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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗

NASA NTRS1997

RIACS

Topics considered include: high-performance computing; cognitive and perceptual prostheses (computational aids designed to leverage human abilities); autonomous systems. Also included: development of a 3D unstructured grid code based on a finite volume formulation and applied to the Navier-stokes equations; Cartesian grid methods for complex geometry; multigrid methods for solving elliptic problems on unstructured grids; algebraic non-overlapping domain decomposition methods for compressible fluid flow problems on unstructured meshes; numerical methods for the compressible navier-stokes equations with application to aerodynamic flows; research in aerodynamic shape optimization; S-HARP: a parallel dynamic spectral partitioner; numerical schemes for the Hamilton-Jacobi and level set equations on triangulated domains; application of high-order shock capturing schemes to direct simulation of turbulence; multicast technology; network testbeds; supercomputer consolidation project.

Oliger, Joseph↗

NASA NTRS1998

Analysis of Autopilot Behavior

Aviation and cognitive science researchers have identified situations in which the pilot's expectations for behavior of autopilot avionics are not matched by the actual behavior of the avionics. These "automation surprises" have been attributed to differences between the pilot's model of the behavior of the avionics and the actual behavior encoded in the avionics software. A formal technique is described for the analysis and measurement of the behavior of the cruise pitch modes of a modern Autopilot. The analysis characterizes the behavior of the Autopilot as situation-action rules. The behavior of the cruise pitch mode logic for a contemporary modern Autopilot was found to include 177 rules, including Level Change (23), Vertical Speed (16), Altitude Capture (50), and Altitude Hold (88). These rules are determined based on the values of 62 inputs. Analysis of the rule-based model also shed light on the factors cited in the literature as contributors to "automation surprises."

Sherry, Lance↗

NASA NTRS1993

Reducing the cognitive workload: Trouble managing power systems

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. Mission control operators are well-trained experts but they can not afford to have their attention diverted by extraneous information. During normal operating conditions monitoring the status of the components of a complex system alone is a big task. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe are its potential uses.

Manner, David B.↗

NASA NTRS2016

Characterization of Carbon Dioxide Washout Measurement Techniques in the Mark-III Space Suit

Providing adequate carbon dioxide (CO2) washout is essential to the reduction of risk in performing suited operations. Long term CO2 exposure can lead to symptoms such as headache, lethargy, dizziness, and in severe cases can lead to unconsciousness and death. Thus maintaining adequate CO2 washout in both ground testing and during in flight EVAs is a requirement of current and future suit designs. It is necessary to understand the inspired CO2 of suit wearers such that future requirements for space suits appropriately address the risk of inadequate washout. Testing conducted by the EVA Physiology Laboratory at the NASA Johnson Space Center aimed to characterize a method for noninvasively measuring inspired oronasal CO2 under pressurized suited conditions in order to better inform requirements definition and verification techniques for future CO2 washout limits in space suits. Prior work conducted by the EPL examined several different wearable, respirator style, masks that could be used to sample air from the vicinity surround the nose and mouth of a suited test subject. Previously published studies utilized these masks, some being commercial products and some novel designs, to monitor CO2 under various exercise and flow conditions with mixed results for repeatability and/or consistency between subjects. Based on a meta-analysis of those studies it was decided to test a nasal cannula as it is a commercially available device that is placed directly in the flow path of the user as they breathe. A nasal cannula was used to sample air inhaled by the test subjects during both rest and exercise conditions. Eight subjects were tasked with walking on a treadmill or operating an arm ergometer to reach target metabolic rates of 1000, 2000, and 3000 BTU/hr. Suit pressure was maintained at 4.3 psid for all tests, with supply flow rates of 6, 4, and 2 actual cubic feet per minute depending on the test condition. Each test configuration was conducted twice with subjects breathing either through their nose only, or however they felt comfortable. By restricting breathing through a single orifice, we are able to more accurately define exactly what flow stream the sampled CO2 is taken from. Oronasal CO2 was monitored using real time infrared gas analyzers fed via sample tubes connected to the nasal cannula within the suit. Two additional sampling tubes were placed at the head and chin of the test subject, in an effort to capture CO2 concentrations across the entire flow stream of the Mark-III vent system (flow path is head to neck). Metabolic rate was calculated via the exhaust CO2 concentration and used to adjust subject workload on either the treadmill or arm ergometer until the target was reached. Forward work will aim to characterize the historically accepted minimum ppCO2 in suit during EVA by repeating this study in the Extravehicular Mobility Unit (EMU) space suit. This will help to define washout requirements for future suits, be they NASA (e.g. Z-2) or Commercial Crew designed. Additionally it is important to determine the functional consequences of CO2 exposure during EVA. Severe CO2 symptoms are a result of very high concentration, acute exposures. While long term, low concentration exposures have been shown to result in slight cognitive decline, symptoms resolve upon quickly returning to nominal concentrations and it remains unknown the impact that minor deficits in cognitive performance can have on EVA performance.

