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At least 163 records · Page 9

Fe(3): An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Collision Avoidance↗

Fe3: An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Trajectory Modeling↗

Automated Contingency Management for Water Recycling System

To enable effective management, planning, and operations for future missions that involve a crewed space habitat, operational support must be migrated from Earth to the habitat. Intelligent System Health Management technologies (ISHM) promise to enable the future space habitats to increase the safety and mission success while minimizing operational risks. In this paper, Water Recycling System (WRS) deployed at NASA Ames Research Center's Sustainability Base is used for verification and validation of the proposed solution. Our work includes the development of the WRS simulation model based on its dynamic physical characteristics and the design of Automatic Contingency Management (ACM) framework that integrates fault diagnosis and optimization. In WRS modeling, a nominal model with fault injectors is developed. Fault detection and isolation techniques are then developed for isolating causes and identifying the severity of the faults. Dynamic Programming (DP) based fault mitigation strategies are designed to accommodate the faults in the system. A series of simulations are presented with different fault modes and the results indicate that the proposed ACM system can alleviate the fault in the WRS optimally regarding energy consumption and effects of the fault.

Systems Health Management↗

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗

Airborne Spacing for Terminal Arrival Routes (ASTAR) Proof-of-Concept Flight Test

The Airborne Spacing for Terminal Arrival Routes (ASTAR) Flight Test was conducted by the NASA Air Traffic Management Technology Demonstration – 1 (ATD- 1) project to demonstrate the use of NASA’s ASTAR algorithm beyond a simulated environment and assess the operational risks of performing a multi-aircraft flight test of Flight-deck Interval Management (FIM). Utilizing contemporary tools of the Federal Aviation Administration’s Next Generation Air Transportation System (NextGen) such as ADS-B, the ASTAR algorithm calculated speeds that the flight crew flew to achieve a precise spacing interval behind another aircraft at the final approach fix. Airspeed commands issued by the algorithm were flown by the flight crew of the FIM-equipped aircraft to achieve or maintain an assigned spacing goal from a target vehicle. The ASTAR algorithm was integrated with the Boeing supplied B-787 ecoDemonstrator aircraft, and five flight trials were conducted as a joint effort between NASA and Boeing on December 12, 2014. Initial results indicated arrival times within several seconds of accuracy of the planned termination point between two aircraft performing FIM in a real world environment. This flight test opened the way for the much more expansive ATD-1 Avionics Phase II flight test which occurred in early 2017. The flight trials under Phase II preceded further testing by the community in preparation for inclusion of the Interval Management concept as a part of the NextGen environment.

Roper, Roy D.↗

NASA Ames Thermophysics Ground Test Facilities Supporting Future Planetary Atmospheric Entry

A review of the current facility capabilities for testing Thermal Protection Systems and quantifying their entry environments at NASA Ames Research Center is presented based on the expected targets of interest to the Planetary Science and Astrobiology communities. While the operational capabilities of these facilities are generally considered sufficient for supporting future missions to targets of interest, expanded ground test capabilities such as larger sample sizes, flight-relevant gas mixtures, dusty environments, and flight-relevant shear/pressure combinations would reduce future entry vehicle design uncertainties and applied margins. These reduced uncertainties may translate into reduced entry vehicle masses, increased robustness, and decreased operational risks during entry phases for science missions. Expanded ground test capabilities would also offer the ability to study material failure modes in environments even more representative of flight than are currently achievable. A list of desired future test capabilities is presented along with suggestions of possible methods of achieving each. The main recommendation of this paper is the undertaking of a detailed study of the benefits and associated costs of each of these expanded capabilities to determine the best future path.

arc jet↗

Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding

As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk. Current spacecraft monitoring systems only target a subset of anomaly types and often require costly expert knowledge to develop and maintain due to challenges involving scale and complexity. We demonstrate the effectiveness of Long Short-Term Memory (LSTMs) networks, a type of Recurrent Neural Network (RNN), in overcoming these issues using expert-labeled telemetry anomaly data from the Soil Moisture Active Passive (SMAP) satellite and the Mars Science Laboratory (MSL) rover, Curiosity. We also propose a complementary unsupervised and nonparametric anomaly thresholding approach developed during a pilot implementation of an anomaly detection system for SMAP, and offer false positive mitigation strategies along with other key improvements and lessons learned during development.

