing (SFT) for management of an electrical power grid is achieved through various innovations. The computation problem relates to evaluation of candidate solutions for external power flows into a power grid, with respect to predetermined constraints and contingencies. Storage and computations are reduced by formulating the problem in terms of transactional nodes (e.g. third party connections for generators and loads) instead of the larger number of bus nodes. Further advantages are achieved by precomputing matrices that can be reused across multiple SFT invocations, organizing matrices and operations to reduce storage and computation, and eliminating branches that have no contingency violations. The fast SFT further enables new applications for integrating SFT with a Security-Constrained Unit Commitment (SCUC) optimizer for efficient single pass solutions; operating SFT as a service to multiple SCUC solvers; or integration with Security-Constrained Economic Dispatch (SCED) optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Are System Baselines within OT Environments Feasible?

Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.

02 PETROLEUM↗
DOE OSTI2023

Feasibility of Power Ramp Testing in the Advanced Test Reactor

For decades, the Halden Boiling Water Reactor (HBWR) in Norway was an international resource for assessing nuclear fuels and materials behavior and its unexpected shutdown in 2018 represented a significant loss in experimental capability for prototypical irradiation testing. In the aftermath of the closure, a study was performed to assess capability gaps related to the Accident Tolerant Fuels (ATF) program. It was concluded that the primary capability gaps left by the closure of the HBWR were the loss of prototypic in-pile Light Water Reactor (LWR) loops that provide operational transient testing and in-pile Loss-of-Coolant Accident (LOCA) testing capabilities. The study also concluded that the Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) likely have the necessary key capabilities to absorb the breadth of the HBWR mission gaps related to the ATF program, but additional investments in experimental infrastructure were needed. One such investment is the design and installation of additional pressurized water loops in the medium-I positions of the ATR, hereafter referred to as I-Loops, to support power ramp testing and testing in Boiling Water Reactor (BWR) conditions. This paper gives an overview of the planned ATR I-Loops and assesses the feasibility of performing power ramp testing inside such a loop.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Deployment Feasibility Futures Analysis of Natural Gas Combined Cycle with Carbon Capture in Five U.S. Regions

A broad suite of technologies will be required to enable the United States to meet the current goal of a zero-carbon power sector by 2035, while continuing to provide the U.S. consumer with reliable, secure, stable, and affordable electricity. This study was conducted to evaluate the competitiveness of a natural gas combined cycle (NGCC) with carbon capture and storage (CCS) in five independent system operating areas, the PJM interconnection (PJM) regional transmission organization, Midcontinent Independent System Operator (MISO), Western Electricity Coordinating Council’s (WECC) Northwest Power Pool (NWPP) region, the Electric Reliability Council of Texas (ERCOT) and the SERC Reliability Corporation (SERC) in the 2030 to 2035 time horizon. The modeling and simulation efforts focused on determining the dispatch characteristics and the economic feasibility of constructing an NGCC plant with CCS in each of those regions. The analysis indicates that a NGCC system with CCS can be economically viable in the ERCOT and PJM regions. Additional revenue stream and/or capacity payments are required in MISO, NWPP, and SERC to enable successful commercial deployment of a NGCC with CCS.

Pickenpaugh, Gavin↗
DOE OSTI2023

Milestone 1.2.15: Feasibility of In Situ Accelerated Aluminum Coupon Radiolysis by Synchrotron X-Rays

Extended dry storage of aluminum-clad spent nuclear fuel (ASNF) requires an assessment of the radiolytic generation of molecular hydrogen gas (H2) from the ASNF’s corrosion layers. H2 accumulation can potentially lead to storage canister embrittlement/rupture and the accumulation of flammable gas mixtures in accident scenarios. To date, computational models have been developed for the prediction of radiolytic H2 generation from samples exposed to lower absorbed dose regimes (up to ~3 MGy). However, greater accuracy is needed for higher absorbed doses (> 25 MGy) where the concentration of H2 ultimately reaches a steady-state. Data in this area is limited due to the amount of time taken (months) to accumulate such high gamma doses. Furthermore, a recent study observed radiation-induced damage to the surface of pre-corroded aluminum alloy coupons at high absorbed gamma doses. Despite this observation and its implications, there is currently no computational connection between the radiolytic formation of H2 and changes in the composition and morphology of the cladding’s corrosion layers with absorbed dose. To develop a better understanding of the processes and effects described above, the present study aimed to evaluate the feasibility of leveraging synchrotron x-ray capabilities for coupled accelerated irradiation and in situ surface characterization of ASNF alloys. To that end, National Synchrotron Light Source II (NSLS-II) beamtime was secured and a series of aluminum alloy 1100 (AA1100) wires, prepared under a variety of conditions, were interrogated using ex situ x-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques at Idaho National Laboratory (INL) and ex situ and in situ XRD capabilities at the NSLS-II x-ray powder diffraction (XPD) beamline. Results indicated that performing synchrotron XRD using the available XPD beamline configuration can provide sufficient radiation dose but cannot discern changes in the composition and morphology of sample corrosion layers. Additionally, ex situ XRD and SEM data from Idaho National Laboratory (INL) indicated that the pre-corrosion of AA1100 wires did not generate an appreciably thick corrosion layer, as compared with previous aluminum coupon studies. These thinner surface corrosion layers were not sufficient for detection by both ex situ and in situ synchrotron XRD, specifically under consideration of the NSLS-II XPD beamline’s configuration primarily capturing information from the sample’s bulk material, i.e., aluminum metal. In summary, the use of the NSLS-II XPD beamline for promoting accelerated radiolysis and in situ surface characterization is not appropriate for this program’s goals.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

