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At least 235 records · Page 13

Highly Automated Arrival Management and Control System Suitable for Early NextGen

This is a presentation of previously published work conducted in the development of the Terminal Area Precision Scheduling and Spacing (TAPSS) system. Included are concept and technical descriptions of the TAPSS system and results from human in the loop simulations conducted at Ames Research Center. The Terminal Area Precision Scheduling and Spacing system has demonstrated through research and extensive high-fidelity simulation studies to have benefits in airport arrival throughput, supporting efficient arrival descents, and enabling mixed aircraft navigation capability operations during periods of high congestion. NASA is currently porting the TAPSS system into the FAA TBFM and STARS system prototypes to ensure its ability to operate in the FAA automation Infrastructure. NASA ATM Demonstration Project is using the the TAPSS technologies to provide the ground-based automation tools to enable airborne Interval Management (IM) capabilities. NASA and the FAA have initiated a Research Transition Team to enable potential TAPSS and IM Technology Transfer.

Swenson, Harry N.↗

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Simulations of Urban Air Mobility Operations

Urban Air Mobility (UAM) aims to offer air taxi service as an alternative to driving on the congested roads. Integration of UAM operations into the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. In this talk, I present results from simulations performed during FY2019 to investigate if NASA’s UAS Traffic Management (UTM) architecture and its implementation are extensible for UAM operations. These simulations also tested a set of core airspace management services tailored to controlled airspace access. In the latter half of this talk, I present the efforts made towards the integration of two such services – a strategic scheduling and a tactical separation service – in a simulation environment under ideal conditions. I will conclude this talk by presenting the future work planned towards enabling UAM operations

Urban Air Mobility↗

Simulations of Urban Air Mobility Operations

Urban Air Mobility (UAM) aims to offer air taxi service as an alternative to driving on the congested roads. Integration of UAM operations into the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. In this talk, I present results from simulations performed during FY2019 to investigate if NASA’s UAS Traffic Management (UTM) architecture and its implementation are extensible for UAM operations. These simulations also tested a set of core airspace management services tailored to controlled airspace access. In the latter half of this talk, I present the efforts made towards the integration of two such services – a strategic scheduling and a tactical separation service – in a simulation environment under ideal conditions. I will conclude this talk by presenting the future work planned towards enabling UAM operations

Urban Air Mobility↗

The 4-D guidance of STOL aircraft in the terminal area

Advanced STOL aircraft for the improvement of the nation's air transportation system by the elimination of delays and congestions associated with today's air travel are discussed. A new guidance technique, referred to as 4-D guidance, is being developed for STOL aircraft. The 4-D guidance technique synthesizes complex three-dimensional flight paths from a minimum set of input and files the aircraft along the paths according to a prespecified time schedule. The two major elements of a 4-D guidance system are the trajectory synthesizer and the control law. Inputs to the trajectory synthesizer are the three-dimensional coordinates of way points, the turning radii, the speed ranges, the acceleration limits, and the arrival times at time control way points. First, the three-dimensional trajectory is computed by using circular arcs and straight lines. Then the airspeed profile, compensated for wind, is calculated to achieve the desired arrival times. The synthesized trajectory is stored as a time sequence of reference states which the aircraft is forced to track by using a linear feedback law.

Pecsvaradi, T.↗

Four-D guidance of STOL aircraft in the terminal area

The primary objective of advanced STOL aircraft is the improvement of the nation's air transportation system by the elimination of delays and congestions associated with today's air travel. A new guidance technique, referred to as 4-D guidance, is being developed to achieve this objective. The 4-D guidance technique synthesizes complex three-dimensional flight paths from a minimum set of input data and flies the aircraft along the paths according to a prespecified time schedule. The two major elements of a 4-D guidance system are the trajectory synthesizer and the control law. Inputs to the trajectory synthesizer are the three-dimensional coordinates of way points, the turning radii, the speed ranges, the acceleration limits, and the arrival times at time control way points. First, the three-dimensional trajectory is computed by using circular arcs and straight lines. Then the airspeed profile, compensated for wind, is calculated to achieve the desired arrival times. The synthesized trajectory is stored as a time sequence of reference states which the aircraft is forced to track by using a linear feedback law.

