SEARCH · Search NASA

Results for “scenario framework”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.

UAM↗

NASA NTRSDate not supplied

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Aircraft Mobility↗

NASA NTRSDate not supplied

The Inspectability Metric: A Formalized System Of Measurement Enabling The Design For Inspection Framework

Nondestructive evaluation (NDE) engineers are often confronted with structural design choices that present challenges to meeting inspection requirements. These challenges, at best, increase the resources needed to design an inspection solution and, at worst, require resource intensive redesign of the structure. If the inspectability of the structure can be determined early in the design cycle, these challenging inspection scenarios can be avoided. The emergence of additive manufacturing has further compounded this problem by enabling the creation of highly optimized structures with no regard to inspection constraints. Design for inspection (DFI) offers a framework to integrate nondestructive evaluation (NDE) into the design process to alleviate the mechanisms that produce uninspectable designs. DFI is the concept of including inspectability in a multi-objective optimization framework so that it can be considered in parallel to other metrics such as mass and manufacturability. This allows rapid evaluation of the trade-off between design metrics to find solutions that meet the inspection needs of a particular material system, structural concept, or vehicle program. To enable DFI, there must be a system by which the inspectability of a structure can be measured. This system must be agile to produce results quickly, it must be versatile to work with the type of incomplete information one would encounter early in the design process (such as lack of inspection requirements), and it must be delivered in a form that is easily understood by designers. To meet this need, this presentation introduces the novel inspectability metric as a system to measure inspectability. The inspectability metric is a standardized, automation friendly procedure that uses simulations to determine inspectability. Along with guidelines to properly process designs and integrate with existing workflows, the inspectability metric provides a suite of simulation tests to interrogate the ability to find defects and the sensitivity to variability. The testing rubric is designed to maximize the coverage of the parameter space while minimizing the number of simulations needed. The inspectability metric has been in development in collaboration with industry partners to ensure compatibility with modern simulation tools and aerospace design workflows. In this study, we will demonstrate how the inspectability metric is able to determine the inspectability of multiple types of structures, including aerospace composites and additively manufactured parts. We will then show how the inspectability score can be plugged into existing design optimization tasks, such as structural sizing algorithms or design for manufacturing (DFM) frameworks.

Design for inspection↗

NASA NTRS2023

Distributed Quantum Processing via Integrated Regional Quantum Networks Using Free-Space Optical Links

The landscape for quantum computing is rapidly evolving with the development of quantum computers and the emergence of future science enabling applications being pursued in many areas, such as distributed quantum computing, hybrid computing scenarios that require cooperatively networked quantum and classical computing assets and more. Quantum networking is also advancing with multiple regional quantum networks and testbeds maturing across the nation. These quantum networking testbeds typically include multiple access points with a heterogeneous mixture of capabilities interconnected by fiber spanning anywhere from tens to hundreds of kilometers; many such networks incorporate a classical networking framework. Alongside these connectivity advancements in the infrastructure, there is quantum sensing device and component technology maturation that is serving to expand the body of quantum networking scenarios that are presently possible and redefining the quantum- enabled future. Bridging the present collective progress in quantum computing and quantum networking will enable the next era of purposeful advancements for national priority use-cases for the benefit of science. One such use-case is enabling future quantum computing applications via integrated regional quantum networking infrastructure in neighboring locations like New York and Maryland, both states are home to robust classical and quantum networking capabilities. To enable near-term distributed quantum computing applications via the practical integration of regional quantum networking infrastructure, free-space optical links via satellite communications will be essential to avoid the exponential loss commonly observed with fiber implementations. There is both an urgent need and a practical justification for pursuing such space-based integration scope now.

