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NASA NTRS2003

Methods Developed by the Tools for Engine Diagnostics Task to Monitor and Predict Rotor Damage in Real Time

Tools for Engine Diagnostics is a major task in the Propulsion System Health Management area of the Single Aircraft Accident Prevention project under NASA s Aviation Safety Program. The major goal of the Aviation Safety Program is to reduce fatal aircraft accidents by 80 percent within 10 years and by 90 percent within 25 years. The goal of the Propulsion System Health Management area is to eliminate propulsion system malfunctions as a primary or contributing factor to the cause of aircraft accidents. The purpose of Tools for Engine Diagnostics, a 2-yr-old task, is to establish and improve tools for engine diagnostics and prognostics that measure the deformation and damage of rotating engine components at the ground level and that perform intermittent or continuous monitoring on the engine wing. In this work, nondestructive-evaluation- (NDE-) based technology is combined with model-dependent disk spin experimental simulation systems, like finite element modeling (FEM) and modal norms, to monitor and predict rotor damage in real time. Fracture mechanics time-dependent fatigue crack growth and damage-mechanics-based life estimation are being developed, and their potential use investigated. In addition, wireless eddy current and advanced acoustics are being developed for on-wing and just-in-time NDE engine inspection to provide deeper access and higher sensitivity to extend on-wing capabilities and improve inspection readiness. In the long run, these methods could establish a base for prognostic sensing while an engine is running, without any overt actions, like inspections. This damage-detection strategy includes experimentally acquired vibration-, eddy-current- and capacitance-based displacement measurements and analytically computed FEM-, modal norms-, and conventional rotordynamics-based models of well-defined damages and critical mass imbalances in rotating disks and rotors.

Baaklini, George Y.↗

NASA NTRS2003

The X-Ray Baldwin Effect: Z = 2 Fe-K and Compton Humps as Ionized Disk Diagnostics

Work on this project is almost complete. A final trip to the XMM Survey Science Center at the University of Leicester is being undertaken to ensure that the with Prof. A. King on theoretical implications in the context of his super- Eddington wind model for AGNs, that has just been published on astro-ph. The wind model we developed has led to a paper being submitted to ApJ. The referee's response requires some care, and so the PI will be visiting Dr. Guido Risaliti, with whom he developed the code, at the Arcetri Observatory, Italy, during the above trip.

Mushotzky, Richard F.↗

NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗

NASA NTRSDate not supplied

Big-data Efficient Automated Science Transfer (BEAST): an open-source software architecture for arc jet data management, modeling, and automation

Data management↗

NASA NTRS2015

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE). an object-oriented toolkit for building distributed applications.

Testbed↗

NASA NTRS1989

Coherent Cerenkov radiation from the Spacelab 2 electron beam

The plasma environment of the Spacelab 2 mission was investigated through the deployment of the Plasma Diagnostics Package (PDP) by the Space Shuttle Orbiter and the Orbiter's ejection of a continuous 1-keV/50-mA electron beam along a field line. As the PDP flew by the beam, its plasma-wave instrument detected intense whistler-mode radiation originating from the beam. A detailed model has been developed of the coherent Cerenkov emission process, using a one-dimensional computer simulation of the beam to model the expected phase space structure of the electrons. The power calculated for the modeled 200-m beam segment can easily account for the measured whistler mode wave power.

Farrell, W. M.↗

NASA NTRS1999

The Density Matrix of H20 - N2 In the Coordinate Representation: A Monte Carlo Calculation of the Far-Wing Line Shape

The far-wing line shape theory within the binary collision and quasistatic framework has been developed using the coordinate representation. Within this formalism, the main computational task is the evaluation of multidimensional integrals whose variables are the orientational angles needed to specify the initial and final positions of the system during transition processes. Using standard methods, one is able to evaluate the 7-dimensional integrations required for linear molecular systems, or the 7-dimensional integrations for more complicated asymmetric-top (or symmetric-top) molecular systems whose interaction potential contains cyclic coordinates. In order to obviate this latter restriction on the form of the interaction potential, a Monte Carlo method is used to evaluate the 9-dimensional integrations required for systems consisting of one asymmetric-top (or symmetric-top) and one linear molecule, such as H20-N2. Combined with techniques developed previously to deal with sophisticated potential models, one is able to implement realistic potentials for these systems and derive accurate, converged results for the far-wing line shapes and the corresponding absorption coefficients. Conversely, comparison of the far-wing absorption with experimental data can serve as a sensitive diagnostic tool in order to obtain detailed information on the short-range anisotropic dependence of interaction potentials.