An Experimental Feasibility Study on Applying Neutron Tomography to Encapsulated Spent Nuclear Fuel - 20050

Visual inspection makes easier to ensure the integrity and safety of spent nuclear fuel (SNF) than any classical techniques. Various classical techniques have been applied but there are no reliable methods to qualitatively and quantitatively verify spent fuel in dry storage. Thus, the present authors have developed the prototype safeguards apparatus for dry storage employing the array of He-4 gas scintillation detectors (S670E, Arktis Radiation Detectors Ltd., Switzerland), newly designed to simultaneously measure thermal and fast neutrons without any moderators. The S670E detector has a cylindrical shape with a diameter of 52 mm and active length of 600 mm (total length: 875 mm). The detector is filled by He-4 gas with an approximate pressure of 180 bar for fast neutron detection, and its inner wall is coated by Li-6 for thermal neutron detection. The scintillation lights generated via Li-6 nuclear reaction and elastic scattering are collected by 24 SiPMs linearly paired at the center of the detector. The detector delivers a TTL (Transistor-Transistor Logic) output for pulse readout and UART (Universal Asynchronous Receiver Transmitter) for device control. In order to assess feasibility of the apparatus, an experimental system has been designed, built, and optimized via computational studies. Cf-252 neutron sources and linearly arrayed detectors, working as a single detector, were occupied for this study due to the difficulties in working with SNF. The laboratory scale cask (diameter: 0.67 m, height: 1.5 m), minimized by a factor of 10 compared to the actual thickness of a commercial TN-32 cask, was also manufactured. The detector array was designed to rotate the lab-scale cask and obtain 36 image profiles at every 10 degrees. All profiles were aligned in single frame image called a sinogram, and the cross-sectional image was then fabricated by the inverse radon transform algorithm. These experiments have been repeated with different configurations and numbers of sources. Some gamma-ray sources were also measured with neutron sources in order to distinguish between neutron and gamma-ray pulses. Basically, a He-4 detector is designed to run on Linux OS so it is difficult to directly apply to Windows-based equipment widely used in S. Korea. Therefore, a new data acquisition board working on Windows OS was designed and built. The board mainly consists of FPGA (Field Programmable Gate Array) and SoC (System on Chip) for TTL pulse readout, sorting measured data, and transferring data to a user interface. In conclusion, the tomographic system at lab-scale has shown considerable potential to detect a partial or gross defect of encapsulated assemblies in dry storage. Next steps of this study will be to 1) repeatedly carry out experiments to demonstrate scientific reliability and validity, and 2) numerically integrate signals with weight factors to enhance the image quality since the suggested system based on passive interrogation method requires longer measurement time. Finally, the system will apply to a commercial dry storage phased out soon in S. Korea. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Feasibility of lead-bismuth-cooled fast reactor with fuel shuffling strategy

This paper investigates the feasibility of fuel shuffling of the Advanced Nitride-fueled Simplified 100 MWe (ANTS-100e) Lead-bismuth-cooled Fast Reactor (LFR). The preliminary design has the active core of 235 cm in diameter and 100 cm high. The core is composed of 138 hexagonal fuel assemblies enclosed with a 15-15Ti steel duct. The core adopts the onion zoning with the two zones of low-enriched uranium for a better breeding capability to maximize the first cycle length to 10 effective full-power years (EFPYs). The fuel shuffling study is performed by using the UNIST in-house Monte Carlo code MCS. The neutronic parameters such as the multiplication factor and burnup are being investigated. The fuel shuffling strategy is evaluated through several loading patterns for flattening radial power distribution. It is also found that the core with fuel shuffling could lengthen the core lifetime by more than 5 EFPYs without introducing fresh fuel. Thus, it appears that the ANTS-100e can be principally designed to have the second cycle with another 10 EFPYs if introducing fresh fuel into the core. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