Search NASA⌕ Search

SEARCH · Search NASA

Results for “model diagnostics”

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.

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

At least 307 records · Page 17

Mean Ages of Stratospheric Air Derived From in Situ Observations of CO2, CH4, and N2O

Accurate mean ages for stratospheric air have been derived from a spatially and temporally comprehensive set of in situ observations of CO2, CH4, and N2O obtained from 1992 to 1998 from the NASA ER-2 aircraft and balloon flights. Errors associated with the tropospheric CO2 seasonal cycle and interannual variations in the CO2 growth rate are less than 0.5 year throughout the stratosphere and less than 0.3 year for air older than 2 years (N2O less than 275 ppbv), indicating that the age spectra are broad enough to attenuate these influences over the time period covered by these observations. The distribution of mean age with latitude and altitude provides detailed, quantitative information about the general circulation of the stratosphere. At 20 km, sharp meridional gradients in the mean age are observed across the subtropics. Between 20 and 30 km, the average difference in mean age between the tropics and midlatitudes is approximately 2 years, with slightly smaller differences at higher and lower altitudes. The mean age in the midlatitude middle stratosphere (approx. 25-32 km) is relatively constant with respect to altitude at 5 plus or minus 0.5 years. Comparison with earlier balloon observations of CO2 dating back to the 1970s indicates that the mean age of air in this region has remained within 11 year of its current value over the last 25 years. A climatology of mean age is derived from the observed compact relationship between mean age and N2O. These characteristics of the distribution of mean age in the stratosphere will serve as critically needed diagnostics for models of stratospheric transport.

Andrews, A. E.↗

Steady and Unsteady Flow Field Measurements Within a NASA 22-Inch Fan Model

Results are presented of an experiment conducted to investigate possible sources of fan noise in the flow developed by a 22-in. (55.9 cm) diameter turbofan model. Flow diagnostic data were acquired to identify possible sources of both tone and broadband noise. Laser Doppler velocimetry was used to characterize the tip flows that develop within the rotor blade passages, the wake flow downstream of the rotor, and the shock waves that develop on the blades when operated at transonic relative tip speeds. Single-point hot-wire measurements were made in the rotor wake to determine the frequency content and the length scales of the flow unsteadiness. The results document the changes in the rotor wake flow with both rotor speed and axial distance downstream of the rotor. The data also show the tip flow development within the blade passage, its migration downstream, and (at high rotor speeds) its merging with the blade wake of the following blade. Data also depict the variation of the tip flow with tip clearance. LDV data obtained within the blade passages at high rotor speeds illustrate the passage-to-passage variation of the mean shock position. Spectra computed from the single-point hot-wire measurements illustrate how the energy in the flow oscillations is split between periodic and random components, and how this split varies with both radial and axial position in the rotor wake.

Podboy, Gary G.↗

Physics of Solar Prominences: I-Spectral Diagnostics and Non-LTE Modelling

This review paper outlines background information and covers recent advances made via the analysis of spectra and images of prominence plasma and the increased sophistication of non-LTE (i.e. when there is a departure from Local Thermodynamic Equilibrium) radiative transfer models. We first describe the spectral inversion techniques that have been used to infer the plasma parameters important for the general properties of the prominence plasma in both its cool core and the hotter prominence-corona transition region. We also review studies devoted to the observation of bulk motions of the prominence plasma and to the determination of prominence mass. However, a simple inversion of spectroscopic data usually fails when the lines become optically thick at certain wavelengths. Therefore, complex

Labrosse, N.↗

NASA Tech Briefs, June 2005

Topics covered include: Apparatus Characterizes Transient Voltages in Real Time; Measuring Humidity in Sealed Glass Encasements; Adaptable System for Vehicle Health and Usage Monitoring; Miniature Focusing Time-of-Flight Mass Spectrometer; Cryogenic High-Sensitivity Magnetometer; Wheel Electrometer System; Carbon-Nanotube Conductive Layers for Thin-Film Solar Cells; Patch Antenna Fed via Unequal-Crossed-Arm Aperture; LC Circuits for Diagnosing Embedded Piezoelectric Devices; Nanowire Thermoelectric Devices; Code for Analyzing and Designing Spacecraft Power System Radiators; Decision Support for Emergency Operations Centers; NASA Records Database; Real-Time Principal- Component Analysis; Fuzzy/Neural Software Estimates Costs of Rocket- Engine Tests; Multicomponent, Rare-Earth-Doped Thermal-Barrier Coatings; Reactive Additives for Phenylethynyl-Containing Resins; Improved Gear Shapes for Face Worm Gear Drives; Alternative Way of Shifting Mass to Move a Spherical Robot; Parylene C as a Sacrificial Material for Microfabrication; In Situ Electrochemical Deposition of Microscopic Wires; Improved Method of Manufacturing SiC Devices; Microwave Treatment of Prostate Cancer and Hyperplasia; Ferroelectric Devices Emit Charged Particles and Radiation; Dusty-Plasma Particle Accelerator; Frozen-Plug Technique for Liquid-Oxygen Plumbing; Shock Waves in a Bose-Einstein Condensate; Progress on a Multichannel, Dual-Mixer Stability Analyzer; Development of Carbon- Nanotube/Polymer Composites; Thermal Imaging of Earth for Accurate Pointing of Deep-Space Antennas; Modifications of a Composite-Material Combustion Chamber; Modeling and Diagnostic Software for Liquefying- Fuel Rockets; and Spacecraft Antenna Clusters for High EIRP.