Harry Shaw↗

NASA NTRS2024

Revisiting High-Energy Polarization from Leptonic and Hadronic Blazar Scenarios

X-ray and MeV polarization can be powerful diagnostics for leptonic and hadronic blazar models. Previous predictions are mostly based on a one-zone framework. However, recent IXPE observations of Mrk 421 and 501 strongly favor a multizone framework. Thus, the leptonic and hadronic polarization predictions need to be revisited. Here we identify two generic radiation transfer effects, namely, double depolarization and energy stratification, that can have an impact on the leptonic and hadronic polarization. We show how they are generalized from previously known multizone effects of the primary electron synchrotron radiation. Under our generic multizone model, the leptonic polarization degree is expected to be much lower than the one-zone prediction, unlikely detectable in most cases. The hadronic polarization degree can reach a value as high as the primary electron synchrotron polarization during simultaneous multiwavelength flares, consistent with the one-zone prediction. Therefore, IXPE and future X-ray and MeV polarimeters such as eXTP, COSI, and AMEGO-X, have good chances to detect hadronic polarization during flares. However, the hadronic polarization cannot be well constrained during the quiescent state. Nonetheless, if some blazar jets possess relatively stable large-scale magnetic structures, as suggested by radio observations, a nontrivial polarization degree may show up for the hadronic model after a very long exposure time (≳1 yr).

Haocheng Zhang↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations Using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗

NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations using Random Finite Sets

Schlenker, Lauren↗

NASA NTRS2012

NASA's Desert RATS Science Backroom: Remotely Supporting Planetary Exploration

NASA's Desert Research and Technology Studies (Desert RATS) is a multi-year series of tests designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable. In recent years, a D-RATS science backroom has conducted science operations and tested specific operational approaches. Approaches from the Apollo, Mars Exploration Rovers and Phoenix missions were merged to become the baseline for these tests. In 2010, six days of lunar-analog traverse operations were conducted during each week of the 2-week test, with three traverse days each week conducted with voice and data communications continuously available, and three traverse days conducted with only two 1-hour communications periods per day. In 2011, a variety of exploration science scenarios that tested operations for a near-earth asteroid using several small exploration vehicles and a single habitat. Communications between the ground and the crew in the field used a 50-second one-way delay, while communications between crewmembers in the exploration vehicles and the habitat were instantaneous. Within these frameworks, the team evaluated integrated science operations management using real-time science operations to oversee daily crew activities, and strategic level evaluations of science data and daily traverse results. Exploration scenarios for Mars may include architectural similarities such as crew in a habitat communicating with crew in a vehicle, but significantly more autonomy will have to be given to the crew rather than step-by-step interaction with a science backroom on Earth.

Cohen, Barbara A.↗

NASA NTRSDate not supplied

A New Era of H-O-C-S Magma Solubility Modeling: Better, Faster, Stronger

H 2 O, CO 2 , and S are the most abundant volatiles in magmatic systems and are critical to understanding magma storage, phase equilibria, and volcanic eruptions. Models that consider all three of these components, however, may not allow for critical examination and adjustment of assumptions underlying the model, or provide benchmark testing or extensible interfaces. Thus, understanding why models produce different results can be challenging. We have gathered authors of established (D-Compress) and recent (VolFe, EVo, Sulfur_X, MAGEC) H-O-C-S volatile solubility models to work together to understand how and why our models diverge. We present a series of benchmark basalt degassing scenarios revealing that often understated model assumptions such as fO 2 buffer equations, fO 2 -Fe 3+ /ΣFe relationships, and even major element normalization routines have outsized effects on model results. All models consider S 2- and S 6+ melt species but with different approaches to sulfate/sulfide capacities, partition coefficients, and species fugacities, leading to divergence in the evolution of modeled gas compositions, melt S and Fe speciation, and fO 2 , with the extent of divergence depending on melt composition. Such scenarios enable meaningful intercomparison of existing models and lay the groundwork for a user-friendly yet powerful solubility modeling framework. Given our wealth of existing solubility literature, we suggest that the field of magmatic volatiles should focus now on the creation of modern tools and the modular implementation of existing model equations or methods, and that the evaluation of code usability, transparency, and benchmarking should be codified pillars of the peer-review process. As an example of such an endeavor, we present early work coupling these sulfur solubility models with VESIcal, an extensible and rigorously tested python library containing seven existing H 2 O-CO 2 solubility models. VESIcal includes the ability to extract, edit, and even interchange assumptions underlying any model. For example, users may combine or swap separately published H 2 O, CO 2 , and S models, as well as underlying model choices, such as Equations of State and redox models.

