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441 records · Page 25

Anomaly Recovery and the Mars Exploration Rovers

The premise of the design of operations for the Mars Exploration Rovers (MER) is that the vehicles will drive each day. As a result, they will encounter some aspect of the terrain environment that cannot be anticipated or otherwise accommodated by the sequences linked onboard that day. The operations team then must correct the problem by planning then commanding the execution of a different drive the next day. Often other aspects of the operation on the surface of Mars: environmental changes, component degradation, errors in sequence design or execution, etc., lead to anomalies which must be addressed before normal operations can resume. The operational design that makes it possible to recover from a driving error each day also reduces the time needed to recover from anomalies. As an example of the efficiency achieved, less than 5% (about 30 sols out of 700 sols of operations) of the time on the surface has been devoted to recovery from anomalies for each vehicle. In this paper the major anomalies experienced by the MER rovers will be recounted and the streamlined approaches to addressing these problems described. The operational flexibility developed for these missions is also a function of the system design that anticipated a number of likely faults and conditions arising from uncertainty in sequence execution and environmental change. This design will be described as well as the considerations in operation that motivated this design. These considerations will likely be present in any future surface mission.

rovers↗

Automatic Alignment of Displacement-Measuring Interferometer

A control system strives to maintain the correct alignment of a laser beam in an interferometer dedicated to measuring the displacement or distance between two fiducial corner-cube reflectors. The correct alignment of the laser beam is parallel to the line between the corner points of the corner-cube reflectors: Any deviation from parallelism changes the length of the optical path between the reflectors, thereby introducing a displacement or distance measurement error. On the basis of the geometrical optics of corner-cube reflectors, the length of the optical path can be shown to be L = L(sub 0)cos theta, where L(sub 0) is the distance between the corner points and theta is the misalignment angle. Therefore, the measurement error is given by DeltaL = L(sub 0)(cos theta - 1). In the usual case in which the misalignment is small, this error can be approximated as DeltaL approximately equal to -L(sub 0)theta sup 2/2. The control system (see figure) is implemented partly in hardware and partly in software. The control system includes three piezoelectric actuators for rapid, fine adjustment of the direction of the laser beam. The voltages applied to the piezoelectric actuators include components designed to scan the beam in a circular pattern so that the beam traces out a narrow cone (60 microradians wide in the initial application) about the direction in which it is nominally aimed. This scan is performed at a frequency (2.5 Hz in the initial application) well below the resonance frequency of any vibration of the interferometer. The laser beam makes a round trip to both corner-cube reflectors and then interferes with the launched beam. The interference is detected on a photodiode. The length of the optical path is measured by a heterodyne technique: A 100- kHz frequency shift between the launched beam and a reference beam imposes, on the detected signal, an interferometric phase shift proportional to the length of the optical path. A phase meter comprising analog filters and specialized digital circuitry converts the phase shift to an indication of displacement, generating a digital signal proportional to the path length.

Halverson, Peter↗

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed for warm waters (25 C). To achieve the required 0.2 psu accuracy, the impact of sea surface roughness (e.g. wind-generated ripples) on the observed brightness temperature has to be corrected to better than one tenth of a degree Kelvin. With this algorithm, the accuracy of retrieved wind speed will be high, varying from a few tenths to 0.6 m/s. The expected direction accuracy is also excellent (less than 10 ) for mid to high winds, but degrades for lower speeds (less than 7 m/s).