Ma, Q.↗

NASA NTRS2020

Motion Sickness and Concerns for Urban Air Mobility Vehicles: A Literature Review

Motion sickness is a general term for a constellation of signs and symptoms, generally due to exposure to abrupt, periodic, or unnatural accelerations, especially when traveling in a vehicle. Motion sickness results from a mismatch of the visual and nonvisual (vestibular and kinesthetic) information, the observed scene and the motion felt or lack of it. Motion sickness onset is associated with a pattern of physiological changes in heart rate, peripheral blood flow, respiration, and skin conductance and the pattern is repeatable for a particular subject but variable between subjects. Demographic factors such as gender and age that affect motion sickness are well known with children, women, and older adults more likely to be susceptible. Often motion sickness is assessed and quantified using variations of the motion sickness susceptibility questionnaires including the Pensacola Diagnostic Rating Scale and the Simulator Sickness Questionnaire. Even though symptoms are easily identified by such questionnaires, they commonly are subjective. Tools such as these questionnaires for screening individuals susceptible to motion sickness are useful, however, they are only mildly predictive. Moreover, models for predicting motion sickness, which have largely been developed for sea sickness, do not consider task characteristics. Predictions of motion sickness rates and prevalence for Urban Air Mobility (UAM) vehicles are not possible at present because data from actual flight or full-fidelity simulation are simply not yet available. Extrapolation from other modes of transportation (i.e., automobiles, buses, trains, boats, other types of aircraft) is difficult because of differences in the motion stimulus experienced, trip duration, and other factors. How UAM vehicles will change the social dynamics of passenger interaction and vehicle interior design changes (e.g., seat orientations) is unknown. Should motion sickness prove to be an issue, vehicle design modifications such as having passengers face forward, providing additional seat recline, giving each person their own climate control for airflow, perhaps ensuring the horizon is visible to all passengers (reducing visual occlusion by the headrest) and visually stabilizing displays on carry-on devices (smart phones, tablets, etc.) may benefit passengers. Several commercial companies provide wearable devices for physiological monitoring that have been validated and are suitable for use with passengers in UAM vehicles or high-fidelity simulators. Potential countermeasures for motion sickness include user-worn devices, anti-motion sickness medications, and non-pharmacological approaches such as biofeedback and Autogenic Feedback Training Exercise. Both simulator and in-vehicle UAM research is needed to evaluate the effectiveness of any potential countermeasure.

motion sickness↗

NASA NTRS1990

A simulation and diagnostic study of water vapor image dry bands

Limited Area Mesoscale Prediction System model simulation and a special 3-hr radiosonde data set were used to investigate warm bands in the 6.7-micron water-vapor satellite imagery on March 6-7, 1982. It was found that the model reproduces major characteristics of the observed blackbody temperature, T(B), field. A 'development' dry image feature was found to occur in conjunction with an upper level shortwave trough, and an 'advective' feature was found associated with a polar jet streak. Both model and observed T(B) features were associated with vorticity maxima.

