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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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Experimental Measurements of the High-Temperature Oxidation of Carbon Fibers

We carried out laboratory experiments to study the decomposition of carbon fibers at high temperature and studied the material used in charring carbon phenolic ablators for planetary probe heatshields. Porous plug samples were exposed to controlled rates of molecular oxygen, carbon dioxide, and carbon monoxide at furnace-heated flow-tube reactor temperatures between 700 and 1500 K and pressures between 2000 and 6200 Pa. We used calibrated mass spectroscopy to make time-resolved quantitative measurements of decomposition products of the gases downstream of the test sample. Absolute and differential pressure measurements were used to determine the high-temperature permeability of the material and to monitor changes during material decomposition, and we characterized the microstructure of the porous sample using scanning electron microscopy. We found substantial carbon fiber oxidation for O2 flows, resulting in increasing CO/CO2 production ratios with increasing temperature. The CO2 was shown to react with carbon fibers following a Boudouard reaction at temperatures above 1200 K.

Francesco Panerai↗

Recent Advances in LIBS for Real-Time Detection of Silicone Contaminants on CFRP Surfaces

Laser induced breakdown spectroscopy (LIBS) is a materials characterization technique that has been advanced and refined to provide in situ, real-time quality control of carbon fiber reinforced polymer (CFRP) surfaces. As part of an effort to improve process control for adhesive bonding, a LIBS system was designed and assembled at NASA Langley Research Center (LaRC) to enable detection of ultralow concentrations of silicone contamination on CFRP adherends. The LIBS instrument provides high sensitivity detection and quasi-nondestructive surface characterization of CFRP adherends prior to adhesive bonding. This review focuses on the advancements at LaRC using LIBS as a quality control tool for the detection of silicone contaminants for improved adhesive bonding reliability of CFRP materials. This work describes how the LIBS technique was advanced by analyzing the laser parameters, studying the laser-matter interactions, and performing time-resolved measurements to determine the optimal plasma conditions for elemental detection. In addition, LIBS results were compared to X-ray photoelectron spectroscopy data to enable quantitative analysis from analytical calibration curves. Examples are shown of how to perform surface mapping of silicone contamination. Finally, a brief discussion is also presented on LIBS instrumentation, recommendations for laser parameters and instrumentation components, and LIBS technique maturity.

Surface characterization, Carbon fiber reinforced ↗

Recent Advances in LIBS for Real-Time Detection of Silicone Contaminants on CFRP Surfaces

Laser induced breakdown spectroscopy (LIBS) is a materials characterization technique that has been advanced and refined to provide in situ, real-time quality control of carbon fiber reinforced polymer (CFRP) surfaces. As part of an effort to improve process control for adhesive bonding, aLIBS system was designed and assembled at the NASA Langley Research Center (LaRC) to enable detection of ultra low concentrations of silicone contamination on CFRP adherends. The LIBS instrument provides high sensitivity detection and quasi-nondestructive surface characterization ofCFRP adherends prior to adhesive bonding. This review focuses on the advancements at LaRC using LIBS as a quality control tool for the detection of silicone contaminants for improved adhesive bonding reliability of CFRP materials. This work describes how the LIBS technique was advanced by analyzing the laser parameters, studying the laser-matter interactions, and performing time-resolved measurements to determine the optimal plasma conditions for elemental detection. In addition, LIBS results were compared to X-ray photoelectron spectroscopy data to enable quantitative analysis from analytical calibration curves. Examples are shown of how to perform surface mapping of silicone contamination. Finally, a brief discussion is presented on LIBS instrumentation, recommendations for laser parameters and instrumentation components, and LIBS technique maturity

Rodolfo I. Ledesma↗

Liquid crystal devices especially for use in liquid crystal point diffraction interferometer systems

Liquid crystal point diffraction interferometer (LCPDI) systems that can provide real-time, phase-shifting interferograms that are useful in the characterization of static optical properties (wavefront aberrations, lensing, or wedge) in optical elements or dynamic, time-resolved events (temperature fluctuations and gradients, motion) in physical systems use improved LCPDI cells that employ a "structured" substrate or substrates in which the structural features are produced by thin film deposition or photo resist processing to provide a diffractive element that is an integral part of the cell substrate(s). The LC material used in the device may be doped with a "contrast-compensated" mixture of positive and negative dichroic dyes.

