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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗
NASA NTRSDate not supplied

arcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗
NASA NTRSDate not supplied

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗
NASA NTRSDate not supplied

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗
NASA NTRS2014

Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article

A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.

Thermal protection materials↗
NASA NTRS2003

Ceramic Foams for TPS Applications

Ceramic foams have potential in many areas of Thermal Protection Systems (TPS) including acreage and tile leading edges as well as being suitable as a repair approach for re-entry vehicles. NASA Ames is conducting ongoing research in developing lower-density foams from pre-ceramic polymer routes. One of the key factors to investigate, when developing new materials for re-entry applications, is their oxidation behavior in the appropriate re-entry environment which can be simulated using ground based arc jet (plasma jet) testing. Arc jet testing is required to provide the appropriate conditions (stagnation pressures, heat fluxes, enthalpies, heat loads and atmospheres) encountered during flight. This work looks at the response of ceramic foams (Si systems) exposed to simulated reentry environments and investigates the influence of microstructure and composition on the material? response. Other foam properties (mechanical and thermal) will also be presented.

Stockpoole, Mairead↗
NASA NTRS2011

Rotating Arc Jet Test Model: Time-Accurate Trajectory Heat Flux Replication in a Ground Test Environment

Though arc jet testing has been the proven method employed for development testing and certification of TPS and TPS instrumentation, the operational aspects of arc jets limit testing to selected, but constant, conditions. Flight, on the other hand, produces timevarying entry conditions in which the heat flux increases, peaks, and recedes as a vehicle descends through an atmosphere. As a result, we are unable to "test as we fly." Attempts to replicate the time-dependent aerothermal environment of atmospheric entry by varying the arc jet facility operating conditions during a test have proven to be difficult, expensive, and only partially successful. A promising alternative is to rotate the test model exposed to a constant-condition arc jet flow to yield a time-varying test condition at a point on a test article (Fig. 1). The model shape and rotation rate can be engineered so that the heat flux at a point on the model replicates the predicted profile for a particular point on a flight vehicle. This simple concept will enable, for example, calibration of the TPS sensors on the Mars Science Laboratory (MSL) aeroshell for anticipated flight environments.

Laub, Bernard↗
NASA NTRS2018

Time-Varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article

A new approach to arc jet testing that replicates the time-varying conditions of atmospheric entry heating was demonstrated. The concept relies on the spatial variation of heat flux and pressure around a cylindrical test article. The spatial variation is transformed to a temporal variation at one location by rotating the test article during exposure to the arc jet stream. The test article rotation mechanism is based on a programmable stepper motor. An entry heat flux profile was mapped to the cylinders heat flux distribution to determine the rotation angle vs. time executed by the mechanism. A series of arc jet tests with instrumented cylindrical TPS test articles was conducted to prove the concept.

Aerothermodynamics↗
NASA NTRS2002

Arc Jet Testing of the TIRS Cover Thermal Protection System for Mars Exploration Rover

This paper summarizes the arc jet test results of the Mars Exploration Rover (MER) Silicone Impregnated Reusable Ceramic Ablator (SIRCA) Transverse Impulse Rocket System (TIRS) Cover test series in the Panel Test Facility (PTF) at NASA Ames Research Center (ARC). NASA ARC performed aerothermal environment analyses, TPS sizing and thermal response analyses, and arc jet testing to evaluate the MER SIRCA TIRS Cover design and interface to the aeroshell structure. The primary objective of this arc jet test series was to evaluate specific design details of the SIRCA TIRS Cover interface to the MER aeroshell under simulated atmospheric entry heating conditions. Four test articles were tested in an arc jet environment with various sea] configurations. The test condition was designed to match the predicted peak flight heat load at the gap region between the SIRCA and the backshell TPS material, SLA-561S, and resulted in an over-test (with respect to heat flux and heat load) for the apex region of the SIRCA TIRS Cover. The resulting pressure differential was as much as twenty times that predicted for the flight case, depending on the location, and there was no post-test visual evidence of over-heating or damage to the seal, bracket, or backshell structure. The exposed titanium bolts were in good condition at post-test and showed only a small amount of oxidation at the leading edge locations. Repeatable thermocouple data were obtained and SIRCA thermal response analyses were compared to applicable thermocouple data. For the apex region of the SIRCA TIRS Cover, a one-dimensional thermal response prediction proved overly conservative, as there were strong multi-dimensional conduction effects evident from the thermocouple data. The one-dimensional thermal response prediction compared well with the thermocouple data for the leading edge "lip" region at the bolt location. In general, the test results yield confidence in the baseline seal design to prevent hot gas ingestion at the bracket and composite aeroshell structure interface.

