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At least 1,585 records · Page 88

Preliminary Analysis of Separation Standards for Urban Air Mobility using Unmitigated Fast-Time Simulation

This research provides a preliminary analysis of various separation standards for Urban Air Mobility (UAM) operations. This study focuses on understanding and analyzing potential conflicts between UAM flights and conflicts between UAM and conventional aircraft. Fast-time simulations are conducted with a projected high-density of UAM traffic scenario and historical conventional non-UAM traffic flying under Instrument Flight Rules (IFR) or Visual Flight Rules (VFR) in Dallas Fort Worth (DFW) airspace. The conflicts are analyzed by examining losses of separation and near mid-air collisions of UAM flights and unmitigated risk of collision. A set of varied separation standards are used to investigate the impact of the new UAM operations on safety. The preliminary conflict analysis results will help inform separation standards development and in airspace and route design activities for future UAM operations.

Urban Air Mobility↗

Interpretable Convolutional Learning Classifier System (C-LCS) for Higher Dimensional Datasets

The purpose of this paper is to devise an interpretable hybrid classification model for Convolutional Neural Networks (CNN) and a Learning Classifier System (LCS). The presented hybrid system integrates the fundamental attributes from both types of these classifiers. In the proposed hybrid model CNN works as an automatic feature extractor, and LCS works to provide interpretable rule-based classification results. Although LCS has limitations working on higher dimensional datasets, we resolve this limitation by using CNN as a feature extractor. The other concept of the non-interpretability of CNN is addressed by using the LCS rule. Furthermore, our experiment with higher dimensional datasets like CIFAR-10 and Fashion-MNIST shows that extended LCS provides comparable performance to the standard neural network model while also providing interpretable results. We named this extended LCS method Convolutional Learning Classifier Cystem (C-LCS).

Jelani Owens↗

A Unifying View of Estimation and Control Using Belief Propagation With Application to Path Planning

The use of estimation techniques on stochastic models to solve control problems is an emerging paradigm that falls under the rubric of Active Inference (AI) and Control as Inference (CAI). In this work, we use probability propagation on factor graphs to show that various algorithms proposed in the literature can be seen as specific composition rules in a factor graph. We show how this unified approach, presented both in probability space and in log of the probability space, provides a very general framework that includes the Sum-product, the Max-product, Dynamic programming and mixed Reward/Entropy criteria-based algorithms. The framework also expands algorithmic design options that lead to new smoother or sharper policy distributions. We propose original recursions such as: a generalized Sum/Max-product algorithm, a Smooth Dynamic programming algorithm and a modified versions of the Reward/Entropy algorithm. The discussion is carried over with reference to a path planning problem where the recursions that arise from various cost functions, although they may appear similar in scope, bear noticeable differences. We provide a comprehensive table of composition rules and a comparison through simulations, first on a synthetic small grid with a single goal with obstacles, and then on a grid extrapolated from a real-world scene with multiple goals and a semantic map.

Francesco A. N. Palmieri↗

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically ATCSCC planning telecon audio transcriptions. The Air Traffic Control System Command Center (ATCSCC) hosts bihourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. ITN is the process of converting un-formatted "raw'' speech-to-text transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With a preliminary overall Word Error Rate with Punctuation and Capitalization (WER PC) of 8.26, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

Air Traffic Management↗

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

The primary contribution of this paper is an initial analysis of integrating digitally enabled cooperative operations (or digital operations for short) with Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) operations in the terminal airspace around a Class D airport, specifically around Fort Worth Alliance airport (KAFW). Enabled by connected digital technologies and automated information exchange, digital operations as envisioned would utilize cooperative practices and operator-responsible separation to ensure safety. In the present study, three conflict management configurations for digital operations were analyzed: 1) centralized with a single instance of a conflict management service to model a scenario with only one fleet operator conducting digital operations or all fleet operators utilizing the same service, 2) federated with two different instances to model a scenario with two different fleet operators conducting digital operations, and 3) fully distributed with a different instance for each digital operation. In simulations in which recorded tracks for VFR and IFR operations were played back and digital operations were modeled that would nominally arrive at KAFW once every 20 minutes (given no conflict resolution maneuvers), there were one or fewer losses of separation (LOS) across the three conflict management configurations. The same result was seen in simulations in which digital operations would nominally arrive at KAFW once every 10 minutes. However, in simulations in which digital operations would nominally arrive at KAFW once every 5 minutes, the number of LOS ranged between six and ten. This highlights the need for follow-on research to investigate the extent to which additional capabilities for digital operations, such as complexity management and/or flow organization, may be needed.