Yueh, Simon H.↗

The Cognition Battery: Developing a Normative Database for Spaceflight and Examining the Impact of Prolonged Isolation and Confinement on Cognitive Performance

INTRODUCTION: Astronauts on future long duration space exploration will be required to execute complex tasks in which even minor errors could have devastating consequences. Intact cognition is critical to maintain exceptional performance standards and it is possible that variability even at the highest ends of the performance spectrum will impact operational tasks. Exposure to spaceflight hazards could compromise cognitive performance, and decrements have been documented under conditions of altered gravity and radiation exposure. The cognitive impacts of prolonged isolation and confinement remain relatively unknown. Traditional neuropsychological assessments cannot support earth independent monitoring, do not have normative comparisons for high functioning individuals, and most are not sensitive enough to detect small performance decrements. The Cognition Battery was developed to address these limitations but currently lacks comprehensive normative data. In this project, we aimed to 1) develop a preliminary normative database for astronauts and astronaut surrogates using the Cognition Battery, and 2) characterize differences in cognitive performance after short and long duration analog missions. PARTICIPANTS & METHODS: We assessed baseline cognitive performance by administering the Cognition Battery to 97 astronaut and astronaut surrogates recruited to approximate astronaut demographics (mean age: 39.38, SD=7.62; 35.1% female; 91.7% advanced degrees). For aim 1, we calculated speed and accuracy outcomes for each subtest and summarized the data with descriptive statistics. We examined the relationship between age and performance with Pearsons’s correlations and the relationship between gender and performance with independent samples t-tests. A subset of individuals on short duration (n=48; mean age: 38.18, SD=7.14; 37.5% female; 91.7% advanced degrees) missions of 45 days and long duration (n=34; mean age: 42.12, SD=8.39; 38.2% female; 94.1% advanced degrees) missions ranging from 4-8 months were administered the Cognition Battery during and after their respective missions. For aim 2, we accounted for practice effects using published corrections, and z-transformed post-mission scores using the full sample’s baseline scores. One-way analysis of covariance tests determined the main effect of analog duration on post-mission performance, after accounting for age and gender. The False Discovery Rate method was applied to adjust for multiple comparisons. RESULTS: In the full normative sample, older age was associated with slower reaction times on a processing speed task (r=.39, p=.02), and men were more accurate on processing speed (t=-2.19, p=.03) and faster on sustained attention (t=2.02, p=.049) and risk-taking tasks (t=2.49, p=.02). We observed a main effect of duration on performance on tasks of visual memory (f(1)=5.62, p=.04), processing speed (f(1)=5.48, p=.03), and sensorimotor functioning (f(1)=39.52, p < .001), such that slower performance was observed after long duration missions relative to short. Only sensorimotor functioning was significant after adjustments for multiple comparisons (adjusted p<.001). DISCUSSION: The full sample represents the largest dataset of cognitive performance assessed by the Cognition Battery available and can be used for further research in spaceflight and high-performance populations. Relationships between performance and key demographic variables suggest future research that include age and gender stratification is needed. Our results also show minimal changes in cognitive performance between longer and shorter periods of isolation and confinement.

S I Dev↗

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Brzezinski, Amy S.↗

Evaluating Retrieval Algorithm Climate Stability: Estimating 3D Optical Thickness Bias Distributions by Cloud Type

Detecting climate trends on large spatiotemporal scales requires accurate, stable measurements and stable retrieval algorithms. We strive to estimate how time-variant retrieval algorithm biases may impact trend detection. Here we focus on the 3D cloud optical thickness (τc) bias, which is among the largest in passive cloud retrieval algorithms. If this bias is time dependent, a possibility with potential decadal changes in cloud morphology, it may obscure genuine trends in τc. Although previous studies have evaluated the cloud- and sun-view geometry-dependent 3D τc bias on small spatial scales, before our current study none have evaluated the stability of this well-known bias on climate-relevant large spatiotemporal scales. These studies must estimate large scale distributions of the 3D τc bias by cloud type and estimate how cloud type amount may change between two climate states. We employ a novel approach to estimate large scale distributions of 3D τc using a proxy of the bias that quantifies the departure of clouds from satisfying the 1D radiative transfer assumption used in passive τc retrievals. This existing globally-distributed proxy is an angular consistency metric that was developed using fused Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) measurements. Calculating the 3D τc bias and the proxy, for known cloud fields enables us to establish statistical relationships between these two quantities, which can be used to calculate large-scale distributions of the 3D τc bias. This approach limits the number of 3D radiative transfer simulations required to only those needed to estimate a statistical relationship between the 3D τc bias for known cloud fields and a proxy of the bias. It is likely that future studies will be needed to evaluate retrieval algorithm bias stability for other geophysical variables as the community develops climate data records from satellite observations and their retrievals. This must be done in addition to monitoring and correcting measurement errors and uncertainties and understanding their impact on retrieved essential climate variables.