Szalai, Christine E.↗
NASA NTRS2009

Detection of Subsurface Material Separation in Shuttle Orbiter Slip-Side Joggle Region of the Wing Leading Edge using Infrared Imaging Data from Arc Jet Tests

The objective of the present study was to determine whether infrared imaging (IR) surface temperature data obtained during arc-jet tests of Space Shuttle Orbiter s reinforced carbon-carbon (RCC) wing leading edge panel slip-side joggle region could be used to detect presence of subsurface material separation, and if so, to determine when separation occurs during the simulated entry profile. Recent thermostructural studies have indicated thermally induced interlaminar normal stress concentrations at the substrate/coating interface in the curved joggle region can result in local subsurface material separation, with the separation predicted to occur during approach to peak heating during reentry. The present study was an attempt to determine experimentally when subsurface material separations occur. A simplified thermal model of a flat RCC panel with subsurface material separation was developed and used to infer general surface temperature trends due to the presence of subsurface material separation. IR data from previously conducted arc-jet tests on three test specimens were analyzed: one without subsurface material separation either pre or post test, one with pre test separation, and one with separation developing during test. The simplified thermal model trend predictions along with comparison of experimental IR data of the three test specimens were used to successfully infer material separation from the arc-jet test data. Furthermore, for the test specimen that had developed subsurface material separation during the arc-jet tests, the initiation of separation appeared to occur during the ramp up to the peak heating condition, where test specimen temperature went from 2500 to 2800 F.

Daryabeigi, Kamran↗
NASA NTRSDate not supplied

On Characterization of Flow Disturbances in Arc-Jet Testing

This paper reports computational simulations and analysis of flow characterization tests in high enthalpy arc-jet facilities at NASA Ames Research Center. Flow disturbances and their characterization are presented through case studies, and their implications for testing are discussed. The case studies include free-jet test configurations from three different arc heaters and nozzles: the 60-MW IHF 30-inch conical nozzle, the 10-MW TP3 15-inch conical nozzle, and the 20-MW AHF 12-inch conical nozzle. For all cases, test articles are placed in the jet exiting the conical nozzle, and the existence of a flow disturbance is confirmed through flow survey data using pitot pressure and heat flux probes and accompanying analysis. The paper focuses on cases where the effects of the disturbances on test article surface quantities are important. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzles and test box, including the models tested. Comparisons of computations with the experimental measurements are presented. The computations that reproduce the probe sweep data approximately are essential to interpret the arc-jet test data accurately, while providing insights into several observed calorimeter anomalies caused by flow disturbances.

Arc-jet testing↗
NASA NTRSDate not supplied

On Characterization of Flow Disturbances in Arc-Jet Testing

This paper reports computational simulations and analysis of flow characterization tests in high enthalpy arc-jet facilities at NASA Ames Research Center. Flow disturbances and their characterization are presented through case studies, and their implications for testing are discussed. The case studies include free-jet test configurations from three different arc heaters and nozzles: the 60-MW IHF 30-inch conical nozzle, the 10-MW TP3 15-inch conical nozzle, and the 20-MW AHF 12-inch conical nozzle. For all cases, test articles are placed in the jet exiting the conical nozzle, and the existence of a flow disturbance is confirmed through flow survey data using pitot pressure and heat flux probes and accompanying analysis. The paper focuses on cases where the effects of the disturbances on test article surface quantities are important. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzles and test box, including the models tested. Comparisons of computations with the experimental measurements are presented. The computations that reproduce the probe sweep data approximately are essential to interpret the arc-jet test data accurately, while providing insights into several observed calorimeter anomalies caused by flow disturbances.