digitally enabled cooperative operations, digital ↗

Inverse Text Normalization of Air Traffic Control System Command Center Planning Telecon Transcriptions

We present a hybrid neural network and rule-based Inverse Text Normalization (ITN) method for domains containing unique technical phraseology, specifically Air Traffic Control System Command Center (ATCSCC) planning telecon audio transcriptions. The ATCSCC hosts bi-hourly planning telephone conferences (or planning telecons) to ensure smooth operations within the National Airspace (NAS). Access to both live and post meeting transcripts of this speech audio would enable quick review of meetings. Provided speech transcripts, ITN is the process of converting unformatted raw Automated Speaker Recognition (ASR) model transcripts into a human (expert) readable written form. Our hybrid ITN framework utilizes a fine-tuned Bidirectional Encoder Representations from Transformers neural network to format conversational English, and rule-based methods to format domain-specific aviation text. With an overall Punctuation Error Rate (PER) of 25.56 and Word Error Rate with Punctuation and Capitalization (WER PC) of 5.47, we show that this method has vast potential in being applied to ATCSCC planning telecon audio and other audio/text based data available in ATM.

ATM↗

Initial Analysis of Digitally Enabled Cooperative Operations in Class D Terminal Airspace

The primary contribution of this paper is an initial analysis of integrating digitally enabled cooperative operations (or digital operations for short) with Visual Flight Rules (VFR) and Instrument Flight Rules (IFR) operations in the terminal airspace around a Class D airport, specifically around Fort Worth Alliance airport (KAFW). Enabled by connected digital technologies and automated information exchange, digital operations as envisioned would utilize cooperative practices and operator-responsible separation to ensure safety. In the present study, three conflict management configurations for digital operations were analyzed: 1) centralized with a single instance of a conflict management service to model a scenario with only one fleet operator conducting digital operations or all fleet operators utilizing the same service, 2) federated with two different instances to model a scenario with two different fleet operators conducting digital operations, and 3) fully distributed with a different instance for each digital operation. In simulations in which recorded tracks for VFR and IFR operations were played back and digital operations were modeled that would nominally arrive at KAFW once every 20 minutes (given no conflict resolution maneuvers), there were one or fewer losses of separation (LOS) across the three conflict management configurations. The same result was seen in simulations in which digital operations would nominally arrive at KAFW once every 10 minutes. However, in simulations in which digital operations would nominally arrive at KAFW once every 5 minutes, the number of LOS ranged between six and ten. This highlights the need for follow-on research to investigate the extent to which additional capabilities for digital operations, such as complexity management and/or flow organization, may be needed.

digitally enabled cooperative operations↗

Recent Progress and Development of Self-Aligned Focusing Schlieren

A broad range of developments and applications of self-aligned focusing schlieren (SAFS)systems is presented. The replacement of the Ronchi ruling (RR) with a𝜇LCD was demonstrated with digital SAFS, which provides the ability to modulate the pattern and orientation without physical intervention. Additionally, replacement of the traditional RR with spectral-spatial filters was demonstrated to yield the ability to simultaneously image horizontal and vertical index of refraction gradients using two separate wavelengths. The application of the Scheimpflug principle to SAFS systems enables off-axis imaging and allowed for extended fields-of-view to be captured using a two-camera system. The addition of a plenoptic camera to a baseline SAFS system enables refocusing capabilities, which is demonstrated on two jets offset along the optical axis. Furthermore, application of an event-based camera to SAFS was shown to enable acquisition of sparse, spatio-temporal data. Beyond the listed developments, SAFS was applied to difficult and constraining facilities, such as the National Full-Scale Aerodynamics Complex(NFAC) 80- by 120-ft Wind Tunnel and the Thermal Acoustic Engines (TAE) rig at NASA Ames Research Center and NASA Glenn Research Center, respectively. Behavior of Ronchi rulings, Rochon prisms, and the use of quarter-wave plates versus quarter-wave films are evaluated to provide insight for future experimental design of SAFS-systems.

