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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 127 records · Page 7

ANTARES: Spacecraft Simulation for Multiple User Communities and Facilities

The Advanced NASA Technology Architecture for Exploration Studies (ANTARES) simulation is the primary tool being used for requirements assessment of the NASA Orion spacecraft by the Guidance Navigation and Control (GN&C) teams at Johnson Space Center (JSC). ANTARES is a collection of packages and model libraries that are assembled and executed by the Trick simulation environment. Currently, ANTARES is being used for spacecraft design assessment, performance analysis, requirements validation, Hardware In the Loop (HWIL) and Human In the Loop (HIL) testing.

Acevedo, Amanda↗

Building Airport Surface HITL Simulation Capability

FutureFlight Central is a high fidelity, real-time simulator designed to study surface operations and automation. As an air traffic control tower simulator, FFC allows stakeholders such as the FAA, controllers, pilots, airports, and airlines to develop and test advanced surface and terminal area concepts and automation including NextGen and beyond automation concepts and tools. These technologies will improve the safety, capacity and environmental issues facing the National Airspace system. FFC also has extensive video streaming capabilities, which combined with the 3-D database capability makes the facility ideal for any research needing an immersive virtual and or video environment. FutureFlight Central allows human in the loop testing which accommodates human interactions and errors giving a more complete picture than fast time simulations. This presentation describes FFCs capabilities and the components necessary to build an airport surface human in the loop simulation capability.

facility capabilities↗

Designing Scenarios for Controller-in-the-Loop Air Traffic Simulations

Within the Human Factors Division at NASA Ames Research Center the Airspace Operations Laboratory (AOL) is developing advanced automation concepts that help to transform the National Airspace System into NextGen, the Next Generation Air Transportation System. High-fidelity human-in-the-loop (HITL) simulations are used as a means to investigate and develop roles, responsibilities, support tools, and requirements for human operators and automation. This paper describes the traffic scenario design process and strategies as used by AOL researchers. Details are presented on building scenarios for specific simulation objectives using various design strategies. A focus is set on creating scenarios based on recorded real world traffic for terminal-area simulations.

scenario design↗

Structural basis for human NKCC1 inhibition by loop diuretic drugs

Abstract Na + –K + –Cl − cotransporters functions as an anion importers, regulating trans-epithelial chloride secretion, cell volume, and renal salt reabsorption. Loop diuretics, including furosemide, bumetanide, and torsemide, antagonize both NKCC1 and NKCC2, and are first-line medicines for the treatment of edema and hypertension. NKCC1 activation by the molecular crowding sensing WNK kinases is critical if cells are to combat shrinkage during hypertonic stress; however, how phosphorylation accelerates NKCC1 ion transport remains unclear. Here, we present co-structures of phospho-activated NKCC1 bound with furosemide, bumetanide, or torsemide showing that furosemide and bumetanide utilize a carboxyl group to coordinate and co-occlude a K + , whereas torsemide encroaches and expels the K + from the site. We also found that an amino-terminal segment of NKCC1, once phosphorylated, interacts with the carboxyl-terminal domain, and together, they engage with intracellular ion exit and appear to be poised to facilitate rapid ion translocation. Together, these findings enhance our understanding of NKCC-mediated epithelial ion transport and the molecular mechanisms of its inhibition by loop diuretics.

Biochemistry & Molecular Biology↗

Clearing the Air: New Approaches to Life Support in Outer Space

This article reports on research into atmospheric revitalization systems for long-term space travel and the use ofCOMSOL Multiphysics to understand how structured sorbents can be used to improve the performance of adsorption processes via thermal management. We are developing the next generation of atmosphere revitalization systems, which will reach for new levels of resource conservation via a high percentage of loop closure. For example, a high percentage of carbon dioxide, exhaled by crew, can be converted via reaction to drinking water, closing the loop from human metabolic waste to supply. Adsorption processes play a lead role in these new/closed loop systems.

