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At least 667 records · Page 37

The application of CRM to military operations

The detailed content of the CRM training component of the C-5 Aircrew Training System (ATS) was left to the discretion of the contractor. As a part of determining what the content should be, United Airlines Services Corporation has made an effort to understand how the needs of MAC crews compare with those of civilian airline crews. There are distinct similarities between the crew roles in the cockpits of civilian airliners and military air transports. Many of the attitudes and behaviors exhibited by civil and military crew members are comparable, hence much of the training in the field referred to as Cockpit Resource Management (CRM) is equally appropriate to civil or military aircrews. At the same time, there are significant differences which require assessment to determine if modifications to what might be termed generic CRM are necessary. The investigation enabled the definition and specification of CRM training which is believed to address the needs of the C-5 operational community. The study has concentrated largely on military airlift, but the training objectives and course content of the CRM training are readily adaptable to a wider range of military cockpits than are found in strategic airlift. For instance, CRM training focusing on communication, leadership, situational awareness, and crew coordination is just as appropriate, with some modification, to the pilots manning a flight to Tactical Airlift Command A-7's as it is to the pilots, flight engineers, and loadmasters crewing a C-5.

Cavanagh, Dale E.↗

Infrastructure for Training and Partnershipes: California Water and Coastal Ocean Resources

The purpose of this project was to advance the existing ICESS/Bren School computing infrastructure to allow scientists, students, and research trainees the opportunity to interact with environmental data and simulations in near-real time. Improvements made with the funding from this project have helped to strengthen the research efforts within both units, fostered graduate research training, and helped fortify partnerships with government and industry. With this funding, we were able to expand our computational environment in which computer resources, software, and data sets are shared by ICESS/Bren School faculty researchers in all areas of Earth system science. All of the graduate and undergraduate students associated with the Donald Bren School of Environmental Science and Management and the Institute for Computational Earth System Science have benefited from the infrastructure upgrades accomplished by this project. Additionally, the upgrades fostered a significant number of research projects (attached is a list of the projects that benefited from the upgrades). As originally proposed, funding for this project provided the following infrastructure upgrades: 1) a modem file management system capable of interoperating UNIX and NT file systems that can scale to 6.7 TB, 2) a Qualstar 40-slot tape library with two AIT tape drives and Legato Networker backup/archive software, 3) previously unavailable import/export capability for data sets on Zip, Jaz, DAT, 8mm, CD, and DLT media in addition to a 622Mb/s Internet 2 connection, 4) network switches capable of 100 Mbps to 128 desktop workstations, 5) Portable Batch System (PBS) computational task scheduler, and vi) two Compaq/Digital Alpha XP1000 compute servers each with 1.5 GB of RAM along with an SGI Origin 2000 (purchased partially using funds from this project along with funding from various other sources) to be used for very large computations, as required for simulation of mesoscale meteorology or climate.

Siegel, David A.↗

Assessment Overview: Regional Impacts of Using the Day Cloud Phase Distinction RGB for Lightning IDSS

The new generation of GOES satellites has presented a wealth of novel observations and data products to the National Weather Service forecasters throughout the country. While high quality, low latency data is always welcome in operational environments, it is valuable to understand how new information is interpreted, and how it complements and supplements existing datasets. To that end, NASA SPoRT, in partnership with the NWS, hosted a formal assessment of the use of the Day Cloud Phase Distinction RGB to anticipate lightning initiation as indicated by either GLM, NLDN, or both, using an approach outlined by Elsenheimer and Gravelle (2019). As is typical for SPoRT assessments, we focused on a targeted time period (about 6 weeks in June and July 2021) and provided a brief training module to help forecasters become familiar with the application we were targeting and the objectives of our assessment. Unlike typical SPoRT assessments, we focused on a broad geographic region, coordinating with NWS Regional offices to garner participation from several different WFOs throughout the country. Given the field of view and observation angles of GOES-East and GOES-West, which anecdotally impacts GLM lightning observations in particular, having a geographically diverse participant list helps us interpret how these viewing differences may impact interpretation of the RGB and its value in anticipating lightning. Not unexpectedly, we found that the participating forecasters expressed that they could readily interpret the RGB to recognize glaciation and, in the absence of lightning data, use the RGB to anticipate that lightning was possible, for the purpose of impact-based decision support services (IDSS). Lead times from observations of glaciation to first flash were 19 minutes on average, and -10C isothermal reflectivities ranged from 34.5 to 52.5 dBZ. Herein, we present the detailed results of the formal assessment period and provide next steps and recommendations based on forecaster feedback for using the DCPD RGB in the context of anticipating lightning initiation and for IDSS, including regional differences in observations.