Arc-jet testing↗
NASA NTRS2012

Characterization of Material Response During Arc-Jet Testing with Optical Methods Status and Perspectives

The characterization of ablation and recession of heat shield materials during arc jet testing is an important step towards understanding the governing processes during these tests and therefore for a successful extrapolation of ground test data to flight. The behavior of ablative heat shield materials in a ground-based arc jet facility is usually monitored through measurement of temperature distributions (across the surface and in-depth), and through measurement of the final surface recession. These measurements are then used to calibrate/validate materials thermal response codes, which have mathematical models with reasonably good fidelity to the physics and chemistry of ablation, and codes thus calibrated are used for predicting material behavior in flight environments. However, these thermal measurements only indirectly characterize the pyrolysis processes within an ablative material pyrolysis is the main effect during ablation. Quantification of pyrolysis chemistry would therefore provide more definitive and useful data for validation of the material response codes. Information of the chemical products of ablation, to various levels of detail, can be obtained using optical methods. Suitable optical methods to measure the shape and composition of these layers (with emphasis on the blowing layer) during arc jet testing are: 1) optical emission spectroscopy (OES) 2) filtered imaging 3) laser induced fluorescence (LIF) and 4) absorption spectroscopy. Several attempts have been made to optically measure the material response of ablative materials during arc-jet testing. Most recently, NH and OH have been identified in the boundary layer of a PICA ablator. These species are suitable candidates for a detection through PLIF which would enable a spatially-resolved characterization of the blowing layer in terms of both its shape and composition. The recent emission spectroscopy data will be presented and future experiments for a qualitative and quantitative characterization of the material response of ablative materials during arc-jet testing will be discussed.

Winter, Michael↗
NASA NTRS2020

3.6 Arc Jet Test Facilities

Among all the ground test facilities that have been developed over the past 7 decades for testing TPS, arc jet ranks as the most flight relevant and extensively used test facility in the history of TPS development in the US. Arc Jet facilities played, and continue to play, a critical role not only in the early screening and selection of TPS materials, but more importantly, in the flight vehicle integrated development and in the flight qualification.

Ethiraj Venkatapathy↗
NASA NTRS2019

Arc Jet Testing

This course will cover an overview of the Entry Systems and Technology Division (TS) at NASA Ames Research Center (ARC) and descriptions of the extensive arc jet testing complex managed within the branch. After a quick look at the Earth and Planetary Entry projects supported by TS, along with the inventions and software developed within the division, a description of the entry environments to which thermal protection systems (TPS) are exposed will be discussed. The question of "How do we insure TPS survival?" will be answered with descriptions of the various test facilities across the agency and beyond and their applicability. The Ames Arc Jet Complex will then be described, starting with how an arc heater works, adding in the associated infrastructure required to run an arc heater, and the capabilities of each of the test tunnels. Finally, examples of TPS test articles will round out the course.

arc jet testing↗
NASA NTRS2019

Arc Jet Testing: A Short Course

This course will cover an overview of the Entry Systems and Technology Division (TS) at NASA Ames Research Center (ARC) and descriptions of the extensive arc jet testing complex managed within the branch. After a quick look at the Earth and Planetary Entry projects supported by TS, along with the inventions and software developed within the division, a description of the entry environments to which thermal protection systems (TPS) are exposed will be discussed. The question of "How do we insure TPS survival?" will be answered with descriptions of the various test facilities across the agency and beyond and their applicability. The Ames Arc Jet Complex will then be described, starting with how an arc heater works, adding in the associated infrastructure required to run an arc heater, and the capabilities of each of the test tunnels. Finally, examples of TPS test articles will round out the course.

ablative materials↗