Results for “CaSe” — Page 13

NASA NTRS2017

A CubeSat-Payload Radiation-Reliability Assurance Case using Goal Structuring Notation

CubeSats have become an attractive platform for universities, industry, and government space missions because they are cheaper and quicker to develop than full-scale satellites. One way CubeSats keep costs low is by using commercial off-the-shelf parts (COTS) instead of space-qualified parts. Space-qualified parts are often costlier, larger, and consume more power than their commercial counterparts precluding their use within the CubeSat form-factor. Given typical power budgets, monetary budgets, and timelines for CubeSat missions, conventional radiation hardness assurance, like the use of space-qualified parts and radiation testing campaigns of COTS parts, is not practical. Instead, a system-level approach to radiation effects mitigation is needed. In this paper an assurance case for a system-level approach to mitigate radiation effects of a CubeSat science experiment is expressed using Goal Structuring Notation (GSN), a graphical argument standard. The case specifically looks at three main mitigation strategies for the radiation environment: total ionizing dose (TID) screening of parts, detection and recovery from single-event latch-ups (SEL) and single-event functional interrupts (SEFI). The graphical assurance case presented makes a qualitative argument for the radiation reliability of the CubeSat experiment using part and system-level mitigation strategies.

COTS↗

NASA NTRS2018

A Hybrid Method of Assurance Cases and Testing for Improved Confidence in Autonomous Space Systems

Autonomous systems react intelligently to their environments, making them capable of handling many possible conditions, but challenging to test. We are investigating a new test development method that aims to maximize the confidence to be achieved by combining Assurance Cases with High Throughput Testing (HTT). Assurance Cases, developed for safety-critical systems, are a rigorous argument that the system satisfies a property (e.g., the Mars rover will not tip over during a traverse). They integrate testing, analysis, and environmental and operational assumptions, from which the set of conditions that testing must cover is determined. In our method, information from the Assurance Case is used to determine the test coverage needed, and then input to HTT to generate the minimal test suites needed to provide that coverage.

Huntsberger, Terry↗

NASA NTRS2021

Numerical Simulation of Pressure-induced Separation of Turbulent Flat-plate Boundary Layers: Definition and Overview of New Cases with Suction-only Transpiration and a Step in Reynolds Number

Results from two new direct numerical simulations (DNSs) are added to the database described in Coleman, Rumsey & Spalart (2018) (henceforth CRS18), and available at the NASA TMR website (https://turbmodels.larc.nasa.gov). The new flows, Cases D and E, are similar to the earlier ones (Cases A–C) in that a transpiration profile above a flat plate creates a prolonged adverse pressure gradient (APG) that drives a canonical turbulent zero-pressure-gradient (ZPG), flat-plate boundary layer towards separation; they differ in that for the new cases (1) the APG is not followed by a favorable gradient (FPG), since only suction transpiration is employed, and (2) the mean shear stress does not cross zero, so that the width of the mean bubble, strictly defined, is essentially zero. However, the probability of reversed skin friction exceeds 49%. The motivation was to produce a flow that is more akin to technological flows, including shock-boundary-layer interaction, with a gradual turbulence-controlled recovery. One of the new simulations is also at a significantly higher Reynolds number than the earlier flows.

Turbulence↗

NASA NTRSDate not supplied

Identifying Common Use Cases across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers

NASA’s Extensible Traffic Management (xTM) builds on the foundation and the architecture of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept and extends it broadly to other domains, such as Advanced / Urban Air Mobility (AAM/UAM) and Upper Class E Traffic Management (ETM). These xTM concepts assume the ability to fly in airspace that is authorized to operate solely under xTM services and mostly without any air traffic control (ATC) support. However, they also assume circumstances in which the xTM vehicles would need to operate in conventional ATC-managed airspace, both during nominal and off-nominal scenarios. Due to the vast differences in the xTM vehicle performances and missions, there is a concern that ATC may have difficulty in safely managing the xTM traffic and providing appropriate services to all vehicles, unless a consistent set of roles, procedures, and data exchange requirements are defined across the diverse set of xTM vehicle operations. In this paper, we describe a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions, and we propose to categorize these use cases across xTM domains based on common trigger events. Organizing the use cases from the perspective of ATC roles per each trigger event is expected to provide the first step in discovering common procedures and data requirements across xTM domains that could help ease the controllers’ cognitive task load and allow them to manage these interactions more safely.