Pecsvaradi, T.↗

Tri-Agency Reliability Engineering Guidance: Post Mission Disposal and Extension Assessment

The Trilateral partners — the European Space Agency (ESA), Japan Aerospace Exploration Agency (JAXA), and National Aeronautics and Space Administration (NASA) and the United States Government (USG) in their execution of safe and successful missions, have a long-standing history of sustaining the shared space environment of operational Earth-Moon orbits with their global space-stewardship, or spacekeeping, of these areas. This has driven missions to limit the generation of new and long-lived debris, control debris releases, minimize accidental explosions and collisions, and ensure Post-Mission Disposal of space systems, so that the environment remains safe for future operations and explorations. Given the continued need for space systems to support global mandatory infrastructure and commercial enterprise, spacefarers are extending beyond the Trilateral partners, more and smaller satellites are being deployed, and current assets are being utilized much longer than expected. This is making space more congested than ever; therefore, the Trilateral partners are evaluating potential future debris mitigation strategies, evolving technology, developing on-orbit servicing capabilities, and advancing their abilities to assess disposal and mission extension plans. They are also sharing their lessons learned and identifying opportunities for future state-of-the-art advancements for current and future space enterprises. Sustaining the space environment cannot be ensured by any one agency or country. Thus, the Trilateral authors have shared their lessons learned, insights, and guidance, herein, on disposal and mission extension assessment strategies with the gratitude of each agency. As such, this document is not prescriptive, but was formulated to enhance value-and-risk-balanced operational decision-making, support policy refinement, and guide spacefaring partners beyond these agencies to assess their activities in space with safety and a global space-stewardship, or spacekeeping, in mind. This includes not only the disposal and mission extension assessment addressed herein, but also preserving space history, ensuring collaboration/interoperability of technology, supporting fellow operators without interfering, and the utilization of in-situ resources for the common benefit of humankind. It is the intention of the Trilateral partners that this document evolves based on community lessons learned and the introduction of new assessment methodologies. So, all readers are encouraged to share their insights with the authors from their own application of this guidance or other strategies to ensure each mission has a successful, safe, and judicious life and conclusion.

ESA↗

Evaluating an Eco-Cooperative Automated Control System

The paper evaluates an Eco-Cooperative Automated Control (Eco-CAC) system on a large-scale network considering a combination of internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), and battery-only electric vehicles (BEVs) in a microscopic traffic simulation environment. We used a novel integrated control system that: (1) routes ICEVs, HEVs, and BEVs in a fuel/energy-efficient manner; (2) selects vehicle speeds based on anticipated traffic network evolution; (3) minimizes vehicle fuel/energy consumption near signalized intersections; and (4) intelligently modulates the longitudinal motion of vehicles along freeways within a cooperative platoon to minimize fuel/energy consumption. The study tested the system using the INTEGRATION software on the Los Angeles (LA), U.S., downtown network for three different demand levels: no congestion, mild congestion, and heavy congestion. The results demonstrated that the Eco-CAC system effectively reduces vehicle fuel and energy consumption, travel time, total delay, and stopped delay in heavily congested conditions. However, different vehicle compositions produced different results. In particular, the maximum energy consumption savings for BEVs (36.9%) for a current vehicle composition occurred at a 10% market penetration rate (MPR) of connected automated vehicles (CAVs) in mild congestion, while the maximum savings for a future vehicle composition (35.5%) occurred at a 50% CAV MPR in no congestion. The system reduced fuel consumption for ICEVs and HEVs by up to 5.4% and 6.3% at a 25% CAV MPR in heavy congestion for current and future vehicle compositions, respectively. However, the system increased total fuel consumption by up to 4.6% at a 50% CAV MPR in no congestion for a current vehicle composition. The study demonstrates that the effectiveness of the Eco-CAC system depends on traffic conditions, including congestion level, network configuration, CAV MPR, and vehicle composition.

Engineering↗

Multifractality in human heartbeat dynamics

There is evidence that physiological signals under healthy conditions may have a fractal temporal structure. Here we investigate the possibility that time series generated by certain physiological control systems may be members of a special class of complex processes, termed multifractal, which require a large number of exponents to characterize their scaling properties. We report on evidence for multifractality in a biological dynamical system, the healthy human heartbeat, and show that the multifractal character and nonlinear properties of the healthy heart rate are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure.