Knox, J.↗

Developing Methods for Exercise System Kinematic Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as open CV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: 1. Busy and visually cluttered background 2. Low-textured tracking object with relatively small motions 3. Occlusions and motion by human subject and loose, floating objects 4. Limited number of video cameras with no fixed global references 5. Limited ability to add tags, markers, or visual references to the tracking object 6. Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L Nilsson↗

Developing Methods for Exercise System Kinematics Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as openCV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: Busy and visually cluttered background Low-textured tracking object with relatively small motions Occlusions and motion by human subject and loose, floating objects Limited number of video cameras with no fixed global references Limited ability to add tags, markers, or visual references to the tracking object Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L B Nilsson↗

Speeding-up fuzzing through directional seeds

Abstract Fuzzing is an automated process for discovering inputs in a program that may trigger unexpected behavior. Today, fuzzing has become a standard practice for the discovery of bugs and security vulnerabilities. However, the main issue with such practices is that the exploration of the input space of programs can often be prohibitively expensive. Therefore, several alternative fuzzing strategies have been introduced during the last few years. Some fuzzing techniques rely on human expertise to provide a plausible set of initial input examples, namely, seeds. However, the process of handcrafting seeds for fuzzing purposes often becomes strenuous for humans as it requires a deeper understanding of the Program-Under-Test (PUT). Also, the use of known inputs to programs often does not trigger vulnerable program behavior or may not reach potentially vulnerable code locations. To address those issues, we propose a seed generation framework that enables Human-In-The-Loop (HITL) directed fuzzing where the human assumes a more active role in the creation of seeds that can penetrate and assess desired locations of the PUT. Our proposed framework uses Symbolic Execution (SE) to generate seeds that exercise paths to target program locations. Moreover, our framework enables the visualization of the explored execution paths in the binary of the PUT for the generated seeds. We evaluated our approach on a set of 12 carefully designed C programs with diverse characteristics that mimic real-world programs. The experimental results show the effectiveness of the proposed approach in improving the performance of standard fuzzing tools such as the American Fuzzy Lop ("Image missing" <#comment/> ). Specifically, our solution can generate seeds that substantially enhance the performance of the fuzzer, achieving speedups ranging from $$1.46\times $$ 1.46 × to $$68.53\times $$ 68.53 × for branch conditions, $$1.39\times $$ 1.39 × to $$254.62\times $$ 254.62 × for branch depths, $$14,879.59\times $$ 14 , 879.59 × to $$30,295.88\times $$ 30 , 295.88 × for branch widths over traditional seeds. Additionally, the speedup increases with the number of target function ranging from $$12,260\times $$ 12 , 260 × to $$22,856.07\times $$ 22 , 856.07 × over traditional seeds while only requiring less than 15 seconds on average for the seed generation step.

97 MATHEMATICS AND COMPUTING↗

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

Matthews, Bryan L.↗

HESTIA Phase I Test Results: The Air Revitalization System

In any human spaceflight mission, a number of Environmental Control & Life Support System (ECLSS) technologies work together to provide the conditions astronauts need to live healthily, productively, and comfortably in space. In a long-duration mission, many of these ECLSS technologies may use materials supplied by In-Situ Resource Utilization (ISRU), introducing more interactions between systems. The Human Exploration Spacecraft Test-bed for Integration & Advancement (HESTIA) Project aims to create a test-bed to evaluate ECLSS and ISRU technologies and how they interact in a high-fidelity, closed-loop, human-rated analog habitat. Air purity and conditioning are essential components within any ECLSS and for HESTIA's first test they were achieved with the Air Revitalization System (ARS) described below. The ARS provided four essential functions to the test-bed chamber: cooling the air, removing humidity from the air, removing trace contaminants, and scrubbing carbon dioxide (CO2) from the air. In this case, the oxygen supply function was provided by ISRU. In the current configuration, the ARS is a collection of different subsystems. A fan circulates the air, while a condensing heat exchanger (CHX) pulls humidity out of the air. A Trace Contaminant Removal System (TCRS) filters the air of potentially harmful contaminants. Lastly, a Reactive Plastic Lithium Hydroxide (RP-LiOH) unit removes CO2 from the breathing air. During the HESTIA Phase I test in September 2015, the ARS and its individual components each functioned as expected, although further analysis is underway. During the Phase I testing and in prior bench-top tests, the energy balance of heat removed by the CHX was not equal to the cooling it received. This indicated possible instrument error and therefore recalibration of the instruments and follow-up testing is planned in 2016 to address the issue. The ARS was tested in conjunction with two other systems: the Human Metabolic Simulator (HMS) and the Electrolyzer. They behaved as anticipated as well. The HMS added humidity, CO2, and heat to the chamber while removing oxygen, and the Electrolyzer (an ISRU technology) added oxygen. The objective for HESTIA in 2015 was achieved: the creation of a high-fidelity test-bed for ECLSS and ISRU technologies. With the 'backbone' technologies installed, more technologies will be added to increase the analog habitat's fidelity over the next few years. The ARS was designed with this in mind, and as new technologies develop and mature, the strategic installation of the existing components will allow for them to be replaced with the new technologies.