volatiles in magmas↗

NASA NTRS2022

Robust Controller Synthesis for Vision-based Spacecraft Guidance and Control

This work develops a method for Robust Controller for Vision-based Spacecraft (RCVS) guidance and control, integral to the robust autonomy framework for multi-spacecraft for- mation control and reconfiguration applications. The method is built around the use of a photo-realistic simulator, where a camera is deployed on a tracking spacecraft (ego) in order to observe an uncontrolled spacecraft (target) in a Low Earth Orbit (LEO). In this direction, the proposed approach performs the relative state (attitude and position) estimation of the target spacecraft using Convolutional Neural Network (CNN). The state estimation error is then modeled and the corresponding error-bounds are obtained around a nominal trajectory of the ego and target spacecraft. Next, this work proposes a linear matrix inequalities (LMIs) based approach to controller synthesis, guaranteed to be robust against both model uncertainties and measurement errors, resulting from vision-based estimation. This controller is comprised of two distinct components, one synthesized based on the nominal trajectory, while the “robust” component corrects for deviations from the nominal trajectory. Finally, a tracking scenario that directly utilize the image data for spacecraft guidance and control, is presented to showcase the performance of the proposed robust autonomy framework.

Rahmani, Amir↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

NASA NTRSDate not supplied

Emulated Spacecraft Communication Testbed for Evaluating Cognitive Networking Technology

The ability to emulate the full space protocol stack is an essential aspect required to evaluate and mature cognitive communication capabilities. The interaction between the physical layer and network layers is key to developing network optimizations for a dynamic and complex environment. We present a laboratory testbed for the evaluation of cognitive radio and networking techniques applied to space communications. The testbed is a high fidelity, flight-like hardware testbed consisting of software-defined radios, channel emulators, modems, and orbital analysis and scheduling software. The testbed uses RF links with signal quality, propagation delay, and Doppler effects driven by orbital mechanics simulations of emulated spacecraft. Our framework enables control of link bidirectionality, data rates, and interference sources. In addition to hardware radio nodes, the testbed can incorporate virtualized emulated nodes for larger and more challenging network scenarios. Our approach to a cognitive communication system uses delay tolerant networking (DTN) to mitigate the challenges of the space environment. While many DTN networks use only preplanned schedules, our system uses User-Initiated Service (UIS) to dynamically schedule service providers. Software-defined radio allows the system to adapt to a variety of service providers. Integration of DTN, UIS, and software-defined radio technologies provides a framework for the implementation of a cognitive communication system. This paper describes the testbed capabilities, network emulation approach, component integration, and initial end-to-end testing results.

cognitive radio↗

NASA NTRS2006

Deep Space Network and Lunar Network Communication Coverage of the Moon

In this article, we describe the communication coverage analysis for the lunar network and the Earth ground stations. The first part of this article focuses on the direct communication coverage of the Moon from the Earth's ground stations. In particular, we assess the coverage performance of the Moon based on the existing Deep Space Network (DSN) antennas and the complimentary coverage of other potential stations at Hartebeesthoek, South Africa and at Santiago, Chile. We also address the coverage sensitivity based on different DSN antenna scenarios and their capability to provide single and redundant coverage of the Moon. The second part of this article focuses on the framework of the constrained optimization scheme to seek a stable constellation six relay satellites in two planes that not only can provide continuous communication coverage to any users on the Moon surface, but can also deliver data throughput in a highly efficient manner.

lunar network↗

NASA NTRS2013

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle.

Verification and Validation↗

NASA NTRS2014

Demonstration of Prognostics-Enabled Decision Making Algorithms on a Hardware Mobile Robot Test Platform

Prognostics-enabled Decision Making (PDM) is an emerging research area that aims to integrate prognostic health information and knowledge about the future operating conditions into the process of selecting subsequent actions for the system. Previous work developing and testing PDM algorithms has been done in simulation; this paper describes the effort leading to a successful demonstration of PDM algorithms on a hardware mobile robot platform. The hardware platform, based on the K11 planetary rover prototype, was modified to allow injection of selected fault modes related to the rover’s electrical power subsystem. The PDM algorithms were adapted to the hardware platform, including development of a software module framework, a new route planner, and modifications to increase the algorithms’ robustness to sensor noise and system timing issues. A set of test scenarios was chosen to demonstrate the algorithms’ capabilities. The modifications to run with a hardware platform, the test scenarios, and the test results are described in detail. The results show a successful use of PDM algorithms on a hardware test platform to optimize mission planning in the presence of electrical system faults.