satellite remote sensing↗

Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

Kateb, Babak↗

Jake Garn Mission Simulator and Training Facility, Building 5, Historical Documentation

In response to President George W. Bush's announcement in January 2004 that the Space Shuttle Program (SSP) would end in 2010, the National Aeronautics and Space Administration (NASA) completed a nation-wide historical survey and evaluation of NASA-owned facilities and properties (real property assets) at all its Centers and component facilities. The buildings and structures which supported the SSP were inventoried and assessed as per the criteria of eligibility for listing in the National Register of Historic Places (NRHP) in the context of this program. This study was performed in compliance with Section 110 of the National Historic Preservation Act (NHPA) of 1966 (Public Law 89-665), as amended; the National Environmental Policy Act (NEPA) of 1969 (Public Law 91-190); Executive Order (EO) 11593: Protection and Enhancement of the Cultural Environment; EO 13287, Preserve America, and other relevant legislation. As part of this nation-wide study, in September 2006, historical survey and evaluation of NASA-owned and managed facilities at was conducted by NASA's Lyndon B. Johnson Space Center (JSC) in Houston, Texas. The results of this study are presented in a report entitled, "Survey and Evaluation of NASA-owned Historic Facilities and Properties in the Context of the U.S. Space Shuttle Program, Lyndon B. Johnson Space Center, Houston, Texas," prepared in November 2007 by NASA JSC's contractor, Archaeological Consultants, Inc. As a result of this survey, the Jake Gam Mission Simulator and Training Facility (Building 5) was determined eligible for listing in the NRHP, with concurrence by the Texas State Historic Preservation Officer (SHPO). The survey concluded that Building 5 is eligible for the NRHP under Criteria A and C in the context of the U.S. Space Shuttle program (1969-2010). Because it has achieved significance within the past 50 years, Criteria Consideration G applies. At the time of this documentation, Building 5 was still used to support the SSP as an astronaut training facility. This documentation package precedes any undertaking as defined by Section 106 of the NHPA, as amended, and implemented in 36 CFR Part 800, as NASA JSC has decided to proactively pursue efforts to mitigate the potential adverse affects of any future modifications to the facility. It includes a historical summary of the Space Shuttle program; the history of JSC in relation to the SSP; a narrative of the history of Building 5 and how it supported the SSP; and a physical description of the structure. In addition, photographs documenting the construction and historical use of Building 5 in support of the SSP, as well as photographs of the facility documenting the existing conditions, special technological features, and engineering details, are included. A contact sheet printed on archival paper, and an electronic copy of the work product on CD, are also provided.

Slovinac, Trish↗

Extreme Tele-Echocardiography: Methodology for Remote Guidance of In-flight Echocardiography Aboard the International Space Station

Echocardiography is ideally suited for cardiovascular imaging in remote environments, but the expertise to perform it is often lacking. In 2001, an ATL HDI5000 was delivered to the International Space Station (ISS). The instrument is currently being used in a study to investigate the impact of long-term microgravity on cardiovascular function. The purpose of this report is to describe the methodology for remote guidance of echocardiography in space. Methods: In the year before launch of an ISS mission, potential astronaut echocardiographic operators participate in 5 sessions to train for echo acquisitions that occur roughly monthly during the mission, including one exercise echocardiogram. The focus of training is familiarity with the study protocol and remote guidance procedures. On-orbit, real-time guidance of in-flight acquisitions is provided by a sonographer in the Telescience Center of Mission Control. Physician investigators with remote access are able to relay comments on image optimization to the sonographer. Live video feed is relayed from the ISS to the ground via the Tracking and Data Relay Satellite System with a 2 second transmission delay. The expert sonographer uses these images along with two-way audio to provide instructions and feedback. Images are stored in non-compressed DICOM format for asynchronous relay to the ground for subsequent off-line analysis. Results: Since June, 2009, a total of 19 resting echocardiograms and 4 exercise studies have been performed in-flight. Average acquisition time has been 45 minutes, reflecting 26,000 km of ISS travel per study. Image quality has been adequate in all studies, but remote guidance has proven imperative for fine-tuning imaging and prioritizing views when communication outages limit the study duration. Typical resting studies have included 12 video loops and 21 still-frame images requiring 750 MB of storage. Conclusions: Despite limited crew training, remote guidance allows research-quality echocardiography to be performed by non-experts aboard the ISS. Analysis is underway and additional subjects are being recruited to define the impact of microgravity on cardiac structure and systolic and diastolic function.