Soderstrom, Tom↗

An Approach for Identifying IASMS Services, Functions, and Capabilities From Data Sources

Assuring safety in the NAS with the inclusion of new entrants that are part of Advanced Air Mobility (AAM) will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using semi-autonomous/autonomous vehicles. Overcoming these AAM safety assurance challenges is the focus of the In-time Aviation Safety Management System (IASMS). The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs)designed to manage operational risks, identify unknown risks, and inform system design to mitigate risk. This paper describes a broad approach for identifying SFCs involving technology trends in research, assessment of known and unknown risks in safety reports, and causal and contributing factors in aviation accidents and incidents. This approach leverages these sources to identify potential SFCs that enable the Monitor, Assess, and Mitigate (M-A-M)functionality that represents the enabling framework of the IASMS.

Kyle Ellis↗

Crewed Mars Mission Mode Options for Nuclear Electric/Chemical Hybrid Transportation System

NASA's Human Exploration and Operation Mission Directorate is continuing to study different concepts and options to field human Mars missions as part of NASA's Moon2Mars directive. For crewed missions to Mars, the transportation system sizing is highly dependent on the total mission duration, Mars orbit dwell time, mission concept of operations, and the chosen propulsion system. NASA has been investigating the use of low-thrust electric propulsion systems to augment high-thrust chemical propulsion system for crewed Mars mission to enable a more energy-efficient operations. Recent studies on these missions have focused on ``All-Up'' piloted mission modes in which the in-space transportation system for crew transit departs Earth with everything it needs for the roundtrip journey, with only the Mars landers and surface assets pre-deployed. This design choice was made to minimize the mission operation risk, as the crew could return safely to Earth in the event of a failure to rendezvous or other failure of any pre-deployed assets. As the Mars Architecture Team continues to investigate and understand the Mars mission trade space, alternate mission mode studies were conducted to understand their impact to the transportation system. These include pre-positioning return assets and discarding expended stages to reduce the overall system mass.

Patrick R Chai↗

An Ontological Approach to Integrate Commercial Space Operations with an In-time Aviation Safety Management System (IASMS)

The emergence of commercial space operations (CSO) is one of many Advanced Air Mobility domains that pose major challenges to in-time safety assurance because of the different architectures used by the operators and other agents. The National Academies recognized the need to improve integration of disparate architectures and recommended that an In-time Aviation Safety Management System(IASMS) be developed to provide seamless connectivity across interacting architectures and enable in-time safety assurance. An ontological approach to integrating CSO with IASMS involves in-time Services, Functions, and Capabilities design to manage operational risks and inform changes to design. The resulting integrated architecture provides a common basis for risk management and in-time safety assurance.

K Ellis↗

Fe3 Traffic Simulator Overview

NASA Ames developed a first of its kind air traffic simulation tool known as Flexible engine for Fast time evaluation of Flight environments (Fe3). The patent-pending technology is a robust simulation tool that provides the capability of statistically analyzing the high-density and low-altitude traffic system. With this capability, stakeholders can study the impacts of critical components (such as wind, surveillance, communication, collision, avoidance, traffic rules, energy consumption, etc.) in the low-altitude high-density traffic system, gain insights and help define requirements, policies, and protocols for a safe and efficient traffic system, and assess operational risks and optimize fight schedules.

Flexible engine for Fast time evaluation of Flight↗

A 1 MW Solar Electric and Chemical Propulsion Vehicle for Piloted Mars Opposition Class Missions

Previous investigations have extensively explored crew missions to and from Mars, with a prevailing approach termed the 'conjunction' class, necessitating an approximately 500-day stay at Mars for a cost-effective return. However, this configuration results in a mission duration exceeding 1000 days (roughly 3 years). In order to reduce crew health and surface operations risks, a shortened mission duration of 850 days is being explored by using a short ~30 day Mars surface stay and a ‘opposition’ class approach. A non-nuclear approach is possible by combining solar electric propulsion and a chemical stage. While past mission concepts for the conjunction missions also used solar electric propulsion they limited the SEP power to <700 kW. In order to achieve the 850 day round trip more SEP power is needed. A 1MW class SEP-Chem vehicle was found sufficient to perform the 850 day mission. The biggest challenge for the design will be the large, high power solar arrays, mainly from their deployment and stability. This work describes the design of the SEP-Chem vehicle, assembled in a Near Rectilinear Halo Orbit (NRHO) and employing super-heavy class and the Space Launch System (SLS) launchers.