Self-Aligned Focusing Schlieren↗

Recent Progress and Development of Self-Aligned Focusing Schlieren

A broad range of developments and applications of self-aligned focusing schlieren (SAFS)systems is presented. The replacement of the Ronchi ruling (RR) with a𝜇LCD was demonstrated with digital SAFS, which provides the ability to modulate the pattern and orientation without physical intervention. Additionally, replacement of the traditional RR with spectral-spatial filters was demonstrated to yield the ability to simultaneously image horizontal and vertical index of refraction gradients using two separate wavelengths. The application of the Scheimpflug principle to SAFS systems enables off-axis imaging and allowed for extended fields-of-view to be captured using a two-camera system. The addition of a plenoptic camera to a baseline SAFS system enables refocusing capabilities, which is demonstrated on two jets offset along the optical axis. Furthermore, application of an event-based camera to SAFS was shown to enable acquisition of sparse, spatio-temporal data. Beyond the listed developments, SAFS was applied to difficult and constraining facilities, such as the National Full-Scale Aerodynamics Complex(NFAC) 80- by 120-ft Wind Tunnel and the Thermal Acoustic Engines (TAE) rig at NASA Ames Research Center and NASA Glenn Research Center, respectively. Behavior of Ronchi rulings, Rochon prisms, and the use of quarter-wave plates versus quarter-wave films are evaluated to provide insight for future experimental design of SAFS-systems.

Self-Aligned Focusing Schlieren↗

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at about 3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching about 4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid's diameter at 60 +/- 7 m. Studies of 2024 YR 4 's potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. We cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid Disruption↗

Space Nuclear Propulsion for Space Applications: Multi-Mission Nuclear Thermal Propulsion Vehicle Design

This NASA Technical Memorandum (TM) is intended to capture design work that the Advanced Concepts Office (ACO) at NASA’s Marshall Space Flight Center (MSFC) performed on behalf of the Space Nuclear Propulsion (SNP) Project during an SNP-driven design and mission analysis initiative in FY2025. Specifically, this TM focuses on several spacecraft design concepts intended to explore the feasibility of nuclear thermal propulsion (NTP) for use in a selection of notional, unmanned space missions. While references to the missions will be made in this TM, the primary focus will be on the spacecraft design concepts themselves, the ground rules and assumptions used for designing the spacecraft, a description of the various subsystems and their performance parameters, and the methodologies used to design them. The TM will also highlight areas of future work and additional considerations that may need to be taken into account when evaluating the feasibility of NTP space systems for other applications. The report will discuss the results from ACO’s analysis as they pertain to the different vehicle concepts that were evaluated. Each discipline section in this report will discuss the discipline-specific ground rules and assumptions, the methodology and design approaches employed, and present the results along with any relevant discussion, and highlight areas of future work where applicable.

Mitchell A Rodriguez↗

A Visual Designer of Layer-wise Relevance Propagation Models

Layer-wise Relevance Propagation (LRP) is an emerging and widely-used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a "best" LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance-based visual analysis with two important functions: relevance-based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

97 MATHEMATICS AND COMPUTING↗

PET imaging of zinc transport

A method for producing a solution including a positron emitting zinc cation of 63Zn, and the method comprises bombarding a solution target including 63 Cu with high energy protons to produce a solution including a positron emitting zinc cation. A method for detecting or ruling out Alzheimer's disease in a patient comprises administering to a patient a detectable amount of a compound including a positron emitting zinc cation, wherein the zinc cation is targeted to β-amyloid in the patient, and acquiring an image to detect the presence or absence of β-amyloid in the patient. A method for detecting or ruling out cancer in a patient comprises administering to a patient a detectable amount of a compound including a positron emitting zinc cation, wherein the zinc cation is targeted to tissue in the patient; and acquiring an image using a medical imaging technique to detect zinc distribution in tissue in the patient.