Non-NASA Center↗

Time Relevance of Convective Weather Forecast for Air Traffic Automation

The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

Chan, William N.↗

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗

Predictability of Top of Descent Location for Operational Idle-Thrust Descents

To enable arriving aircraft to fly optimized descents computed by the flight management system (FMS) in congested airspace, ground automation must accurately predict descent trajectories. To support development of the trajectory predictor and its uncertainty models, commercial flights executed idle-thrust descents at a specified descent speed, and the recorded data included the specified descent speed profile, aircraft weight, and the winds entered into the FMS as well as the radar data. The FMS computed the intended descent path assuming idle thrust after top of descent (TOD), and the controllers and pilots then endeavored to allow the FMS to fly the descent to the meter fix with minimal human intervention. The horizontal flight path, cruise and meter fix altitudes, and actual TOD location were extracted from the radar data. Using approximately 70 descents each in Boeing 757 and Airbus 319/320 aircraft, multiple regression estimated TOD location as a linear function of the available predictive factors. The cruise and meter fix altitudes, descent speed, and wind clearly improve goodness of fit. The aircraft weight improves fit for the Airbus descents but not for the B757. Except for a few statistical outliers, the residuals have absolute value less than 5 nmi. Thus, these predictive factors adequately explain the TOD location, which indicates the data do not include excessive noise.

Stell, Laurel L.↗

Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty

This paper addresses the challenges in accurate and realtime traffic congestion prediction with uncertainty by proposing Ising-Traffic, a novel quantum-inspired dual-model Ising based traffic prediction framework which delivers higher accuracy and lower latency than SOTA solutions. While traditional and deep learning methods face the trade-off between algorithm complexity and computational efficiency, our Ising-based method leverages Ising’s inherent and unique capability of finding the state of a system with the lowest energy and applying it to traffic prediction. In this work, traffic prediction under uncertainty is formulated into two separate Ising models: Reconstruct-Ising and Predict-Ising. Reconstruct-Ising is mapped onto modern Ising machine and handles uncertainty in traffic accurately with negligible latency and energy consumption, while Predict-Ising is mapped onto traditional processors and predicts future congestion precisely with only at most 1.8% computational demands of existing solutions. Our evaluation shows Ising-Traffic delivers on average 98× speedups and 5% accuracy improvement over SOTA.

traffic flow control, Ising↗

New Mobility Technology Assessment - Benefits, Risks, and Safety

The age of vehicle automation is upon us. The fundamental perception and control technology is maturing as we speak (and write) with robo-taxis proliferating in select US cities. The news cycle is no longer filled with technological skepticism, but rather societal commentary on our collective response and use of the technology. This maturing of the technology is also accompanied by a renaissance in new types of urban movement technology to more effectively link people with goods, services, and employment, particularly in dense development areas where vehicle congestion (even automated vehicles) prevents high quality mobility. The National Renewable Energy Laboratory, through the DOE Clean Energy to Communities (C2C) program has worked with two jurisdictions to assess the benefits, risks, and safety concerns for a new product offering based on suspended cable technology which is fully automated and proposes an aerial network of self-propelled gondolas. The recognized need, independent of the technology, is to fairly assess the benefits of the proposed transportation system, assess its technical maturity, as well as risks and safety concerns. Using this new technology as an example, a technology represented by Swyft Cities, NREL developed a succession of mini-studies that characterized the technical maturity level, assessed the proposed benefits for Greenville, SC, examined the risks involved in moving forward with an emerging mobility technology, and determined the governing safety protocols and standards that are applicable to the space. These mini-case studies, though centered on Swyft Cities aerial automated gondola technology, are highly transferable to any type of new mobility technology and lays out a repeatable process for assessing new technology within an city or community context.