Yolanda Shea↗

Decision Making In A High-Tech World: Automation Bias and Countermeasures

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Mosier, Kathleen L.↗

Precision Oxygen Isotope Measurements of Two C-Rich Hydrated Interplanetary Dust Particles

Introduction: Chondritic-smooth IDPs (Interplanetary Dust Particles) are low porosity objects whose mineralogy is dominated by aqueous alteration products such as Mg-rich phyllosilicates (smectite and serpentine group) and Mg-Fe carbonate minerals. Their hydrated mineralogy combined with low atmospheric entry velocities have been used to infer an origin largely from asteroidal sources. Spectroscopic studies show that the types and abundance of organic matter in CS IDPs is similar to that in CP IDPs. Although CS IDPs show broad similarities to primitive carbonaceous chondrites, only a few particles have been directly linked to specific meteorite groups such as CM and CI chondrites based on the presence of diagnostic minerals. Many CS IDPs however, have carbon contents that greatly exceed that of known meteorite groups suggesting that they either may derive from comets or represent samples of more primitive parent bodies than do meteorites. It is now recognized that many large, dark primitive asteroids in the outer main belt, as well as some trans-Neptunian objects, show spectroscopic evidence for aqueous alteration products on their surfaces. Some CS IDPs exhibit large bulk D enrichments similar to those observed in the cometary CP IDPs. While hydrated minerals in comets have not been unambiguously identified to date, the presence of the smectite group mineral nontronite has been inferred from infrared spectra obtained from the ejecta from comet 9P/Tempel 1 during the Deep Impact mission. Recent observations of low temperature sulfide minerals in Stardust mission samples suggest that limited aqueous activity occurred on comet Wild-2. All of these observations, taken together, suggest that the high-carbon hydrated IDPs are abundant and important samples of primitive solar system objects not represented in meteorite collections. Oxygen isotopic compositions of chondrites reflect mixing between a 16O-rich reservoir and a 17O,18O-rich reservoir produced via mass-independent fractionation. The composition of the 16O-rich reservoir is well constrained but material representing the 17O,18O-rich end-member is rare. Self-shielding models predict that cometary water, presumed to represent this reservoir, should be enriched in 17O and 18O by greater than 200 per mille. The high-carbon hydrated IDPs may be among the best materials available to search for preserved "cometary" H2O signatures. In order to better understand the origin and evolution of these particles, we have obtained 10 hydrated interplanetary dust particles for coordinated mineralogical, isotopic and organic analyses. We have previously reported the results of mineralogical and O isotopic measurements of two hydrated IDPs; here we present results of O isotopic measurements of three additional IDPs. Samples and Methods: Three interplanetary dust particles (L2079C35, L2083D46 and L2083E46) were embedded in S and partially ultramicrotomed into approximately 70 nanometer sections for analysis via transmission electron microscopy (TEM). The remainders of the unsliced particles were removed from S and pressed into high purity Au foil that was cleaned with HF acid and annealed at 800 degrees Centigrade. The pressed IDPs were analyzed via electron microprobe analysis (EPMA) for quantitative bulk chemical analysis. After EPMA analysis, the IDPs were subjected to precision O isotope analysis with the UCLA Cameca IMS-1270 ion probe. A 20 kiloelectronvolt, 0.5 nanoangstrom Cs+ primary beam of approximately 15 micrometers diameter was used for each measurement. Small particles of San Carlos olivine and Burma spinel were pressed into the Au foil for use as standards to correct for instrumental mass fractionation. The detection system was configured for multicollection, with 16O measured on a Faraday cup, and 17O and 18O measured on electron multipliers (EMs). Individual analyses consisted of 15 cycles of 10 