Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model diagnostics and development”

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 469 records · Page 26

Mass and Reliability Source (MaRS) Database

The Mass and Reliability Source (MaRS) Database consolidates components mass and reliability data for all Oribital Replacement Units (ORU) on the International Space Station (ISS) into a single database. It was created to help engineers develop a parametric model that relates hardware mass and reliability. MaRS supplies relevant failure data at the lowest possible component level while providing support for risk, reliability, and logistics analysis. Random-failure data is usually linked to the ORU assembly. MaRS uses this data to identify and display the lowest possible component failure level. As seen in Figure 1, the failure point is identified to the lowest level: Component 2.1. This is useful for efficient planning of spare supplies, supporting long duration crewed missions, allowing quicker trade studies, and streamlining diagnostic processes. MaRS is composed of information from various databases: MADS (operating hours), VMDB (indentured part lists), and ISS PART (failure data). This information is organized in Microsoft Excel and accessed through a program made in Microsoft Access (Figure 2). The focus of the Fall 2017 internship tour was to identify the components that were the root cause of failure from the given random-failure data, develop a taxonomy for the database, and attach material headings to the component list. Secondary objectives included verifying the integrity of the data in MaRS, eliminating any part discrepancies, and generating documentation for future reference. Due to the nature of the random-failure data, data mining had to be done manually without the assistance of an automated program to ensure positive identification.

Valdenegro, Wladimir↗

Overview of the Development of the Solar Electric Propulsion Technology Demonstration Mission 12.5-kW Hall Thruster

NASA is developing mission concepts for a solar electric propulsion technology demonstration mission. A number of mission concepts are being evaluated including ambitious missions to near Earth objects. The demonstration of a high-power solar electric propulsion capability is one of the objectives of the candidate missions under consideration. In support of NASAs exploration goals, a number of projects are developing extensible technologies to support NASAs near and long term mission needs. Specifically, the Space Technology Mission Directorate Solar Electric Propulsion Technology Demonstration Mission project is funding the development of a 12.5-kW magnetically shielded Hall thruster system to support future NASA missions. This paper presents the design attributes of the thruster that was collaboratively developed by the NASA Glenn Research Center and the Jet Propulsion Laboratory. The paper provides an overview of the magnetic, plasma, thermal, and structural modeling activities that were carried out in support of the thruster design. The paper also summarizes the results of the functional tests that have been carried out to date. The planned thruster performance, plasma diagnostics (internal and in the plume), thermal, wear, and mechanical tests are outlined.

Electric Propulsion↗

Overview of the Development of the Solar Electric Propulsion Technology Demonstration Mission 12.5-kW Hall Thruster

NASA is developing mission concepts for a solar electric propulsion technology demonstration mission. A number of mission concepts are being evaluated including ambitious missions to near Earth objects. The demonstration of a high-power solar electric propulsion capability is one of the objectives of the candidate missions under consideration. In support of NASA's exploration goals, a number of projects are developing extensible technologies to support NASA's near and long term mission needs. Specifically, the Space Technology Mission Directorate Solar Electric Propulsion Technology Demonstration Mission project is funding the development of a 12.5-kilowatt magnetically shielded Hall thruster system to support future NASA missions. This paper presents the design attributes of the thruster that was collaboratively developed by the NASA Glenn Research Center and the Jet Propulsion Laboratory. The paper provides an overview of the magnetic, plasma, thermal, and structural modeling activities that were carried out in support of the thruster design. The paper also summarizes the results of the functional tests that have been carried out to date. The planned thruster performance, plasma diagnostics (internal and in the plume), thermal, wear, and mechanical tests are outlined.

High power long life hall thrusters↗

CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Flux Improvement based on Machine Learning for the CERES FluxByCldTyp Data Product

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Improving Radiative Fluxes for the CERES FluxByCldTyp Data Product Using Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Preliminary results show significant LW improvement.