33 ADVANCED PROPULSION SYSTEMS↗

Effects of moderate heart failure and functional overload on rat plantaris muscle

It is thought that changes in sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) of skeletal muscle contribute to alterations in skeletal muscle function during congestive heart failure (CHF). It is well established that exercise training can improve muscle function. However, it is unclear whether similar adaptations will result from exercise training in a CHF patient. Therefore, the purpose of this study was to determine whether skeletal muscle during moderate CHF adapts to increased activity, utilizing the functional overload (FO) model. Significant increases in plantaris mass of the CHF-FO and sham-FO groups compared with the CHF and control (sham) groups were observed. Ca(2+) uptake rates were significantly elevated in the CHF group compared with all other groups. No differences were detected in Ca(2+) uptake rates between the CHF-FO, sham, and sham-FO groups. Increases in Ca(2+) uptake rates in moderate-CHF rats were not due to changes in SERCA isoform proportions; however, FO may have attenuated the CHF-induced increases through alterations in SERCA isoform expression. Therefore, changes in skeletal muscle Ca(2+) handling during moderate CHF may be due to alterations in regulatory mechanisms, which exercise may override, by possibly altering SERCA isoform expression.

Non-NASA Center↗

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗

Air Traffic Control Response to Delays: A System Study of Newark International Airport

Airport delays are a significant problem in the United States air transportation system. Between 1999 and 2000 the number of flights delayed increased by 20 percent despite only a 0.4% increase in total operations. Newark International Airport (EWR), one of New York City's primary airports, is one of the airports in the United States most impacted by delays. Newark had the highest percentage of operations delayed in 1999, and was second only to LaGuardia Airport in 2000. Nearly 85% of delays at Newark are caused by adverse weather impacting an airport that may be characterized as having limited capacity and a very full schedule. Although Newark is heavily impacted by weather, delays have not increased significantly since 1998. This indicates that the airlines, air traffic control (ATC), and the Port Authority of New York and New Jersey have successfully adapted. On June 29, 2000, a research team from MIT visited Newark airport to assess the effectiveness of any adaptations made, and to collect data on airline and ATC departure operations, and of the national and local weather affecting the airport. Airline and ATC personnel were also interviewed. Results of this study indicate that airspace capacity limitations downstream of the airport are a primary flow constraint at the airport, and that these constraints are the source of most surface delays. A number of tactical ATC responses to delays were examined, including the application of restrictions, re-routing with the help of the National Playbook, and the use of decision-aiding tools such as the Dynamic Spacing Program (DSP) and the Integrated Terminal Weather System (ITWS). Improved interfacility communications and further utilization of runway 11-29 were identified as other tactical responses to delays, whilst the formation of the Air Traffic Control System Command Center and the New York Airspace redesign were identified as thekey strategic ATC responses to delays. Particularly the New York airspace redesign has great potential to reduce delays at the airport. Because delays at Newark are caused by downstream flow constraints, the responses at the airport can be applied to other airports as delays from downstream constraints increase. Such an increase in delays system wide from downstream constraints is inevitable as the system becomes more congested.

Evans, Antony D.↗

The Potential Impact of Offshore Wind Energy on a Future Power System in the U.S. Northeast

This study aims to understand and quantify the potential impact of offshore wind on a future electricity system in the U.S. Northeast. In this analysis, a detailed representation of the Northeast power system is adopted, using a generation portfolio for 2024 paired with offshore wind nameplate capacities of 0 gigawatts (GW), 2 GW, and 7 GW. The analysis identifies points of offshore wind interconnection in the ISO-New England and New York Independent System Operator control areas and uses hourly wind profiles from the Wind Integration National Dataset Toolkit. Hourly simulations of the 2024 power system operations show an ability to accommodate the prescribed offshore wind capacities by adapting the system's generation dispatch. Curtailment levels of offshore wind range between 4% and 5%. Offshore wind generation displaces primarily natural-gas combined-cycle generation; however, requires increased flexibility from combined cycles through more frequent start-ups. The number of hours with transmission congestion increases because of offshore wind injection, with varying impact on a subregional level. Offshore wind's capacity credit was found to be 14.5%-28.3% and is lower than estimated in other large-scale power system studies, in part because this study considered a different weather year and a power system representation with higher shares of solar PV and onshore wind. The reliability contribution of resources is a topic area identified for more research and collaboration. The 7-GW scenario shows a reduction in locational marginal price of 11%, with production cost savings of up to 18% compared to the 0-GW scenario.

17 WIND ENERGY↗