Norcross, J.↗

DOE OSTI2025

Advances in Desiccant Wheels for Dehumidification, VOC Mitigation, and CO 2 Removal for Energy-Efficient IAQ Management

Humidity control is pivotal to maintain occupant thermal comfort and suppress mold growth in indoor environments. Furthermore, poor indoor air quality (IAQ) due to the presence of volatile organic compounds (VOCs) and high concentrations (>1,000 ppm) of CO 2 can cause health issues and negatively affect cognitive performance. Therefore, providing high-quality indoor air has gained significant attention over the past decade. Conventional cooling coil and filter-based HVAC systems have limited capability to meet the augmented demand for occupant thermal comfort and high indoor air quality. Moreover, modern buildings are increasingly airtight to save energy, and increasing ventilation to mitigate VOC and CO 2 concentration is discouraged. Separate sensible and latent cooling technology using a rotary desiccant wheel presents a promising solution in this respect. Because of the development of desiccant materials with high water vapor, VOC, and CO 2 uptake, desiccant wheels can be used as an integrated technology option for IAQ management. Here, to promote desiccant wheel use for energy-efficient management of IAQ in buildings, this article reviews recent advancements in using desiccant wheels for dehumidification, VOC mitigation, and CO 2 capture from outdoor air. Finally, the article presents the authors’ perspective by summarizing the key research gaps in the field and discussing the future direction of research to address these gaps from two different aspects, namely, suitable adsorbent material development and desiccant wheel design.

CO2 capture↗

NASA NTRSDate not supplied

The Doppler Wind Temperature Sensor (DWTS) Flight Evaluation and Experiments (TES-16, 17)

The Doppler Wind and Temperature Sounder instrument (DWTS), developed by Global Atmospheric Technologies and Sciences (GATS), is a simple but powerful tool that has the potential to become a new window through which to study the dynamics of the upper atmosphere. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, the DWTS instrument infers wind velocities and kinetic temperatures through the stratosphere and lower thermosphere. The DWTS achieves this scanning by measuring the induced Doppler shift and Doppler broadening of emissions as they pass through the DWTS field of view (Gordley, et al., 2011). The DWTS holds promise in improving accuracy in weather determination , and the core technology can be adapted to study other planetary atmospheres. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano Orbital Workshop group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible nanosatellite payload. The first mission selected for DWTS evaluation is preparing for flight in early 2024, which will be followed by a more capable science mission in 2025, with both missions being part of the TES-n/NOW heritage flight series. The first rapid technology demonstration flight, TES-16/DWTS-A, will demonstrate a single DWTS instrument in an approximately 2U payload volume with the imaging aperture perpendicular to the flight velocity vector. With an estimated power consumption of 50 watts, supplied via a custom NOW-designed DC-DC converter, the instrument will maintain the imaging sensor plane at 80K during instrument evaluation periods using an integrated pulse-tube cryocooler. Data from DWTS will be captured and processed via a NOW-designed custom data interface unit before being transmitted via S-band radio back to select ground stations, with instrument command and control operated via L-band global-coverage radio. The subsequent TES-17/DWTS-B mission will be a dedicated science mission to obtain full altitude coverage from 20 to 200 km during both day and night, all from a single small-satellite equipped with three DWTS instruments, each hosting a different gas cell chemistry. The intention of this flight series, and one of NASA’s interests in this instrument, is to advance a Martian atmospheric instrument (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric behavior. The proposed paper will review the flight series in detail, including challenges facing the TES-16 flight tests and the projected challenges and application to Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center will also be discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

nanosatellite↗

NASA NTRSDate not supplied

The Doppler Wind Temperature Sensor (DWTS) Flight Evaluation and Experiments (TES-16,17)