Sun, Moguo↗

Flare loop radiative hydrodynamics. I - Basic methods

The study presented here has two goals. The first is to examine the role of energy transport mechanisms in flare dynamics, for instance, thermal cone conduction in the corona and radiative transfer in the chromosphere. The second is to provide diagnostics of flare energization processes by predicting the evolutionary behavior of concurrent emissions from all regions of the flaring atmosphere. To attain these ends, a numerical method is developed for the simultaneous solution of thy continuity, momentum, and energy equations; the time-dependent atomic rate equations describing ionization and excitation; and the radiative transfer equations. With the physical model and computational methods used here, all components of the plasma move as a single fluid and in the initial studies are assumed to have a common kinetic temperature. The plasma is constrained to move in one dimension along the axis of a loop of nonuniform cross section, the geometry of which is defined by a sufficiently strong magnetic field.

Mcclymont, A. N.↗

SHADOZ (Southern Hemisphere ADditional OZonesondes): An Ozonesonde Network for Satellite Validation, Climatology and Modeling

In the past 5 years, new tropical ozone data products have been developed from TOMS and other satellites, During this period, global chemical-transport models have been used for ozone assessment studies. However, there has been a lack of independent ozone profiles in the tropics for evaluation of the data sets and models. In 1998, NASA's Goddard Space Flight Center, Wallops Flight Facility and NOAA's CMDL (Climate Monitoring and Diagnostics Lab), began a 2-year project to collect a consistent data set by augmenting ozonesonde launches at southern hemisphere tropical sites The measurements are available to the scientific community at a single electronic location - the SHADOZ website at NASA/Goddard: http://code9l6.gsfc.nasa.gov/Data services/Shadoz/shadoz hmpg2.html. Stations in SHADOZ include four islands in the Pacific: Fiji, Tahiti, San Cristobal (Galapagos) and American Samoa. Two sites are at and in the Atlantic: Natal (Brazil) and Ascension Island. Three other sites span Africa (Nairobi and Irene, South Africa) and the Indian Ocean (Reunion Island and Watukosek in Java, Indonesia). All SHADOZ sites are using ECC-type sondes, with the conversion from JMD sondes at Java in 1999, but there are variations in sonde preparation technique and data processing. During the 1998-1999 period, more than 550 sondes were incorporated into the SHADOZ data base. Examples from these measurements illustrate the tropical wave-one pattern in total ozone which is easily detectable by satellite. They also show that the wave-one pattern appears to be in the troposphere, as assumed in creating the modified-residual tropospheric ozone data product from TOMS. SHADOZ will add data from intensive field campaigns from time to time. Recent contributions to the SHADOZ archive are from the INDOEX (Indian Ocean Experiment January-March 1999)sondes at the Maldives (5N, 73E) and 27 sondes on the US NOAA oceanographic vessel, the FIN Ronald H Brown between Virginia (US) and Mauritius via CapeTown, during a cruise in January and February 1999. In 2000, as part of the SAFARI-2000 experiment and a validation project called Southern African Validation for EOS (SAVE), enhancement of ozonesonde launches at Irene (South Africa) will extend the data set from this site beyond the 1998-1999 period.

Thompson, Anne M.↗

Rapid Technology Assessment via Unified Deployment of Global Optical and Virtual Diagnostics

This paper discusses recent developments in rapid technology assessment resulting from an active collaboration between researchers at the Air Force Research Laboratory (AFRL) at Wright Patterson Air Force Base (WPAFB) and the NASA Langley Research Center (LaRC). This program targets the unified development and deployment of global measurement technologies coupled with a virtual diagnostic interface to enable the comparative evaluation of experimental and computational results. Continuing efforts focus on the development of seamless data translation methods to enable integration of data sets of disparate file format in a common platform. Results from a successful low-speed wind tunnel test at WPAFB in which global surface pressure distributions were acquired simultaneously with model deformation and geometry measurements are discussed and comparatively evaluated with numerical simulations. Intensity- and lifetime-based pressure-sensitive paint (PSP) and projection moire interferometry (PMI) results are presented within the context of rapid technology assessment to enable simulation-based R&D.