Marshall, Kenneth L.↗

Surface Characterization of Carbon Fiber Reinforced Polymers by Picosecond Laser Induced Breakdown Spectroscopy

Adhesive bonding of composite materials requires reliable monitoring and detection of surface contaminants as part of a vigorous quality control process to assure robust and durable bonded structures. Surface treatment and effective monitoring prior to bonding are essential in order to obtain a surface which is free from contaminants that may lead to inferior bond quality. In this study, the focus is to advance the laser induced breakdown spectroscopy (LIBS) technique by using pulse energies below 100 μJ (μLIBS) for the detection of low levels of silicone contaminants in carbon fiber reinforced polymer (CFRP) composites. Various CFRP surface conditions were investigated by LIBS using ∼10 ps, 355 nm laser pulses with pulse energies below 30 μJ. Time-resolved analysis was conducted to optimize the gate delay and gate width for the detection of the C I emission line at 247.9 nm to monitor the epoxy resin matrix of CFRP composites and the Si I emission line at 288.2 nm for detection of silicone contaminants in CFRP. To study the surface sensitivity to silicone contamination, CFRP surfaces were coated with polydimethylsiloxane (PDMS), the active ingredient in many mold release agents. The presence of PDMS was studied by inspecting the Si I emission lines at 251.6 nm and 288.2 nm. The measured PDMS areal densities ranged from 0.15 to 2 μg/cm(sup 2). LIBS measurements were performed before and after laser surface ablation. The results demonstrate the successful detection of PDMS thin layers on CFRP using picosecond μLIBS.

Rodolfo Ledesma↗

Instrumentation Working Group Summary

The Instrumentation Working Group compiled a summary of measurement techniques applicable to gas turbine engine aerosol precursors and particulates. An assessment was made of the limits, accuracy, applicability, and technology readiness of the various techniques. Despite advances made in emissions characterization of aircraft engines, uncertainties still exist in the mechanisms by which aerosols and particulates are produced in the near-field engine exhaust. To adequately assess current understanding of the formation of sulfuric acid aerosols in the exhaust plumes of gas turbine engines, measurements are required to determine the degree and importance of sulfur oxidation in the turbine and at the engine exit. Ideally, concentrations of all sulfur species would be acquired, with emphasis on SO2 and SO3. Numerous options exist for extractive and non-extractive measurement of SO2 at the engine exit, most of which are well developed. SO2 measurements should be performed first to place an upper bound on the percentage of SO2 oxidation. If extractive and non-extractive techniques indicate that a large amount of the fuel sulfur is not detected as SO2, then efforts are needed to improve techniques for SO3 measurements. Additional work will be required to account for the fuel sulfur in the engine exhaust. Chemical Ionization Mass Spectrometry (CI-MS) measurements need to be pursued, although a careful assessment needs to be made of the sampling line impact on the extracted sample composition. Efforts should also be placed on implementing non-intrusive techniques and extending their capabilities by maximizing exhaust coverage for line-of-sight measurements, as well as development of 2-D techniques, where feasible. Recommendations were made to continue engine exit and combustor measurements of particulates. Particulate measurements should include particle size distribution, mass fraction, hydration properties, and volatile fraction. However, methods to ensure that unaltered samples are obtained need to be developed. Particulate speciation was also assigned a high priority for quantifying the fractions of carbon soot, PAH, refractory materials, metals, sulfates, and nitrates. High priority was also placed on performing a comparison of particle sizing instruments. Concern was expressed by the workshop attendees who routinely make particulate measurements about the variation in number density measured during in-flight tests by different instruments. In some cases, measurements performed by different groups of researchers during the same flight tests showed an order of magnitude variation. Second priority was assigned to measuring concentrations of odd hydrogen and oxidizing species. Since OH, HO2, H2O2, and O are extremely reactive, non-extractive measurements are recommended. A combination of absorption and fluorescence is anticipated to be effective for OH measurements in the combustor and at the engine exit. Extractive measurements of HO2 have been made in the stratosphere, where the ambient level of OH is relatively low. Use of techniques that convert HO2 to OH for combustor and engine exit measurements needs to be evaluated, since the ratio of HO2/OH may be 1% or less at both the combustor and engine exit. CI-MS might be a viable option for H2O2, subject to sampling line conversion issues. However, H2O2 is a low priority oxidizing species in the combustor and at the engine exit. Two candidates for atomic oxygen measurements are Resonance Enhanced Multi-Photon Ionization (REMPI) and Laser-Induced Fluorescence (LIF). Particulate measurement by simultaneous extractive and non-extractive techniques was given equal priority to the oxidizer measurements. Concern was expressed over the ability of typical ground test sampling lines to deliver an unaltered sample to a remotely located instrument. It was suggested that the sampling probe and line losses be checked out by attempting measurements using an optical or non-extractive technique immediately upstream of the sampling probe. This is a possible application for Laser Induced Incandescence (LII) as a check on the volume fraction of soot. Optical measurements of size distribution are not well developed for ultrafine particles less than about 20 nm in diameter, so a non-extractive technique for particulate size distribution cannot be recommended without further development. Carbon dioxide measurements need to be made to complement other extractive measurement techniques. CO2 measurements enable conversion of other species concentrations to emission indices. Carbon monoxide, which acts as a sink for oxidizing species, should be measured using non-extractive techniques. CO can be rapidly converted to CO2 in extractive probes, and a comparison between extractive and non-extractive measurements should be performed. Development of non-extractive techniques would help to assess the degree of CO conversion, and might be needed to improve the concentration measurement accuracy. Measurements of NO(x) will continue to be critical due to the role of NO and NO2 in atmospheric chemistry, and their influence on atmospheric ozone. Time-resolved measurements of temperature, velocity, and species concentrations were included on the list of desired measurement. Thermocouples are typically adequate for engine exit measurements. PIV and LDV are well established for obtaining velocity profiles. The techniques are listed in the accompanying table; are divided into extractive and non-extractive techniques. Efforts were made to include a measurement uncertainty for each technique. An assessment of the technology readiness was included.