Extensible Traffic Management (xTM)↗

NASA NTRSDate not supplied

DAA Use Case for Auto Cargo m:N Operations

A detect and avoid use-case was developed to highlight detect and avoid issues associated with m:N operations in the auto cargo domain. This work is being done in conjunction with industry partners and developed for the Operational Scenario and Environmental Description (OSED) for RTCA SC-228. The detect and avoid function is critical, required technology for unmanned aircraft to operation in the national airspace. RTCA SC-228 has published MOPS (phase 1 & 2) detailing the requirements and methods of compliance. This work will help address additional operational aspects of how/when DAA will be employed by unmanned systems. Specifically, this work focuses on “auto cargo” operations. Auto cargo, in this context, refers to regularly scheduled cargo-size aircraft that are flown remotely. The Remote Pilot In Command (RPIC), in this case, is responsible for multiple aircraft, flown simultaneously. The use-case details the use of DAA in this context, the potential issues and gaps that exist.

multi-vehicle control↗

NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗

NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗

NASA NTRS2022

NASA's Responsible AI Use Cases

This submission consists of NASA's Responsible Artificial Intelligence (RAI) Use Cases. These RAI Use Cases are to be made public, pursuant to the Presidential Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government. They were collected from NASA's practicing AI research community and cover the gamut of NASA's AI activities. These Use Cases will be updated annually as required by the Executive Order. The information included consists of the NASA Center, a summary of the goal, the AI techniques being applied, information on training data, and information on source code.

Artificial Intelligence↗

NASA NTRSDate not supplied

FUN3D Analyses of the 5th AIAA Propulsion Aerodynamics Workshop Inlet Test Case

This work presents the results of FUN3D analyses that were performed for the 5th AIAA Propulsion Aerodynamics Workshop. The workshop was separated into two sections that focused on inlet and nozzle flows. This paper focuses on the inlet section of the workshop, which considered an axisymmetric inlet in close-proximity to the ground and subjected to a crosswind. Four levels of grid refinement were provided by the workshop committee. Participants were asked to perform simulations for three crosswind velocities on a minimum of three levels of grid refinement, for a total of nine required cases. This work employed an updated set of grids provided by the committee after completion of the workshop based on feedback from participants. The updated grids featured a larger computational domain and increased refinement near the ground vortex region. This work employed the three coarsest grid levels from the updated grid set. Note that an additional extension downstream of the inlet was added to the provided grids for this work to mitigate observed convergence issues. Additionally, a limited turbulence model study was performed for the highest value of crosswind velocity and the finest grid. The results show that grid convergence was only achieved for the case with the lowest value of crosswind velocity. However, the results were generally observed to improve, relative to the experimental data, with increasing grid refinement. The FUN3D predictions were observed to agree qualitatively with the provided experimental data. However, FUN3D exhibited a tendency to underpredict the minimum value of the radially averaged total pressure at the Aerodynamic Interface Plane, which is consistent with the general findings from the workshop. Overall, FUN3D was found to perform well relative to its peers for the PAW5 workshop inlet test case.