Jordan, Jeffrey D.↗

The Nature of the Vela Supernova Remnant as Revealed by O VI and C IV Absorption

Highly ionized gas, in particular C IV and O VI, is produced in the interstellar medium in regions with hot (T approx. 10(exp 6) K) X-ray emitting gas and at the boundaries where hot gas and cooler (T approx. 10(exp 4) K) gas interact. Supernova remnant shocks produce most of the hot gas in the ISM and, if they are in the correct range of speeds, should produce observable quantities of C IV and O VI absorption. In turn, the column densities of these ions are potentially powerful diagnostics of the shock speed and interstellar environment in which the SNR is evolving. With the advent of FUSE, the power of this diagnostic technique is now available. We have FUSE data toward 8 stars behind the Vela SNR, and have developed a data reduction and analysis method that produces reasonably reliable O VI column densities, in spite of the complexities of the FUSE spectra in this region. In order to gain insight into the observational results, the Vela SNR evolution was modelled using Piecewise Parabolic Method numerical hydrodynamics code. The code is 1-D and incorporates non-equilibrium ionization, radiative cooling, thermal conduction and magnetic pressure.

Lines, Nichols J.↗

Spontaneous Raman Scattering (SRS) System for Calibrating High-Pressure Flames Became Operational

A high-performance spontaneous Raman scattering (SRS) system for measuring quantitative species concentration and temperature in high-pressure flames is now operational. The system is located in Glenn s Engine Research Building. Raman scattering is perhaps the only optical diagnostic technique that permits the simultaneous (single-shot) measurement of all major species (N2, O2, CO2, H2O, CO, H2, and CH4) as well as temperature in combustion systems. The preliminary data acquired with this new system in a 20-atm hydrogen-air (H2-air) flame show excellent spectral coverage, good resolution, and a signal-to-noise ratio high enough for the data to serve as a calibration standard. This new SRS diagnostic system is used in conjunction with the newly developed High- Pressure Gaseous Burner facility (ref. 1). The main purpose of this diagnostic system and the High-Pressure Gaseous Burner facility is to acquire and establish a comprehensive Raman-scattering spectral database calibration standard for the combustion diagnostic community. A secondary purpose of the system is to provide actual measurements in standardized flames to validate computational combustion models. The High-Pressure Gaseous Burner facility and its associated SRS system will provide researchers throughout the world with new insights into flame conditions that simulate the environment inside the ultra-high-pressure-ratio combustion chambers of tomorrow s advanced aircraft engines.

Nguyen, Quang-Viet↗

Overview of aerothermodynamic loads definition study

The objective of the Aerothermodynamic Loads Definition Study is to develop methods of accurately predicting the operating environment in advanced Earth-to-Orbit (ETO) propulsion systems, such as the Space Shuttle Main Engine (SSME) powerhead. Development of time averaged and time dependent three dimensional viscous computer codes as well as experimental verification and engine diagnostic testing are considered to be essential in achieving that objective. Time-averaged, nonsteady, and transient operating loads must all be well defined in order to accurately predict powerhead life. Described here is work in unsteady heat flow analysis, improved modeling of preburner flow, turbulence modeling for turbomachinery, computation of three dimensional flow with heat transfer, and unsteady viscous multi-blade row turbine analysis.

Gaugler, Raymond E.↗

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Dempsey, Paula J.↗

Integrated Diagnostics and Prognostics for the Electrical Power System of a Planetary Rover

For electric vehicles, technology for monitoring, diagnosis, and prognosis of the electrical power system (EPS) becomes essential for safe and efficient operation. To this end, we develop a general system-level integrated diagnosis and prognosis framework, which detects, isolates, and identifies EPS faults, and predicts when the EPS will fail to deliver sufficient power. The approach takes advantage of recent work in structural model decomposition in order to distribute the global diagnosis and prognosis problems into local subproblems that can be solved in parallel, thus enabling implementation on distributed computational platforms. The framework is applied to the EPS of a planetary rover testbed, and is demonstrated using data from field experiments.

Daigle, Matthew↗

Kepler Data Validation II–Transit Model Fitting and Multiple-Planet Search

This paper discusses the transit model-fitting and multiple-planet search algorithms and performance of the Kepler Science Data Processing Pipeline, developed by the Kepler Science Operations Center (SOC). Threshold crossing events (TCEs), which are transit candidate events, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the data validation (DV) component. The transit model is used in DV to fit TCEs to characterize planetary candidates and to derive parameters that are used in various diagnostic tests to classify them. After the signature associated with the TCE is removed from the light curve of the target star, the residual light curve goes through TPS again to search for additional TCEs. The iterative process of transit model fitting and multiple-planet search continues until no TCE is generated from the residual light curve or an upper limit is reached. The transit model-fitting and multiple-planet search performance of the final release (9.3, 2016January) of the pipeline is demonstrated with the results of the processing of four years (17 quarters) of flight data from the primary Kepler Mission. The transit model-fitting results are accessible from the NASA Exoplanet Archive. The final version of the SOC codebase is available through GitHub.