DeGrado, Timothy R.↗

Snowmass2021 CMB-HD White Paper

CMB-HD is a proposed millimeter-wave survey over half the sky that would be ultra-deep (0.5 uK-arcmin) and have unprecedented resolution (15 arcseconds at 150 GHz). Such a survey would answer many outstanding questions about the fundamental physics of the Universe. Major advances would be 1.) the use of gravitational lensing of the primordial microwave background to map the distribution of matter on small scales (k~10 h Mpc^(-1)), which probes dark matter particle properties. It will also allow 2.) measurements of the thermal and kinetic Sunyaev-Zel'dovich effects on small scales to map the gas density and velocity, another probe of cosmic structure. In addition, CMB-HD would allow us to cross critical thresholds: 3.) ruling out or detecting any new, light (< 0.1 eV) particles that were in thermal equilibrium with known particles in the early Universe, 4.) testing a wide class of multi-field models that could explain an epoch of inflation in the early Universe, and 5.) ruling out or detecting inflationary magnetic fields. CMB-HD would also provide world-leading constraints on 6.) axion-like particles, 7.) cosmic birefringence, 8.) the sum of the neutrino masses, and 9.) the dark energy equation of state. The CMB-HD survey would be delivered in 7.5 years of observing 20,000 square degrees of sky, using two new 30-meter-class off-axis crossed Dragone telescopes to be located at Cerro Toco in the Atacama Desert. Each telescope would field 800,000 detectors (200,000 pixels), for a total of 1.6 million detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CANShield: Signal-based Intrusion Detection for Controller Area Networks

Modern vehicles rely on complex cyber-physical systems made up of hundreds of electronic control units (ECUs) connected through controller area network (CAN) buses. However, the CAN bus attack surface is increasing due to advanced features in automobiles, making it prone to injection attacks. The ordinary injection attacks disrupt the typical timing properties of the CAN data stream, and the rule-based intrusion detection systems (IDS) can easily detect them. However, advanced attackers can inject false data to the signal level, maintaining the regular pattern/frequency of the CAN messages. Such attacks can bypass the rule-based IDS or any anomaly-based IDS built on binary payload data. To make the vehicles robust against such intelligent attacks, we propose CANShield, a signal-based intrusion detection framework for the CAN bus that consists of three modules. A data preprocessing module handles the high-dimensional CAN data stream at the signal level and make them suitable for any machine learning model. A data analyzer module consists of multiple deep autoencoder networks, each analyzing the time series data from a different perspective. Finally, an attack detection module uses an ensemble method to make the final decision. Evaluation results on a standard signal-based dataset show the effectiveness of the CANShield in detecting five advanced attacks.

Shahriar, Md Hasan↗

Model Predictive Control for a Grid-interactive Efficient Thermal Storage-integrated Heat Pump System

Building heating and cooling systems can be used to overcome the mismatch between the intermittent supply of renewable power and the fluctuating demand for electricity. A novel underground thermal energy storage integrated with a dual-source heat pump has been proposed to mitigate the mismatch while meeting the thermal demand of buildings efficiently. Conventional thermostat control with heuristic rules cannot provide intelligent decisions to maximize the thermal efficiency and flexibility of the proposed system. Advanced control strategies like model predictive control (MPC) have provided a new paradigm for grid-interactive efficient building operation with the advancement of computation and sensing. This study developed an MPC for the proposed system to provide grid service for Demand Side Management and minimize the operating cost of building owners. A control-oriented dynamic model of the proposed system has been developed. Given an objective function and proper constraints, an optimization problem is formulated to determine the optimal control strategy of the system. Dynamic Programming is adopted to solve the optimization problem. A rule-based control (RBC) is also developed to achieve similar goals. Short-term simulations are conducted to compare the system performance resulting from the two controls. The simulation results indicate that the MPC performs more intelligently than the RBC in charging thermal energy storage and selecting heat pump sources by taking advantage of the predicted cooling demands of the building and the performance of the integrated system. As a result, the MPC could save energy and reduce operating costs compared with the RBC. A case study shows that, for a 3-day operation, the MPC saves 36.9% energy and reduces 38.5% operating cost compared with the RBC.

Shi, Liang↗

Auto Procedure Parsing: A Natural Language Processing Approach

Nuclear Power Plant (NPP) operating procedure is “a set of rules that describes how actions on the plant should be made if a certain system goal should be accomplished. U.S. NPPs use paper-based procedures (PBPs). PBPs are difficult to use. Common errors with PBPs are: following the wrong procedure, omit a step etc. Computer based procedures (CPBs) offer great improvement in ensuring plant safety. Some studies rely on experienced operators to understand the procedure content and then reorganize the procedure with digitally executable capabilities. Other studies utilize the procedure format to design rules to extract information from the operating procedures. Existing studies in procedure parsing are manual, laborious and extract limited information. This study aims to automatically extract critical information from operating procedures for generating computer interpretable representation of procedures. Such representation can further be used for automatic dynamic human reliability analysis and CPB design etc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