Zaller, Michelle↗

Studies of Minerals, Organic and Biogenic Materials through Time-Resolved Raman Spectroscopy

A compact remote Raman spectroscopy system was developed at NASA Langley Research center and was previously demonstrated for its ability to identify chemical composition of various rocks and minerals. In this study, the Raman sensor was utilized to perform time-resolved Raman studies of various samples such as minerals and rocks, Azalea leaves and a few fossil samples. The Raman sensor utilizes a pulsed 532 nm Nd:YAG laser as excitation source, a 4-inch telescope to collect the Raman-scattered signal from a sample several meters away, a spectrograph equipped with a holographic grating, and a gated intensified CCD (ICCD) camera system. Time resolved Raman measurements were carried out by varying the gate delay with fixed short gate width of the ICCD camera, allowing measurement of both Raman signals and fluorescence signals. Rocks and mineral samples were characterized including marble, which contain CaCO3. Analysis of the results reveals the short (approx.10-13 s) lifetime of the Raman process, and shows that Raman spectra of some mineral samples contain fluorescence emission due to organic impurities. Also analyzed were a green (pristine) and a yellow (decayed) sample of Gardenia leaves. It was observed that the fluorescence signals from the green and yellow leaf samples showed stronger signals compared to the Raman lines. Moreover, it was also observed that the fluorescence of the green leaf was more intense and had a shorter lifetime than that of the yellow leaf. For the fossil samples, Raman shifted lines could not be observed due the presence of very strong short-lived fluorescence.

Garcia, Christopher S.↗

Shockwave/Boundary-Layer Interaction Studies Performed in the NASA Langley 20-Inch Mach 6 Air Tunnel