Martin, David↗

Extreme Tele-Echocardiography: Methodology for Remote Guidance of In-Flight Echocardiography Aboard the International Space Station

Methods: In the year before launch of an ISS mission, potential astronaut echocardiographic operators participate in 5 sessions to train for echo acquisitions that occur roughly monthly during the mission, including one exercise echocardiogram. The focus of training is familiarity with the study protocol and remote guidance procedures. On-orbit, real-time guidance of in-flight acquisitions is provided by a sonographer in the Telescience Center of Mission Control. Physician investigators with remote access are able to relay comments on image quality to the sonographer. Live video feed is relayed from the ISS to the ground via the Tracking and Data Relay Satellite System with a 2- second transmission delay. The expert sonographer uses these images, along with twoway audio, to provide instructions and feedback. Images are stored in non-compressed DICOM format for asynchronous relay to the ground for subsequent off-line analysis. Results: Since June, 2009, a total of 27 resting echocardiograms and 5 exercise studies have been performed during flight. Average acquisition time has been 45 minutes, reflecting 26,000 km of ISS travel per study. Image quality has been adequate in all studies, and remote guidance has proven imperative for fine-tuning imaging and prioritizing views when communication outages limit the study duration. Typical resting studies have included 27 video loops and 30 still-frame images requiring 750 MB of storage. Conclusions: Despite limited crew training, remote guidance allows research-quality echocardiography to be performed by non-experts aboard the ISS. Analysis is underway and additional subjects are being recruited to define the impact of microgravity on cardiac structure and systolic and diastolic function.

Martin, David S.↗

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Pretlow, Robert A., III↗

Skylab simulator visual displays and training for joint observing programs

The complexity of the Skylab Apollo Telescope Mount (ATM) experiment operations necessitated the use of high fidelity simulations of the onboard visual displays and pointing system for crew training. The displays which were simulated included the H-alpha displays, XUV monitor display, XUV/slit/white light display, X-ray image display, and the white light coronagraph display. The pointing simulation was achieved by projecting film sequences which were subsequently viewed by TV cameras. An optical system in front of the vidicons simulated the pointing, roll, and zoom capabilities of the ATM and sensing systems. The simulation enabled the Skylab crewmen to obtain valuable integrated training combining such tasks as target recognition and status assessment, complex and the time dependent pointing operations, malfunction analyses, and rapid responses to flare and other transient events.

Holt, A. C.↗

SETI Pulse Detection Algorithm: Analysis of False-alarm Rates

Some earlier work by the Search for Extraterrestrial Intelligence (SETI) Science Working Group (SWG) on the derivation of spectrum analyzer thresholds for a pulse detection algorithm based on an analysis of false alarm rates is extended. The algorithm previously analyzed was intended to detect a finite sequence of i periodically spaced pulses that did not necessarily occupy the entire observation interval. This algorithm would recognize the presence of such a signal only if all i-received pulse powers exceeded a threshold T(i): these thresholds were selected to achieve a desired false alarm rate, independent of i. To simplify the analysis, it was assumed that the pulses were synchronous with the spectrum sample times. This analysis extends the earlier effort to include infinite and/or asynchronous pulse trains. Furthermore, to decrease the possibility of missing an extraterrestrial intelligence signal, the algorithm was modified to detect a pulse train even if some of the received pulse powers fall below the threshold. The analysis employs geometrical arguments that make it conceptually easy to incorporate boundary conditions imposed on the derivation of the false alarm rates. While the exact results can be somewhat complex, simple closed form approximations are derived that produce a negligible loss of accuracy.