PAI↗

NASA NTRSDate not supplied

FUN3D Analyses of the 5th AIAA Propulsion Aerodynamics Workshop Inlet Test Case

This work presents the results of FUN3D analyses that were performed for the 5th AIAA Propulsion Aerodynamics Workshop. The workshop was separated into two sections that focused on inlet and nozzle flows. This paper focuses on the inlet section of the workshop, which considered an axisymmetric inlet in close-proximity to the ground and subjected to a crosswind. Four levels of grid refinement were provided by the workshop committee. Participants were asked to perform simulations for three crosswind velocities on a minimum of three levels of grid refinement, for a total of nine required cases. This work employed an updated set of grids provided by the committee after completion of the workshop based on feedback from participants. The updated grids featured a larger computational domain and increased refinement near the ground vortex region. This work employed the three coarsest grid levels from the updated grid set. Note that an additional extension downstream of the inlet was added to the provided grids for this work to mitigate observed convergence issues. Additionally, a limited turbulence model study was performed for the highest value of crosswind velocity and the finest grid. The results show that grid convergence was only achieved for the case with the lowest value of crosswind velocity. However, the results were generally observed to improve, relative to the experimental data, with increasing grid refinement. The FUN3D predictions were observed to agree qualitatively with the provided experimental data. However, FUN3D exhibited a tendency to underpredict the minimum value of the radially averaged total pressure at the Aerodynamic Interface Plane, which is consistent with the general findings from the workshop. Overall, FUN3D was found to perform well relative to its peers for the PAW5 workshop inlet test case.

PAI↗

NASA NTRS2023

NASA's Responsible AI Use Cases

This submission consists of summary use cases for NASA's Responsible Artificial Intelligence (RAI). These RAI Use Cases are to be made public, pursuant to the Presidential Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government. They were collected from NASA's practicing AI research community and cover the gamut of NASA's AI activities. These Use Cases will be updated annually as required by the Executive Order. The information included consists of the NASA Center, a summary of the goal, the AI techniques being applied, information on training data, and information on source code.

Artificial Intelligence↗

NASA NTRS2023

Wildfire-fighting Use Case Requirements to Monitor

In this technical report, we provide requirements for a wildfire-fighting use-case, towards the Safety Demonstrator 1. The use case will incorporate ground and airborne assets operating in a coordinated fashion, and will comprise five activities, from detection to the execution of the initial attack. Depending on the activity and the data involved, the requirements identified may be non-probabilistic or probabilistic. In both cases, we first identify some of the requirements we wish to monitor, and then present a formalization using the language of requirements of the NASA requirements elicitation tool FRET. To formalize probabilistic requirements, we use a novel extension to FRET’s requirements language that incorporates notions of probability, and discuss how requirements can be translated into existing probabilistic temporal logics like PCTL. We exemplify how some of the requirements presented can be monitored using the existing tools Ogma and Copilot. We close with a summary and future directions.

Requirements↗

NASA NTRS2022

Measuring, mapping, and anticipating climate gentrification in Florida: Miami and Tampa case studies

This article introduces an experimental methodology to identify proxy indicators that are conceptually consistent with the processes of Climate Gentrification (“CG”), in which a change in demand preferences among consumers and investors drives the increased consumption for real estate, in part, on lower measures of physical risk from climate change. Evaluated through case studies in the state of Florida, this article builds on the integration of multiple datasets concerning rental properties, evictions, and socioeconomic data, as well as environmental risk indices to build a Climate Gentrification Risk Index (CGRI). In the Miami case study, we find that the CGRI identifies a hotly contested neighborhood that is already known to be in a state of transition consistent with the processes of CG. In the Tampa case, the index highlights a district that exhibits strong metrics for the future accelerated occurrence of CG. Our findings suggest that transitional land uses and flexible zoning in low-exposure areas are key elements for attracting new development consistent with CG and offer insight into the challenges that local governments face understanding the types and rates of change that may be catalyzed in the broader urban processes of public and private sector climate adaptation in the built environment.