Source record↗

Global and Regional Seasonal Variability of Mid-Tropospheric CO2 as Measured by the Atmospheric Infrared Sounder (AIRS)

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral infrared instrument on the Earth Observing System (EOS) Aqua Spacecraft, launched on May 4, 2002 into a near polar sun-synchronous orbit. AIRS has 2378 infrared channels ranging from 3.7 ?m to 15.4 ?m and a 13.5 km footprint at nadir. AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), produces temperature profiles with 1K/km accuracy on a global scale, as well as water vapor profiles and trace gas amounts for CO2, CO, SO2, O3 and CH4. AIRS CO2 climatologies have been shown to be useful for identifying anomalies associated with geophysical events such as El Nino-Southern Oscillation or Madden-Julian oscillation. In this study, monthly representations of mid-tropospheric CO2 are constructed from 10 years of AIRS Version 5 monthly Level 3 data. We compare the AIRS mid-tropospheric CO2 representations to ground-based measurements from the Scripps and National Oceanic and Atmospheric Administration Climate Modeling and Diagnostics Laboratory (NOAA CMDL) ground networks to better understand the phase lag of the CO2 seasonal cycle between the surface and middle troposphere. Results show only a small phase lag in the tropics that grows to approximately two months in the northern latitudes.

satellite↗

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)< 1 cm/s and v(sub f)> 10 cm/s, N(sub i)/N(sub IN)<< 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)< 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Fridlin, Ann↗

A System for Fault Management for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

Fault management↗

Boron Nitride Nanotube: Synthesis and Applications

Scientists have predicted that carbon's immediate neighbors on the periodic chart, boron and nitrogen, may also form perfect nanotubes, since the advent of carbon nanotubes (CNTs) in 1991. First proposed then synthesized by researchers at UC Berkeley in the mid 1990's, the boron nitride nanotube (BNNT) has proven very difficult to make until now. Herein we provide an update on a catalyst-free method for synthesizing highly crystalline, small diameter BNNTs with a high aspect ratio using a high power laser under a high pressure and high temperature environment first discovered jointly by NASA/NIA JSA. Progress in purification methods, dispersion studies, BNNT mat and composite formation, and modeling and diagnostics will also be presented. The white BNNTs offer extraordinary properties including neutron radiation shielding, piezoelectricity, thermal oxidative stability (> 800 C in air), mechanical strength, and toughness. The characteristics of the novel BNNTs and BNNT polymer composites and their potential applications are discussed.

Tiano, Amanda L.↗

A System for Fault Management and Fault Consequences Analysis for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy

System Effects Analysis↗

The Impacts of Climate and Wildfire on Ecosystem Gross Primary Productivity in Alaska

The increase in wildfire occurrence and severity seen over the past decades in the boreal and Arctic biomes is expected to continue in the future in response to rapid climate change in this region. Recent studies documented positive trends in gross primary productivity (GPP) for Arctic boreal biomes driven by warming, but it is unclear how GPP trends are affected by wildfires. Here, we used satellite vegetation observations and environmental data with a diagnostic GPP model to analyze recovery from large fires in Alaska over the period 2000‐2019. We confirmed earlier findings that warmer‐than‐average years provide favorable climate conditions for vegetation growth, leading to a GPP increase of 1 Tg C/yr, contributed mainly from enhanced productivity in the early growing season. However, higher temperatures increase the risk of wildfire occurrence leading to direct carbon loss over a period of 1‐3 years. While mortality related to severe wildfires reduce ecosystem productivity, post‐fire productivity in moderately burned areas shows a significant positive trend. The rapid GPP recovery following fires reported here might be favorable for maintaining the region’s net carbon sink, but wildfires can indirectly promote the release of long‐term stored carbon in the permafrost. With the projected increase in severity and frequency of wildfires in the future, we expect a reduction of GPP and therefore amplification of climate warming in this region.

