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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.↗

DOE OSTI2020

Carbon Support Microstructure Impact on High Current Density Transport Resistances in PEMFC Cathode

Cell voltages at high current densities (HCD) of an operating proton-exchange membrane fuel cell (PEMFC) cathode suffer from losses due to the local-O 2 and bulk-H + transport resistances in the catalyst layer. Particularly, the microstructure of high surface area carbon (HSC) support upon which both the platinum catalyst and ionomer are dispersed play a pivotal role in controlling the reactant transport to the active site in the catalyst layer. In this study, we perform a systematic analysis of the underlying microstructure of platinum-cobalt catalyst dispersed on various HSC supports in terms of their surface area and pore-size distribution. The carbon microstructure was found to strongly influence the PtCo nanoparticle dispersion, catalyst layer ionomer distribution and transport losses governing the performance at HCD. Catalyst layer electrochemical diagnostics carried out to quantify local-O 2 transport resistance and bulk-H + transport resistance in the cathode were found to be directly correlated to the micropore (<2 nm) and macropore (>8 nm) surface areas of the carbon support, respectively. Finally, a 1D-performance model has been developed to assimilate our understanding of the catalyst layer microstructure and transport resistances at HCD.

25 ENERGY STORAGE↗

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.↗

DOE OSTI2023

Extending the Asay window measurement model to high areal mass ranges [Slides]

The accretion layer addition to Asay window analysis results in new equations of motion that depend on the location of collisions within the layer. Asay window equations of motion can be represented in terms of experiment observables. Balance of linear momentum for variable mass systems provides a framework for developing equations of motion for Asay window diagnostics under a variety of operating assumptions. The growth in the accretion layer thickness during an experiment substantially influences mass and density measurements when high accumulation of areal mass is present.

97 MATHEMATICS AND COMPUTING↗

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↗

DOE OSTI2022

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗

DOE OSTI2024

Phase retrieval for refraction-enhanced x-ray radiography using a deep neural network

X-ray refraction-enhanced radiography (RER) or phase contrast imaging is widely used to study internal discontinuities within materials. The resulting radiograph captures both the decrease in intensity caused by material absorption along the x-ray path, as well as the phase shift, which is highly sensitive to gradients in density. A significant challenge lies in effectively analyzing the radiographs to decouple the intensity and phase information and accurately ascertain the density profile. Conventional algorithms often yield ambiguous and unrealistic results due to difficulties in including physical constraints and other relevant information. We have developed an algorithm that uses a deep neural network to address these issues and applied it to extract the detailed density profile from an experimental RER. To generalize the applicability of our algorithm, we have developed a technique that quantitatively evaluates the complexity of the phase retrieval process based on the characteristics of the sample and the configuration of the experiment. Accordingly, this evaluation aids in the selection of the neural network architecture for each specific case. Beyond RER, the model has potential applications for other diagnostics where phase retrieval analysis is required.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

NO x Control and Measurement Technology for Heavy-Duty Diesel Engines (CRADA Final Report)

The Catalyst CRADA focused on lean-NO x trap (LNT) and selective catalytic reduction (SCR) automotive emission control catalyst technology. It particularly had the goal of developing and applying advanced diagnostics capable of elucidating the network and sequence of catalyst reactions, as well as how they are affected by real-world operation and aging. Another overarching goal and action of this CRADA section was to develop methods to quantify and monitor catalyst states and support the development of full and reduced models for design and in-use control applications. William Partridge was the ORNL principal investigator (PI) throughout the Catalyst CRADA; Neal Currier was the Cummins PI through circa 2017, and Saurabh Joshi was the subsequent Cummins PI.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

A Miniaturized Ignition Screening Rapid Compression Machine for probing low-to-intermediate temperature chemistry

With an objective to achieve net-zero emissions by no later than 2050, biofuels hold enormous potential as sustainable, renewable fuels that can be produced on a large scale. However, fuels of a similar type, derived from limited feedstock batch can dramatically vary in terms of their chemical structures and compositions, causing significant differences in physicochemical properties mainly influencing ignition-relevant properties. Rigorous prescreening and testing efforts are involved to evaluate fuels to comply with engines equipped with advanced combustion modes. The testing of some of these fuels implies low quantity fuel samples, access to relevant temperature and pressure conditions, high reproducibility, and a high throughput rate. In light of these considerations, a Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC). Some design features include a smaller bellows-actuated driver section compared to other RCM designs, an adjustable brake section, and full optical access. The setup is designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions are relevant to low-to-intermediate temperature auto-ignition and can generate data for developing relevant chemical kinetics models or ignition maps. A brief insight into MISR design and its operating mechanism is shown. Also, to demonstrate the performance characteristics of the MISR, Ignition Delay (I.D) experiments for ethanol fuel at different equivalence ratios (Φ) are discussed in the context of plans with additional optical diagnostics, high-speed imaging, and gas sampling experiments.

Tomar, Mukul↗

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↗

DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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↗

DOE OSTI2020

Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

Limited therapy options due to antibiotic resistance underscore the need for optimization of current diagnostics. In some bacterial species, antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and expression profiles, we generated predictive models and identified biomarkers of resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8–0.9) or very high (> 0.9) sensitivity and predictive values. For all drugs except for ciprofloxacin, gene expression information improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. Finally, the implementation of a molecular susceptibility test system in routine microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

59 BASIC BIOLOGICAL SCIENCES↗