Wright, Sarah E.↗

Evaluating human performance modeling for system assessment: Promise and problems

The development and evaluation of computational human performance models is examined. An intention is to develop models which can be used to interact with system prototypes and simulations to perform system assessment. Currently LR is working on a set of models emulating cognitive, psychomotor, auditory, and visual activity for multiple operator positions of a command and control simulation system. These models, developed in conjunction with BBN Systems and Technologies, function within the simulation environment and allow for both unmanned system assessment and manned (human-in-loop) assessment of system interface and team interactions. These are relatively generic models with built-in flexibility which allows modification of some model parameters. These models have great potential for improving the efficiency and effectiveness of system design, test, and evaluation. However, the extent of the practical utility of these models is unclear. Initial verification efforts comparing model performance within the simulation to actual human operators on a similar, independent simulation have been performed and current efforts are directed at comparing human and model performance within the same simulation environment.

Patterson, Robert W.↗

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Parameter estimation in linear models of the human operator in a closed loop with application of deterministic test signals

Parameter estimation techniques are discussed with emphasis on unbiased estimates in the presence of noise. A distinction between open and closed loop systems is made. A method is given based on the application of external forcing functions consisting of a sun of sinusoids; this method is thus based on the estimation of Fourier coefficients and is applicable for models with poles and zeros in open and closed loop systems.

Vanlunteren, A.↗

Development of Logistics for Building Radiation Storm Shelters and Their Operational Evaluation

Over the past three years NASA has been studying the operational effectiveness and astronaut protection efficacy of numerous radiation protection shelters for use in space exploration activities outside of earth's magnetosphere. The work presented was part of NASA's Advanced Exploration Systems (AES) RadWorks Storm Shelter project. This paper is a summary of the concept development activities of this third year. Fabricated items were integrated into mock up deep space habitat vehicle sections for operational evaluations. Two full scale human-in-loop simulations were designed, fabricated, and implemented through an Institutional Review Board approved solicited participant assessment process. Fabricated items are described, along with usage scenarios of two protection approaches. Existing ISS type logistics along with proposed variations of those logistics were used. Preliminary Discrete Event Simulation (DES) work is noted to be useful in quantifying and documenting operational performance measures for the two primary shelter methods, including some characterization of radiation dose accumulation over a mission timeline. The project also performed correlation analyses between effective radiation dose and the Risk of Exposure Induced Death (REID) to show that concept level work may be able to include such a performance metric in early stages of mission scenario habitat design trade space investigation.

Cerro, Jeffrey A.↗

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Integrated Demand Management↗

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↗

An Evaluation of Operational Airspace Sectorization Integrated System (OASIS) Advisory Tool

In January 2013, a human-in-the-loop evaluation of the Operational Airspace Sectorization Integrated System (OASIS) was conducted in the Airspace Operations Laboratory of the Human Systems Integration Division (Code TH) in conjunction with the Aviation Systems Division (Code AF). The development of OASIS is a major activity of the Dynamic Airspace Configuration (DAC) research focus area within the Aeronautics Research Mission Directorate (ARMD) Airspace Systems Program. OASIS is an advisory tool to assist Federal Aviation Administration (FAA) En Route Area Supervisors in their planning of sector combinedecombine operations as well as opening closing of Data-side (D-side) control positions. These advisory solutions are tailored to the predicted traffic demand over the next few hours. During the experiment, eight retired FAA personnel served as participants for a part-task evaluation of OASIS functionality, covering the user interface as well as the underlying algorithm. Participants gave positive feedback on both the user interface and the algorithm solutions for airspace configuration, including an excellent average rating of 94 on the tool usability scales. They also suggested various enhancements to the OASIS tool, which will be incorporated into the next tool development cycle for the full-scale human-in-the-loop evaluation to be conducted later this year.

decision support tools↗