Prognosis↗

NASA NTRS2014

Upset Recovery Human Factors

Accident and incident analyses as well as industry group concerns and recommendations have justified taking a second look at proficiency standards related to upset recovery training and performance. Quite a number of factors and theories have been suggested-- leading the NASA Aviation Safety Program to reconsider manual handling skills in highly automated aircraft particularly in conditions that can potentially lead to Loss of Control events. Our team of Subject Matter Experts (SMEs) first identified 76 Basic Recovery Skills that were important for effective crew response under five different anomaly conditions. In addition to manual handling skills, the skill set included knowledge and cognitive skills, as well as decision making and management skills. Advanced Recovery Skills were identified by combining skills, integrating with crew resource management skills, and developing heuristics for decision making.Using the Advanced Recovery Skill set, the SMEs then developed a generic process flow starting from the problem discovery phase (e.g., identifying an anomaly) through the decision making and management phase (e.g., assessing response options), through the recovery phase (e.g., controlling the aircraft). The generic process flow was refined by testing it against six additional scenarios. The next part of the project was to develop an approach for assessing and revising a generic training curriculum (we used an operators Advanced Qualification Program (AQP) as a framework). Although many of the Basic and Advanced Recovery Skills could be found in the Job Task Listing, they were not always structured or combined in the most effective way. Recommendations were developed for assessing relevant aspects of the Job Task Listing and Continuing Qualification curriculum so that the more comprehensive set of Upset Recovery skillsincluding Human Factors--could be trained and assessed in the most appropriate and effective context. The existing AQP methodology provides a natural way to insert targeted Upset Recovery skills into its system of proficiency objectives, training devices, training activities, and ultimately, into the event sets of a simulator training scenario.

AQP training↗

NASA NTRSDate not supplied

SIRIUS: Simulation Infrastructure for Research on Interoperating Unmanned Systems

This paper presents the Simulation Infrastructure for Research on Interoperating Unmanned Systems (SIRIUS), a research framework for simulation and analysis of future conceptual Urban Air Mobility (UAM) operations. SIRIUS is being developed under the auspices of the NASA Air Traffic Management eXploration project, UAM subproject (ATM-X UAM). SIRIUS provides an intuitive, highly configurable graphical user interface to design complex traffic scenarios and airspace configurations representative of conceptual UAM operations. Aircraft simulated with SIRIUS can be equipped with flight-tested capabilities for detect and avoid (DAA), geofencing, distributed merging and spacing, path conformance, and path planning while executing time-constrained, 4D trajectories generated by a UAM ground operations system. Central to the design of the SIRIUS simulation framework is the capability to evaluate the integration and interoperability of ground-based separation services (e.g., strategic separation) with extended DAA functionality (e.g., path monitoring, separation provision, merging and spacing, etc.) The simulation environment also supports modelling of wind, navigation, and sensor uncertainties, as well as communication delays. SIRIUS enables distributed simulation of large-scale scenarios. An interactive graphical analysis capability helps isolate, visualize, and compare relevant vehicle state data and widely used measures of performance metrics across multiple scenarios.

Andrew Peters↗

NASA NTRS1989

Power from space for use on earth: An emerging global option

The concept of the Earth as a closed ecological system is addressed from the point of view of the availability and use of energy from space and its potential influence on the economies of both developed and developing countries. The results of past studies of the solar power satellite (SPS) are reviewed, and the current international activities exploring various aspects of an SPS are mentioned. The functions of an SPS, including collection of solar energy in orbit, conversion to an intermediate form of energy, transmission of energy from orbit to Earth, and conversion to useful energy in the most appropriate form are discussed. Directions for future developments are addressed including a suggested planning framework. Salient aspects of SPS technologies are presented, and the potential benefits of the uses of lunar materials for the SPS construction are outlined. Scenarios within the context of international participation in a global SPS system are presented. The conclusion is drawn that an SPS system is one of the few promising, globally applicable power generation options that has the potential to meet energy demands in the 21st Century and to achieve the inevitable transition to inexhaustible and renewable energy sources.

Glaser, Peter E.↗