SEP-Chem↗

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement↗

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗

Assessment, Planning, and Execution Considerations for Conjunction Risk Assessment and Mitigation Operations

An operational Conjunction Assessment Risk Analysis (CARA) concept is the real-time process of assessing risk posed by close approaches and reacting to those risks if necessary. The most effective way to completely mitigate conjunction risk is to perform an avoidance maneuver. The NASA Goddard Space Flight Center has implemented a routine CARA process since 2005. Over this period, considerable experience has been gained and many lessons have been learned. This paper identifies and presents these experiences as general concepts in the description of the Conjunction Assessment, Flight Dynamics, and Flight Operations methodologies and processes. These general concepts will be tied together and will be exemplified through a case study of an actual high risk conjunction event for the Aura mission.

Frigm, Ryan C.↗

A Risk Assessment Architecture for Enhanced Engine Operation

On very rare occasions, in-flight emergencies have occurred that required the pilot to utilize the aircraft's capabilities to the fullest extent possible, sometimes using actuators in ways for which they were not intended. For instance, when flight control has been lost due to damage to the hydraulic systems, pilots have had to use engine thrust to maneuver the plane to the ground and in for a landing. To assist the pilot in these situations, research is being performed to enhance the engine operation by making it more responsive or able to generate more thrust. Enabled by modification of the propulsion control, enhanced engine operation can increase the probability of a safe landing during an inflight emergency. However, enhanced engine operation introduces risk as the nominal control limits, such as those on shaft speed, temperature, and acceleration, are exceeded. Therefore, an on-line tool for quantifying this risk must be developed to ensure that the use of an enhanced control mode does not actually increase the overall danger to the aircraft. This paper describes an architecture for the implementation of this tool. It describes the type of data and algorithms required and the information flow, and how the risk based on engine component lifing and operability for enhanced operation is determined.

Litt, Jonathan S.↗

Evolution and Implementation of the NASA Robotic Conjunction Assessment Risk Analysis Concept of Operations

Reacting to potential on-orbit collision risk in an operational environment requires timely and accurate communication and exchange of data, information, and analysis to ensure informed decision-making for safety of flight and responsible use of the shared space environment. To accomplish this mission, it is imperative that all stakeholders effectively manage resources: devoting necessary and potentially intensive resource commitment to responding to high-risk conjunction events and preventing unnecessary expenditure of resources on events of low collision risk. After 10 years of operational experience, the NASA Robotic Conjunction Assessment Risk Analysis (CARA) is modifying its Concept of Operations (CONOPS) to ensure this alignment of collision risk and resource management. This evolution manifests itself in the approach to characterizing, reporting, and refining of collision risk. Implementation of this updated CONOPS is expected to have a demonstrated improvement on the efficacy of JSpOC, CARA, and owner/operator resources.

operations↗

Managing Risk for Cassini During Mission Operations and Data Analysis (MOandDA)

A Risk Management Process has been tailored for Cassini that not only satisfies the requirements of NASA and JPL, but also allows the Program to proactively identify and assess risks that threaten mission objectives. Cassini Risk Management is a team effort that involves both management and engineering staff. The process is managed and facilitated by the Mission Assurance Manager (MAM), but requires regular interactions with Program Staff and team members to instill the risk management philosophy into the day to day mission operations. While Risk Management is well defined for projects in the development phase, it is a relatively new concept for Mission Operations. The Cassini team has embraced this process and has begun using it in an effective, proactive manner, to ensure mission success. It is hoped that the Cassini Risk Management Process will form the basis by which risk management is conducted during MO&DA on future projects. proactive in identifying, assessing and mitigating risks before they become problems. Cost ehtiveness is achieved by: Comprehensively identifying risks Rapidly assessing which risks require the expenditure of pruject cewums Taking early actions to mitigate these risks Iterating the process frequently, to be responsive to the dynamic internal and external environments The Cassini Program has successfully implemented a Risk Management Process for mission operations, The initial SRL has been developed and input into he online tool. The Risk Management webbased system has been rolled out for use by the flight team and risk owners we working proactive in identifying, assessing and mitigating risks before they become problems. Cost ehtiveness is achieved by: Comprehensively identifying risks Rapidly assessing which risks require the expenditure of pruject cewums Taking early actions to mitigate these risks Iterating the process frequently, to be responsive to the dynamic internal and external environments The Cassini Program has successfully implemented a Risk Management Process for mission operations, The initial SRL has been developed and input into he online tool. The Risk Management webbased system has been rolled out for use by the flight team and risk owners we working put into place will become visible and will be illusmted in future papers.

risk management↗