Levitt, B. K.↗

Learning time series for intelligent monitoring

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

Manganaris, Stefanos↗

Interactive Media and Simulation Tools for Technical Training

Over the last several years, integration of multiple media sources into a single information system has been rapidly developing. It has been found that when sound, graphics, text, animations, and simulations are skillfully integrated, the sum of the parts exceeds the individual parts for effective learning. In addition, simulations can be used to design and understand complex engineering processes. With the recent introduction of many high-level authoring, animation, modeling, and rendering programs for personal computers, significant multimedia programs can be developed by practicing engineers, scientists and even managers for both training and education. However, even with these new tools, a considerable amount of time is required to produce an interactive multimedia program. The development of both CD-ROM and Web-based programs are discussed in addition to the use of technically oriented animations. Also examined are various multimedia development tools and how they are used to develop effective engineering education courseware. Demonstrations of actual programs in engineering mechanics are shown.

Gramoll, Kurt↗

Task Analytic Models to Guide Analysis and Design: Use of the Operator Function Model to Represent Pilot-Autoflight System Mode Problems

Task-analytic models structure essential information about operator interaction with complex systems, in this case pilot interaction with the autoflight system. Such models serve two purposes: (1) they allow researchers and practitioners to understand pilots' actions; and (2) they provide a compact, computational representation needed to design 'intelligent' aids, e.g., displays, assistants, and training systems. This paper demonstrates the use of the operator function model to trace the process of mode engagements while a pilot is controlling an aircraft via the, autoflight system. The operator function model is a normative and nondeterministic model of how a well-trained, well-motivated operator manages multiple concurrent activities for effective real-time control. For each function, the model links the pilot's actions with the required information. Using the operator function model, this paper describes several mode engagement scenarios. These scenarios were observed and documented during a field study that focused on mode engagements and mode transitions during normal line operations. Data including time, ATC clearances, altitude, system states, and active modes and sub-modes, engagement of modes, were recorded during sixty-six flights. Using these data, seven prototypical mode engagement scenarios were extracted. One scenario details the decision of the crew to disengage a fully automatic mode in favor of a semi-automatic mode, and the consequences of this action. Another describes a mode error involving updating aircraft speed following the engagement of a speed submode. Other scenarios detail mode confusion at various phases of the flight. This analysis uses the operator function model to identify three aspects of mode engagement: (1) the progress of pilot-aircraft-autoflight system interaction; (2) control/display information required to perform mode management activities; and (3) the potential cause(s) of mode confusion. The goal of this paper is twofold: (1) to demonstrate the use of the operator functio model methodology to describe pilot-system interaction while engaging modes And monitoring the system, and (2) to initiate a discussion of how task-analytic models might inform design processes. While the operator function model is only one type of task-analytic representation, the hypothesis of this paper is that some type of task analytic structure is a prerequisite for the design of effective human-automation interaction.

Degani, Asaf↗

Cyrano "Nose" The Smell of Success

Cyrano Sciences, Inc. has commercialized a simple, accurate, non- invasive tool that enables "machines to smell". The Cyranose 320 is used for quality control purposes in the food and chemical industries. Using a sensor array and onboard pattern recognition algorithms, the lightweight, portable device works by exposing an array of polymer composite sensors to the chemical components in a vapor. When the sensors come in contact with the vapor, the polymer expands like a sponge, changing the resistance of the composites. The change in resistance is measured, and from that measurement, the presence of a pre-trained substance is determined with a quick and accurate diagnosis. This real-time, portable device enables food companies to spot test raw materials for batch-to-batch consistency, spoilage, or contamination. The Cyranose 320 is also used by chemical and petrochemical companies for quick assessment of the chemical status associated with various industrial processes. Profiling a chemical environment in a hazardous materials situation allows emergency crews to accurately select fire retardants, containment strategies, and protective gear. Future applications for the Cyranose 320 are fast growing and other uses of this technology are on the horizon.