This paper highlights results from a collaborative study performed by The University of Tennessee Space Institute (UTSI) and NASA Langley Research Center on the Shockwave/Boundary-Layer Interaction (SWBLI) generated by a cylindrical protuberance on a flat plate in a Mach 6 flow. The study was performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center and consisted of two separate entries. In the first entry, simultaneous high-speed schlieren and high-speed pressure-sensitive paint (PSP) imaging – which was performed for the first time in the 20-Inch Mach 6 facility at NASA Langley – were performed as well as simultaneous high-speed schlieren and oil-flow imaging. In the second entry, the model configuration was modified to increase the size of the interaction region. High-speed schlieren and infrared thermography (IR) surface imaging were performed in this second entry. The goal of these tests was to characterize the SBLI in the presence of a laminar, transitional, and turbulent boundary layer using high-speed optical imaging techniques. AoA = sting angle-of-attack (°) dcylinder = cylinder diameter (mm) dtrip = cylindrical tripping element diameter (mm) Δshock = shock stand-off distance (mm) hcylinder = cylinder height (mm) htrip = cylindrical tripping element height (mm) HSS = high-speed schlieren M∞ = freestream Mach number PSP = pressure-sensitive paint Re∞ = freestream unit Reynolds number (m-1) SWBLI = shockwave/boundary-layer interaction θplate = model plate angle (°) Introduction his paper highlights two experimental entries performed in the 20-Inch Mach 6 Air Blowdown Tunnel at NASA Langley Research Center in collaboration with The University of Tennessee Space Institute (UTSI). The purpose of these entries was to characterize the dynamic shockwave/boundary-layer interaction (SWBLI) between a vertical cylinder on a flat plate and laminar, transitional (XSWBLI), and turbulent (SWTBLI) boundary layers with a freestream Mach number of 6 using non-intrusive optical diagnostics. Experiments performed by Murphree et al.1,2 were among the first to specifically characterize XSWBLI induced by a vertical cylinder on a flat plate geometry using several optical measurement techniques. Recent optical studies of XSWBLI phenomenon have been performed by UTSI at Mach 2 in their low-enthalpy blow wind tunnel3-8 and by Texas A&M University and UTSI at Mach numbers of 6 and 7 in their Adjustable Contour Expansion wind tunnel.9 The experiments described in this paper were intended to complement previous studies by expanding the freestream unit Reynolds number range, Re∞, over which the XSWBLI phenomena has been observed. Additionally these experiments, made possible under NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project, promoted collaboration between university and NASA researchers. The initial entry in the 20-Inch Mach 6 Air Tunnel at NASA Langley occurred in December of 2016. Originally, testing was to occur in November of 2016 in the 31-Inch Mach 10 Air Tunnel at NASA Langley. This facility was chosen so that the XSWBLI phenomenon could be observed at much higher Mach numbers than had previously been attempted in ground test experiments. The model selected for this experiment, a 10° half-angle wedge with a sharp leading edge (described in detail in section II.B), had previously been used by Danehy et al. [10] for boundary layer transition studies using the nitric oxide planar laser-induced fluorescence (NO PLIF) flow visualization technique. In that work, it was determined that transition could be induced downstream of a single htrip = 1-mm tall, dtrip = 4-mm diameter cylindrical tripping element and that the streamwise location of the transition could be changed for a single Re∞ by changing the model angle-of-attack (AoA) (see Fig. A3 in Ref. [10] for more details). Based on the findings of that work, a decision was made to use the wedge model with the cylindrical tripping element to trip the boundary layer flow ahead of a cylindrical protuberance in order to achieve a XSWBLI. Unfortunately, the 31-Inch Mach 10 facility had been taken offline for repairs in October of 2016 and a decision was made to move the test to the 20-Inch Mach 6 facility. Since the behavior of the boundary layer with the chosen model configuration had not been studied before in that facility and the available test time was limited, the entry was considered to be exploratory and was used to collect spatially-resolved and time-resolved flow and surface visualization data that would be used to inform a second entry. Test techniques included simultaneous high-speed schlieren (HSS) captured at 160 kHz and high-speed pressure sensitive paint captured at 10 kHz as well as oil flow visualization, captured at 750 Hz. The second entry in the 20-Inch Mach 6 facility occurred in June and July of 2017. In this follow-on test, modifications to the wind tunnel model were made based on observations made during the first entry and included removing the cylindrical tripping element, increasing the size of the cylinder used to induce the SWBLI to increase the size of the interaction while simultaneously improving spatial resolution, and using a swept ramp array, similar to that described in Ref. [11], to trip the flow to turbulence. Simultaneous HSS (captured at 140 kHz, 100 kHz, and 40 kHz) and conventional IR thermography (captured at 30 Hz) imaging were performed simultaneously in this follow-on entry. This paper is intended to serve as a summary of the work performed during these two entries, to detail lessons learned from each entry, and to highlight some of the datasets acquired. Details on the experimental setup, model configuration, and techniques used are provided. Papers providing a more rigorous analysis of data acquired during the second entry, including statistical, spectral, and modal decomposition methods, can be found in Refs. [12,13]. An entry examining XSWBLI in the 31-Inch Mach 10 Blowdown Wind Tunnel facility is currently planned for mid-to-late calendar year 2019, pending the success of facility repairs. The work performed and described in this paper and the upcoming entry in the 31-Inch Mach 10 facility at NASA Langley have been made possible by NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project. Wind Tunnel Facility All experiments discussed in this paper were performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center. Specific details pertaining to this facility can be found in Refs. [14,15], with only a brief description of the facility provided here. For both entries, the nominal freestream unit Reynolds number was varied between 1.8×106 m-1 (0.5×106 ft-1) and 26.3×106 m-1 (8×106 ft-1). The nominal stagnation pressure was varied between 0.21 MPa and 3.33 MPa and the nominal stagnation temperature was varied between 480 K and 520 K to achieve the desired Re∞ condition. For all runs, the nominal freestream Mach number was 6. The nearly square test section is 520.7-mm (20.5-inches) wide by 508-mm (20-inches) high. Two 431.8-mm (17-inch) diameter windows made of Corning 7940, Grade 5F schlieren-quality glass serve as the side walls of the tunnel and provide optical access for the high-speed schlieren measurements. A rectangular window made of the same material as the side windows served as the top wall of the test section and provided optical access for the high-speed PSP and oil flow measurements. For the second entry, this top window was replaced with a Zinc Selenide (ZnSe) window with an anti-reflection coating capable of passing IR wavelengths between 8μm and 12μm with greater than 98% transmittance. The model was sting supported by a strut attached to a hydraulic system that allows for the model pitch angle to be adjusted between -5° to +55°. For the first entry, an initial pitch/pause sweep of the model AoA was performed to observe the resulting SWBLI. Ultimately, however, the sting pitch angle for this entry was fixed at +10.0° so that the angle of the top surface of the wedge relative to the streamwise axis of the tunnel (referred to herein as the plate angle, θplate), was θplate = 0°. For the second entry, θplate = 0° and θplate = -13.25° were initially tested with the swept ramp array (discussed in the following section) to determine which orientation produced conditions most favorable for XSWBLI to occur based on the heating signatures observed over the top surface of the model in the IR thermography images. Based on these initial tests, θplate = -13.25° was set for the remainder of the runs in the second entry. For both entries, any model changes were performed in a housing located beneath the closed test section. Prior to performing a run of the tunnel, the housing was sealed and the tunnel started. Once the appropriate freestream conditions were achieved, the model was injected into the test section using a hydraulic injection system. B. Model Geometry For all runs, a 10° half-angle (20° full-angle) wedge model with a sharp leading edge was used. The model is described in detail in Refs. [10,16]. The top surface of the sharp leading edge of the model extended 47.8 mm from its upstream-most edge to a junction with the upstream edge of a stainless steel top plate that then extended an (a) (c) (b) Fig. 1 (a) Schematic of top surface of wedge model with gas seeding insert, (b) perspective view of the model in the 20-Inch Mach 6 tunnel with centerline pressure orifices on sharp leading edge, and (c) a perspective view of the model with stainless steel (top) and SLA middle insert (bottom) during the first entry. Flow occurs from left to right.