Threshold crossing events (TCEs↗

Transport processes in the middle atmosphere: Reflections after MAP

The Middle Atmosphere Program (MAP) has provided a focus for considerable research on atmospherical radiative, chemical, and dynamical processes and the mutual coupling among these processes. In particular, major advances have occurred in the understanding of constituent transport as a result of near-global measurements obtained during MAP from several satellite based instruments (e.g., LIMS, SAMS, SAGE, and SSU among others). Using selected portions of these data, the development is reviewed of progress in understanding transport processes with special emphasis on dynamically active periods. Examples are presented which demonstrate coupling between chemistry and dynamics. In addition to the constituent data, the use is reviewed of Ertel's potential vorticity, inferred from satellite temperature data, as a diagnostic for interpreting transport phenomena. Finally, the use is briefly illustrated of 3-D model simulations, in conjunction with the satellite data, for providing additional insight into fundamental transport mechanisms.

Grose, W. L.↗

Human Exploration Science Office (KX) Overview

The Human Exploration Science Office supports human spaceflight, conducts research, and develops technology in the areas of space orbital debris, hypervelocity impact technology, image science and analysis, remote sensing, imagery integration, and human and robotic exploration science. NASA's Orbital Debris Program Office (ODPO) resides in the Human Exploration Science Office. ODPO provides leadership in orbital debris research and the development of national and international space policy on orbital debris. The office is recognized internationally for its measurement and modeling of the debris environment. It takes the lead in developing technical consensus across U.S. agencies and other space agencies on debris mitigation measures to protect users of the orbital environment. The Hypervelocity Impact Technology (HVIT) project evaluates the risks to spacecraft posed by micrometeoroid and orbital debris (MMOD). HVIT facilities at JSC and White Sands Test Facility (WSTF) use light gas guns, diagnostic tools, and high-speed imagery to quantify the response of spacecraft materials to MMOD impacts. Impact tests, with debris environment data provided by ODPO, are used by HVIT to predict risks to NASA and commercial spacecraft. HVIT directly serves NASA crew safety with MMOD risk assessments for each crewed mission and research into advanced shielding design for future missions. The Image Science and Analysis Group (ISAG) supports the International Space Station (ISS) and commercial spaceflight through the design of imagery acquisition schemes (ground- and vehicle-based) and imagery analyses for vehicle performance assessments and mission anomaly resolution. ISAG assists the Multi-Purpose Crew Vehicle (MPCV) Program in the development of camera systems for the Orion spacecraft that will serve as data sources for flight test objectives that lead to crewed missions. The multi-center Imagery Integration Team is led by the Human Exploration Science Office and provides expertise in the application of engineering imagery to spaceflight. The team links NASA programs and private industry with imagery capabilities developed and honed through decades of human spaceflight, including imagery integration, imaging assets, imagery data management, and photogrammetric analysis. The team is currently supporting several NASA programs, including commercial demonstration missions. The Earth Science and Remote Sensing Team is responsible for integrating the scientific use of Earth-observation assets onboard the ISS, which consist of externally mounted sensors and crew photography capabilities. This team facilitates collaboration on remote sensing and participates in research with academic organizations and other Government agencies, not only in conjunction with ISS science, but also for planetary exploration and regional environmental/geological studies. Human exploration science focuses on science strategies for future human exploration missions to the Moon, Mars, asteroids, and beyond. This function provides communication and coordination between the science community and mission planners. ARES scientists support the operation of robotic missions (i.e., Mars Exploration Rovers and the Mars Science Laboratory), contribute to the interpretation of returned mission data, and translate robotic mission technologies and techniques to human spaceflight.

Calhoun, Tracy A.↗