Source record↗

Role of physical countermaneuvers in the management of orthostatic hypotension: efficacy and biofeedback augmentation

OBJECTIVE: To evaluate the efficacy of various physical countermaneuvers in reducing orthostatic hypotension and its associated symptoms and to assess the efficacy of biofeedback training in enhancing the effectiveness of physical countermaneuvers. MATERIAL AND METHODS: In nine study subjects with neurogenic orthostatic hypotension, four training sessions on physical countermaneuvers were performed after tilt-up, three with visual feedback on the effect of physical countermaneuvers on blood pressure and other cardiovascular variables. Blood pressure change and orthostatic symptoms during tilt-up were determined, as were the changes in total peripheral resistance, stroke index, and heart rate. RESULTS: The five female and four male patients had a mean age of 53 years and a mean duration of symptoms of 4.2 years. On an orthostatic symptom scale of 0 to 10, these patients had a mean symptom score of 7.3. The increment in systolic blood pressure was better for some maneuvers (such as leg crossing and a combination) than others (such as neck flexion and abdominal contraction). Three patterns of responses to biofeedback were found. Simple maneuvers such as squatting did not improve with training; visual feedback was needed for maneuvers such as thigh contraction, and performance declined without biofeedback; the third pattern, seen in maneuvers such as leg crossing, showed continued improvement with training, even without biofeedback. A survey at 3 to 4 months after training revealed continued use of physical maneuvers (3.8 +/- 3.1 per day), increased standing time with each episode of presyncopal symptoms (8.3 +/- 5.8 minutes), and continued global symptomatic improvement. Total peripheral resistance, but not heart rate or stroke index, showed significant regression with blood pressure improvement. CONCLUSION: Physical countermaneuvers are efficacious in reducing orthostatic hypotension, can be augmented by use of biofeedback, and may significantly improve the functional outcome. The major mechanism of improvement is an increase in total peripheral resistance, presumably by reducing the vascular capacitance.

NASA Program Space Physiology and Countermeasures↗

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM for digital-to-optical correlation-filter data conversion, and a charge-coupled device (CCD) for detection of correlation peaks. In operation, the input scene grabbed by a video sensor is streamed into the input SLM. Precomputed correlation-filter data files representative of known targets are then downloaded and sequenced into the filter SLM at a rate of 1,000 Hz. When there occurs a match between the input target data and one of the known-target data files, the CCD detects a correlation peak at the location of the target. Distortion- invariant correlation filters from a bank of such filters are then sequenced through the optical correlator for each input frame. The net result is the rapid preliminary recognition of one or a few targets.

Moynihan, Philip↗

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗

New Tools for Automating Arcjet Sample Recession Tracking and Analysis

Arcjet Computer Vision (arcjetCV) has been significantly upgraded to enhance accuracy and performance in tracking material recession and shock-material standoff in test videos. These improvements include integrating new machine learning models, developing a specialized edge detection class, and incorporating a more comprehensive training dataset. These upgrades have refined the software’s ability to automate time-resolved recession tracking, making it more precise and reliable for analyzing complex physical processes. In parallel, a new tool called STARscan (Spatial Targeting and Alignment Rig for Scanning) is being developed to capture detailed 3D surface data before and after testing. By comparing these pre- and post-test scans with arcjetCV’s automated video analysis results, users can achieve a more comprehensive assessment of material recession. This method enables cross-validation of results, improving confidence in the analysis of tested materials. The expanded capabilities of arcjetCV have been successfully demonstrated on videos from various facilities, including the NASA Ames arcjets, UIUC’s PlasmatronX, and the VKI Plasmatron. It has been adopted as a new standard for in-situ recession tracking by the Mars Sample Return Project and Orion. ArcjetCV’s improved efficiency and accuracy are critical for reducing testing uncertainties and validating heatshield material performance under extreme conditions. The software’s user-friendly graphical interface ensures ease of use, enabling seamless processing and precise analysis of arcjet videos, providing deeper insights into material behavior in hypersonic environments. ArcjetCV is now available on both PyPI and Conda, allowing easy installation via "pip install arcjetCV" or through the Conda package manager, ensuring broad accessibility and streamlined deployment for users across various platforms.

Ablation↗