Bathel, Brett F.↗

Spacecraft Material Characterization Using Reflectance Spectra Extracted from RGB/IR Color Images

The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.

Jainisha R. Shah↗

Spacecraft Material Characterization Using Reflectance Spectra Extracted from RGB/IR Color Images

The space environment is detrimental to the exterior of the spacecraft and imposes stringent requirements on spacecraft materials. Space materials are often expected to perform for 15-20 years in the harsh space environment without significant degradation of their optical, electrical, mechanical and thermal properties. Further, as commercial activities increase in the space domain, development of predictive capability for material evolution is critical for agile adaption of novel materials. Therefore, it is very important to understand the effects of the space environments on the spacecraft materials. The Materials on the International Space Station Experiment Flight Facility (MISSE-FF) has flown numerous material samples to investigate the effect of LEO space weather exposure on the performance and durability of materials and devices. We are manifest on the MISSE-16 mission, scheduled to launch in June 2022, to fly fifteen novel and well-characterized materials in the LEO environment for a duration of six months. Changes in spectral reflectivity will be measured in real time throughout the mission with an RGB/IR camera. These time-resolved data will function as a "space-truth" reference for our team's ongoing laboratory-based space weather-material interaction experiments. Correlation of the MISSE-16 data with extensive ground testing of duplicate samples under simulated space weather conditions will enable development of fundamental chemical models for material degradation. This paper discusses preliminary results from the ground test campaign to collect the RGB/IR images for pristine and damaged materials and the development of machine learning algorithms to extract reflectance spectra from the color images.

Jainisha R. Shah↗

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↗

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↗

arcjetCV: automating recession extraction from video

Arc jet Computer Vision (arcjetCV)[1][2] is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV 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.

Recession tracking↗

ArcjetCV: Automating Recession Tracking

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV 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.

Recession tracking↗

ArcjetCV: Automating Arc Jet Analysis

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV 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.

Recession tracking↗