Nima Madani↗

A Framework to Debug Diagnostic Matrices

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Model-based↗

Software Users Manual (SUM): Extended Testability Analysis (ETA) Tool

This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual

Maul, William A.↗

Modeling of a spatially resolved ion temperature diagnostic for inertial confinement fusion

Here, the performance of modern laser-driven inertial confinement fusion (ICF) experiments is degraded by contamination of the deuterium–tritium (DT) fuel with high-Z material during compression. Simulations suggest that this mix can be described by the ion temperature distribution of the implosion, given that such contaminants deviate in temperature from the surrounding DT plasma. However, existing neutron time-of-flight (nTOF) diagnostics only measure the spatially integrated ion temperature. This paper describes the techniques and forward modeling used to develop a novel diagnostic imaging system to measure the spatially resolved ion temperature of an ICF implosion for the first time. The technique combines methods in neutron imaging and nTOF diagnostics to measure the ion temperature along one spatial dimension at yields currently achievable on the OMEGA laser. A detailed forward model of the source and imaging system was developed to guide instrument design. The model leverages neutron imaging reconstruction algorithms, radiation hydrodynamics and Monte Carlo simulations, optical ray tracing, and more. The results of the forward model agree with the data collected on OMEGA using the completed diagnostic. The analysis of the experimental data is still ongoing and will be discussed in a separate publication.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

Beam-driven plasma wakefield acceleration (PWFA) achieves the same energy gain in a single meter, for which conventional accelerators require several kilometers, however much work is still required to match the beam quality of conventional accelerators. The PWFA processes to be studied at the FACET-II facility will utilize extremely short (down to a few fs) high energy (10 GeV), high charge (few nC) electron and eventually positron bunches. The PWFA process is extremely sensitive to the detailed longitudinal current profiles of these bunches and it would be of great benefit to have precise measurement and control of these profiles. We present an adaptive model tuning technique for FACET-II to adaptively tune online models based on real time accelerator and beam data to continuously provide a non-invasive diagnostic which predicts the longitudinal phase space (LPS) of extremely short and highly compressed electron beams, which otherwise require destructive X-band transverse deflecting cavity (XTCAV)-based measurements. Based on simulation studies, our method has the potential for: (1). The development of a non-invasive longitudinal phase space diagnostic by adaptively tuning models based on non-invasive measurements such as energy spread spectra which could be recorded at all of the bunch compressors in the facility. (2). Utilize these diagnostic to perform model-independent feedback-based to achieve desired longitudinal phase space distributions. (3). Utilize the model-independent feedback approach to maximize energy gain while minimizing emittance growth and energy gain variance of the PWFA process by tuning accelerator parameters, while monitoring what longitudinal phase space the algorithm has found, information that will be useful for further analytical and simulation studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Model Calibration with Markov Chain Monte Carlo Tutorial

The purpose of this tutorial is to demonstrate how to use Markov chain Monte Carlo (MCMC) to calibrate a model. By calibration, we mean the selection of model parameters (and, when relevant, structures). A common goal in model development and diagnostics is calibration, or the identification of model structures and parameters which are consistent with data. While models can be calibrated through hand-tuning parameters or minimizing simple error metrics such as root-mean-square-error (RMSE), these approaches can underrepresent the probabilistic nature of the data-generating process, as well as the potential for multiple model configurations to be consistent with the data. Probabilistic uncertainty quantification, which is the topic of this notebook, can address these concerns. This tutorial is presented as an appendix to the e-book: Addressing Uncertainty in MultiSector Dynamics Research.

Markov chain Monte Carlo↗

A Cryogenic Fluid System Simulation in Support of Integrated Systems Health Management

Simulations serve as important tools throughout the design and operation of engineering systems. In the context of sys-tems health management, simulations serve many uses. For one, the underlying physical models can be used by model-based health management tools to develop diagnostic and prognostic models. These simulations should incorporate both nominal and faulty behavior with the ability to inject various faults into the system. Such simulations can there-fore be used for operator training, for both nominal and faulty situations, as well as for developing and prototyping health management algorithms. In this paper, we describe a methodology for building such simulations. We discuss the design decisions and tools used to build a simulation of a cryogenic fluid test bed, and how it serves as a core technology for systems health management development and maturation.

cryogenics↗

Model Based Inference for Wire Chafe Diagnostics

Presentation for Aging Aircraft conference covering chafing fault diagnostics using Time Domain Reflectometry. Laboratory setup and experimental methods are presented, along with initial results that summarize fault modeling and detection capabilities.

Schuet, Stefan R.↗