Muller, Bradley M.↗

NASA NTRSDate not supplied

An Updated Model for the Effect of Atmospheric Absorption on Sounding Rockets

A very high-resolution R > 20,000 Far Ultraviolet full-disk, solar spectrograph will be launched in the Spring of 2023. This paper describes the in-flight wavelength calibration techniques and the fortuitous retrieval of Earth’s thermospheric information during the flight. Building and calibration of the Full-sun Ultraviolet Rocket Spectrograph (FURST) is currently underway. The purpose of this instrument is to obtain the highest resolution and most complete Far Ultra-Violet (FUV) spectra of the full disk Sun. This so-called "Sun-as-a-star" spectra will allow direct comparisons between our Sun and other stars measured by the Hubble Space Telescope(HST) and the upcoming James Webb Space Telescope (JWST). The Solar Physics groups at NASA Marshall Space Flight Center (MSFC) and Montana State University (MSU) have been developing the tools and procedures necessary to achieve the high spectral resolution goal. These include, among other things, improved tracking of error propagation, in-situ monitoring of the camera gain with a radioactive Fe-55 source, and the development of a simulated spectral calibration map under a noisy diagnostic-lamp signal. This mapping introduces a clocked CCD in order to obtain sub-pixel spectral resolution and overcome the Nyquist limit by about a factor of 2. Aside from the main purpose of FURST, we have been investigating the effect of absorption in the upper atmosphere at sounding-rocket altitudes (about 100-300 km). We present here an improved model of the optical depth caused by the thermospheric Oxygen cross-section and H and O self-absorption. This data-based model uses concentric spherical shells to account for the curvature of the Earth’s atmosphere and refraction. Using these calculations, we present the anticipated effect on the signal received by FURST, how that signal changes over the course of the flight-path These absorption peaks would provide wavelength fiducials at line-center that might add to in-flight calibration of the instrument. Many studies have found ways to correct for these so-called "Telluric" lines. However, it may be that these lines can in fact be a useful tool to further improve our calibration, rather than simply a nuisance to be corrected for! Finally, we discuss the inversion problem: how we could take actual flight data and back-out the atmospheric data (such as density and temperature) from any such sounding rocket flight that shows evidence of atmospheric absorption.

Nicolas Donders↗

NASA NTRS1993

DMS augmented monitoring and diganosis application (DMS AMDA) prototype

The Data Management System Augmented Monitoring and Diagnosis Application (DMS AMDA) is currently under development at NASA Ames Research Center (ARC). It will provide automated monitoring and diagnosis capabilities for the Space Station Freedom (SSF) Data Management System (DMS) in the Control Center Complex (CCC) at NASA Johnson Space Center. Several advanced automation applications are under development for use in the CCC for other SSF subsystems. The DMS AMDA, however, is the first application to utilize digraph failure analysis techniques and the Extended Realtime FEAT (ERF) application as the core of its diagnostic system design, since the other projects were begun before the digraph tools were available. Model-based diagnosis and expert systems techniques will provide additional capabilities and augment ERF where appropriate. Utilization of system knowledge captured in the design phase of a system in digraphs should result in both a cost savings and a technical advantage during implementation of the diagnostic software. This paper addresses both the programmatic and technical considerations of this approach, and describes the software design and initial prototyping effort.

Patterson-Hine, F. A.↗

NASA NTRS2013

Preparation for Scaling Studies of Ice-Crystal Icing at the NRC Research Altitude Test Facility

This paper describes experiments conducted at the National Research Council (NRC) of Canadas Research Altitiude Test Facility between March 26 and April 11, 2012. The tests, conducted collaboratively between NASA and NRC, focus on three key aspects in preparation for later scaling work to be conducted with a NACA 0012 airfoil model in the NRC Cascade rig: (1) cloud characterization, (2) scaling model development, and (3) ice-shape profile measurements. Regarding cloud characterization, the experiments focus on particle spectra measurements using two shadowgraphy methods, cloud uniformity via particle scattering from a laser sheet, and characterization of the SEA Multi-Element probe. Overviews of each aspect as well as detailed information on the diagnostic method are presented. Select results from the measurements and interpretation are presented which will help guide future work.