Climate change↗

NASA NTRSDate not supplied

Heated Supersonic Axisymmetric Jet Cases for the NASA Turbulence Modeling Resource

This paper will describe three new supersonic jet cases for the NASA Turbulence Modeling Resource (TMR). These cases were taken from the 6th AIAA Propulsion Aerodynamics Workshop (PAW) nozzle test problem, which utilized data taken at NASA GRC consisting of non-intrusive measurements of jet plume velocities and temperatures, including both mean values and turbulence statistics. The three jet cases all used a Mach 1.63 axisymmetric nozzle: A heated jet for each at on-design conditions, a temperature-matched on-design condition at Mach 1.63, and an off-design heated condition for the Mach 1.63 nozzle. Computational fluid dynamics (CFD) solutions are obtained using three established Reynolds-averaged Navier-Stokes (RANS) codes: Wind-US, FUN3D, and Vulcan, all using the Menter Shear Stress Transport (SST) k-ω turbulence model. The NASA TMR requires at least two CFD codes yielding essentially identical results to certify that the approaches are verified, that is - providing solutions that may not necessarily provide close comparisons with experimental data, but solve the posed CFD equations as intended.

nozzle↗

NASA NTRS2024

NASA Engineering and Safety Center Technical Bulletin No. 24-04: 6DOF Check Cases

In 2015, the NESC released benchmark Earth-based check-cases for well specified, rigid-body, six-degree-of-freedom (6DOF) aero/spacecraft models to promote consistent and accurate flight simulations across multiple Agency tools and facilities. Recently, the NESC expanded upon that effort to add Lunar-based check-cases to support new lunar exploration initiatives. This study produced a smaller, focused set of cases that exercise new and unique features of missions in the lunar environment in comparison with 8 high-fidelity NASA simulation tools and provides a measure of validation for simulations supporting Human Landing Systems.

Flight Mechanics↗

NASA NTRS2024

Expansion of Check-Cases for 6DOF Simulation: Appendix A

This is the Appendix containing figures of simulation output data plots for comparison from the assessment, “Expansion of Check-Cases for 6DOF Simulation”. This effort expands upon a previous NASA activity that developed flight simulation benchmark check-cases to include new check-cases for the Cislunar domain, comparing multiple NASA simulation tools. The results of this effort describe the benefits of standardizing inputs, simulation comparisons and describe an interactive website that enables comparison of externally provided simulation data. Participating simulations improved their software and identified implementation errors. This activity elevated simulation credibility and provided a measure of validation for the simulations actively in use for NASA’s Human Landing Systems (HLS).

Modeling↗

NASA NTRSDate not supplied

A Case Study of AI-assisted Creation of a Thermodynamics Model of Precipitation Formation During Rapid Depressurization of a Vented Container

Precipitation may form in humid containers undergoing rapid depressurization. This precipitation may be liquid, i.e. fog, if the dewpoint is crossed above the freezing point of water, or direct snow crystallization if the dewpoint is crossed below the freezing point. Accurate modeling of this effect is potentially important for rapidly ascending vented containers in aircraft, spacecraft, and launch vehicles, as well as rapidly depressurizing vacuum chambers. A transient thermodynamics model of precipitation formation during the rapid depressurization of a container was developed in python. The model is written for a generic container and includes an optional water pool and water vapor source. Details of the model and results from several example cases spanning the full capabilities of the model, including a validation case, will be presented. Although the model is not novel, in contrast to prior works, this one was treated as a case study of the assistance of AI Large Language Models (LLMs) to create physical models. Impressions, performance, time, and cost of using AI for this task will be discussed.

precipitation↗

NASA NTRS2013

A Formal Basis for Safety Case Patterns

By capturing common structures of successful arguments, safety case patterns provide an approach for reusing strategies for reasoning about safety. In the current state of the practice, patterns exist as descriptive specifications with informal semantics, which not only offer little opportunity for more sophisticated usage such as automated instantiation, composition and manipulation, but also impede standardization efforts and tool interoperability. To address these concerns, this paper gives (i) a formal definition for safety case patterns, clarifying both restrictions on the usage of multiplicity and well-founded recursion in structural abstraction, (ii) formal semantics to patterns, and (iii) a generic data model and algorithm for pattern instantiation. We illustrate our contributions by application to a new pattern, the requirements breakdown pattern, which builds upon our previous work

Formal Methods↗