seconds per cycle. Additionally, two microtome thin sections were measured for H isotopic compositions with the JSC NanoSIMS 50L ion probe. An 8 picoangstrom, 16 kiloelectronvolt Cs plus primary beam was used. Measurements consisted of H, C, 12C, 16O, and 18O collected with EMs in multicollection. Terrestrial biotite and kerogen were used for isotopic standards. A significant challenge in O isotope measurement of hydrated minerals is the interference from 16OH at mass 17O. We ensured that the 17O and 16OH peaks were fully resolved by using a mass resolution of greater than 7000 and by careful analyses of San Carlos olivine, Burma spinel and chlorite hydrated mineral standards. The hydride was further suppressed with a cold finger attached to an LN2 dewar to trap volatiles in the sample chamber. All sputtered ions were counted (i.e. presputtering was not used); after applying background, yield and deadtime corrections, we performed a change-point analysis on our data via R in order to determine when the sample reached sputtering equilibrium; data points collected prior to the change point were excluded. Change-point analysis was also used to determine whether the IDP had completely sputtered. Results: Mineralogy. IDPs C35 and E46 exhibited hydrated mineralogies, Fe-Ni sulfide grains, nanoglobules and occasional enstatite grains distributed throughout a fine-grained Mg-Fe saponite matrix. C35 also contained breunnerite (Mg,Fe)CO3; solar flare tracks were observed in enstatite, indicating minimal atmospheric entry heating. The mineralogy of D46 is dominated by a large FeS grain with a minor component of adhering silicate material. D46 was strongly heated during atmorpheric entry as evidenced by a well-developed magnetite rim. EPMA analyses show that both C35 and E46 have high carbon contents of 20 weight percentage (approximately 6X CI). D46 contains approximately 6 wt.weight percentage C. A significant amount of the carbon is present as carbon nanoglobules. Results: Hydrogen isotopes: Although the bulk delta D values of both sections of L2079C35 were within error of SMOW (minus 33 plus or minus 19 per mille, 1 plus or minus 14 per mille 1 sigma), several delta D-rich hotspots were also identified, reaching 2000 per mille. As shown in Fig. 1, these hotspots are clearly associated with discrete carbonaceous inclusions that are akin to nanoglobules found in many meteorites and other IDPs. Oxygen Isotopes. Results of the oxygen isotope measurements are shown in Figure 1. The oxygen isotope composition for L2079C35 was delta 18O equals plus11.6 plus or minus 1.9per mille, delta 17O equals plus 7.9 plus or minus 1.9per mille (2 standard errors). The oxygen isotope composition for L2083D46 was delta 18O equals minus 8.1 plus or minus 1.9 per mille, delta 17O equals minus 6.4 plus or minus 3.1 per mille (2 standard errors). The oxygen isotope composition for L2083E46 was delta 18O equals plus 12.0 plus or minus 1.9 per mille, delta 17O equals plus 9.2 plus or minus 2.0 per mille (2 standard errors). Discussion: Despite mineralogical similarities to highly aqueously altered carbonaceous chondrites, the hydrated IDPs we analyzed have oxygen isotopic compositions that are distinct from matrix materials in the CI, CM, and CR chondrites. The IDPs plot along the Young-Russell line, with delta 17O values for C35 and E46 suggestive of interaction with a 16O-poor reservoir. However, we have thus far not observed evidence of extreme 16O-poor reservoirs expected from self-shielding models and observed in Acfer 094 simplectite. The high carbon contents of the IDPs also set them apart from known meteoritic samples. The lack of atmospheric entry heating effects are consistent with low encounter velocities and suggest either an asteroidal source, or a low inclination, low eccentricity cometary origin. Conclusions: The unusual oxygen isotopic compositions, high carbon contents, and the abundance of Drich nanoglobules, together, suggest that the high-carbon, hydrated IDPs are derived from a primitive source that is not yet represented in meteorite collections.

Snead, C. J.↗

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