Ice formation↗

NASA NTRS2017

Medical Optimization Network for Space Telemedicine Resources

INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. NASA recognizes the need to improve capabilities for autonomous care on such missions. As the medical system is developed, it is important to have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources was developed for this reason, and is now a system to gauge the relative importance of medical resources in addressing medical conditions. METHODS: A list of medical conditions of potential concern for an exploration mission was referenced from the Integrated Medical Model, a probabilistic model designed to quantify in-flight medical risk. The diagnostic and treatment modalities required to address best and worst-case scenarios of each medical condition, at the terrestrial standard of care, were entered into a database. This list included tangible assets (e.g. medications) and intangible assets (e.g. clinical skills to perform a procedure). A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program ranked each of the items listed according to its criticality. Data was then obtained from the IMM for the probability of occurrence of the medical conditions, including a breakdown of best case and worst case, during a Mars reference mission. The probability of occurrence information and criticality for each resource were taken into account during analytics performed using Tableau software. RESULTS: A database and weighting system to evaluate all the diagnostic and treatment modalities was created by combining the probability of condition occurrence data with the criticalities assigned by the physician team. DISCUSSION: Exploration Medical Capabilities research at NASA is focused on providing a medical system to support crew medical needs in the context of a Mars mission. MONSTR is a novel approach to performing a quantitative risk analysis that will assess the relative value of individual resources needed for the diagnosis and treatment of various medical conditions. It will provide the operational and research communities at NASA with information to support informed decisions regarding areas of research investment, future crew training, and medical supplies manifested as part of the exploration medical system.

Shah, R. V.↗

NASA NTRS2006

Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

The primary focus of my presentation is the development of the jet noise prediction code JeNo with most examples coming from the experimental work that drove the theoretical development and validation. JeNo is a statistical jet noise prediction code, based upon the Lilley acoustic analogy. Our approach uses time-average 2-D or 3-D mean and turbulent statistics of the flow as input. The output is source distributions and spectral directivity. NASA has been investing in development of statistical jet noise prediction tools because these seem to fit the middle ground that allows enough flexibility and fidelity for jet noise source diagnostics while having reasonable computational requirements. These tools rely on Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solutions as input for computing far-field spectral directivity using an acoustic analogy. There are many ways acoustic analogies can be created, each with a series of assumptions and models, many often taken unknowingly. And the resulting prediction can be easily reverse-engineered by altering the models contained within. However, only an approach which is mathematically sound, with assumptions validated and modeled quantities checked against direct measurement will give consistently correct answers. Many quantities are modeled in acoustic analogies precisely because they have been impossible to measure or calculate, making this requirement a difficult task. The NASA team has spent considerable effort identifying all the assumptions and models used to take the Navier-Stokes equations to the point of a statistical calculation via an acoustic analogy very similar to that proposed by Lilley. Assumptions have been identified and experiments have been developed to test these assumptions. In some cases this has resulted in assumptions being changed. Beginning with the CFD used as input to the acoustic analogy, models for turbulence closure used in RANS CFD codes have been explored and compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

Bridges, James E.↗

NASA NTRS2000

Aerospike Engine Post-Test Diagnostic System Delivered to Rocketdyne

The NASA Glenn Research Center at Lewis Field, in cooperation with Rocketdyne, has designed, developed, and implemented an automated Post-Test Diagnostic System (PTDS) for the X-33 linear aerospike engine. The PTDS was developed to reduce analysis time and to increase the accuracy and repeatability of rocket engine ground test fire and flight data analysis. This diagnostic system provides a fast, consistent, first-pass data analysis, thereby aiding engineers who are responsible for detecting and diagnosing engine anomalies from sensor data. It uses analytical methods modeled after the analysis strategies used by engineers. Glenn delivered the first version of PTDS in September of 1998 to support testing of the engine s power pack assembly. The system was used to analyze all 17 power pack tests and assisted Rocketdyne engineers in troubleshooting both data acquisition and test article anomalies. The engine version of PTDS, which was delivered in June of 1999, will support all single-engine, dual-engine, and flight firings of the aerospike engine.

Meyer, Claudia M.↗

NASA NTRS2008

Multi-wavelength Observations and Modelling of a Solar Flare

Aims: The aim of this work is to investigate the dynamic behavior of a C-class solar flare through the evolution of temperature, emission measure, energy loss and velocity. In particular, the variation of these properties with time are studied using multi-wavelength observations in combination with a recently developed 0-D hydrodynamic model. Methods: The temperature and emission measure evolution were studied using several instruments covering a wide range of temperatures - the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI, >5 MK), GOES-12 (5- 30 MK), the Transition Region and Coronal Explorer (TRACE 171 A, 1 MK) and the Coronal Diagnostic Spectrometer (CDS, 0.03-8 MK). The temperature and emission measure were analysed through the systematic cooling of flare plasma through the response functions of these instruments. These parameters were then investigated using the Enthalpy Based Thermal Evolution of Loops model (EBTEL). The Doppler shifts at both flare footpoints were analysed using five emission lines seen by CDS. Results: The flare began with clear evidence for pre-flare heating. Upflows of approx.90 km/s and low level emission, both observed in Fe XIX before the main impulsive phase were explained by pre-flare gentle chromospheric evaporation. During the main impulsive phase, the flare plasma was heated to a temperature of >13 MK in approximately 10 minutes. Explosive chromospheric evaporation was observed, driving upflows of approx.80 km/s in Fe XIX and simultaneous downflows of approx.20 km/s in He I and O v. At the peak of the Rare, conduction modelled by EBTEL was found to be the dominant loss mechanism, working efficiently to both lower the temperatures and drive gentle chromospheric evaporation. As the temperature fell below approx.8 MK, radiation became the dominant loss mechanism. During the final stages of the decay phase, downflowing plasma was observed at the footpoints in He I, O v and Mg x at velocities of up to approx.40 km/s, suggesting loop draining occurred. Conclusions. This is the first extensive study of the evolution of flare plasma using both spectroscopic and broad-band instruments in conjunction with a comprehensive hydrodynamic model. The flare began with pre-flare heating and then evolved following the predictions of the standard flare model. Detailed analysis of the plasma heating mechanisms was carried out and the heating function most consistent with observations was found to be Gaussian in shape. The simulations suggested that both direct heating and heating by a non-thermal beam played significant roles in this event.

Raftery, Claire L.↗

NASA NTRS2009

Efficient Model-Based Diagnosis Engine

An efficient diagnosis engine - a combination of mathematical models and algorithms - has been developed for identifying faulty components in a possibly complex engineering system. This model-based diagnosis engine embodies a twofold approach to reducing, relative to prior model-based diagnosis engines, the amount of computation needed to perform a thorough, accurate diagnosis. The first part of the approach involves a reconstruction of the general diagnostic engine to reduce the complexity of the mathematical-model calculations and of the software needed to perform them. The second part of the approach involves algorithms for computing a minimal diagnosis (the term "minimal diagnosis" is defined below). A somewhat lengthy background discussion is prerequisite to a meaningful summary of the innovative aspects of the present efficient model-based diagnosis engine. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD (see figure). Diagnosis - the task of finding faulty components - is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. A minimal diagnosis stands in contradistinction to the trivial solution, in which all components are deemed to be faulty, and which, therefore, always explains all inconsistencies.

Fijany, Amir↗

NASA NTRSDate not supplied

Model Development of Large-Scale Spacecraft Fires During the Saffire-IV Experiments

An accidental fire can pose dire consequences to crew safety and mission success. The Saffire Project aims to investigate large-scale fire behavior in microgravity in order to aid in the prediction of spacecraft fires. These series of experiments ignite solid materials within the Northrup Grumman Cygnus vehicle after it departs from a resupply mission to the International Space Station. A model of the Cygnus vehicle during the Saffire-IV experiment was developed using the commercial software PyroSim. The cargo arranged during the descent phase was used for the geometry of the model. In the model, cabin air flows into the Saffire payload while heat and combustion species flow out of the Saffire downstream through a standoff to a bed of sensors called the Far Field Diagnostic (FFD). The temperature sensors near the Saffire payload were used to determine the heat release rate at the outlet of Saffire, while the details of the combustion and stoichiometry are used to determine the species flow at the outlet. Gas measurements previously reported for the Saffire-IV experiments are compared against the simulation results and sources of error are discussed.

Modeling↗