The Doppler Wind Temperature Sensor instrument (DWTS), developed by Global Atmospheric Technologies and Sciences (GATS), is a powerful yet simple tool with the potential of becoming a new window to upper atmosphere dynamics. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, the DWTS is designed to measure the fingerprints of wind and thermal waves as they propagate to the mesosphere and lower thermosphere. DWTS achieves this scanning by measuring the induced change in the doppler shift of the emission as it passes through the DWTS field of view. DWTS holds promise to aid in more accurate weather determination (Gordley, et al), and the core technology can be easily adapted to study other atmospheres of interest. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano Orbital Workshop group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible cube satellite payload. The first mission selected for DWTS evaluation is preparing for flight in early 2024, followed by a more capable science mission in 2025, with both missions part of the TES-n/NOW flight series. The first flight, TES-16/DWTS-A, will incorporate a single DWTS instrument in an approximately 2U payload volume with the imaging aperture perpendicular to the flight velocity vector. With an estimated power consumption of 20 watts, supplied via a custom NOW-designed GaN converter, the instrument will maintain the imaging sensor plane at 80K using an integrated pulse-tube cryocooler during instrument evaluation periods. Data from DWTS will be captured via a NOW-designed custom data processor before being transmitted via S-band radio back to select ground stations, with instrument command and control operated via L-band global-coverage radio. After the TES-16/DWTS-A initial demonstration mission, the subsequent TES-17/DWTS-B mission will be a dedicated science mission equipped with three DWTS instruments, each hosting a different gas cell to obtain full altitude coverage from 20 to 200 km both day and night from a single cube satellite. The intention of the flight series, and one of NASA’s interests in the instrument, is to advance a Martian atmospheric instrument (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric behavior. The proposed paper will review the flight series in detail, including challenges from the TES-16 flight tests and the projected challenges and application to Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center will also be discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

Doppler Wind Temperature Sensor↗

NASA NTRS2014

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.↗

NASA NTRS2017

Behavioral Health and Performance Laboratory Standard Measures (BHP-SM)

The Spaceflight Standard Measures is a NASA Johnson Space Center Human Research Project (HRP) project that proposes to collect a set of core measurements, representative of many of the human spaceflight risks, from astronauts before, during and after long-duration International Space Station (ISS) missions. The term "standard measures" is defined as a set of core measurements, including physiological, biochemical, psychosocial, cognitive, and functional, that are reliable, valid, and accepted in terrestrial science, are associated with a specific and measurable outcome known to occur as a consequence of spaceflight, that will be collected in a standardized fashion from all (or most) crewmembers. While such measures might be used to define standards of health and performance or readiness for flight, the prime intent in their collection is to allow longitudinal analysis of multiple parameters in order to answer a variety of operational, occupational, and research-based questions. These questions are generally at a high level, and the approach for this project is to populate the standard measures database with the smallest set of data necessary to indicate further detailed research is required. Also included as standard measures are parameters that are not outcome-based in and of-themselves, but provide ancillary information that supports interpretation of the outcome measures, e.g., nutritional assessment, vehicle environmental parameters, crew debriefs, etc. The project's main aim is to ensure that an optimized minimal set of measures is consistently captured from all ISS crewmembers until the end of Station in order to characterize the human in space. -This allows the HRP to identify, establish, and evaluate a common set of measures for use in spaceflight and analog research to: develop baselines, systematically characterize risk likelihood and consequences, and assess effectiveness of countermeasures that work for behavioral health and performance risk factors. -By standardizing the battery of measures on all crewmembers, it will allow the HRP to evaluate countermeasures that work for one physiological system and ensure another system is not negatively affected. -These measures, named "Standard Measures," will serve as a data repository and be available to other studies under data sharing agreements.

Williams, Thomas J.↗

NASA NTRSDate not supplied

The Doppler Wind and Temperature Sounder (DWTS) Flight Evaluation and Experiments (TES-16,17)

The Doppler Wind and Temperature Sounder instrument (DWTS) developed by Global Atmospheric Technologies and Sciences (GATS) is a simple yet powerful tool with the potential to become a new window through which the study of upper atmosphere dynamics can occur. Based around a defense-grade infrared camera peering through a static gas cell used as a scanning spectral filter, a DWTS instrument can infer wind velocities and kinetic temperatures throughout the stratosphere and lower thermosphere. The DWTS achieves this scanning by measuring the induced Doppler shift and Doppler broadening of emissions as they pass through the DWTS field of view (Gordley, Marshall, 2011). The DWTS holds promise in improving accuracy in weather determination among other terrestrial benefits, and the core technology can be easily adapted to study the dynamics of other planetary atmospheres. In partnership with GATS, NOAA, and other collaborators, NASA Ames and the Nano-Orbital Workshop (NOW) group have been working to evaluate the DWTS instrument on orbit and optimize it as a flexible payload for nanosatellites. The first mission selected for DWTS technical evaluation is preparing for flight in early 2024, which will be followed by a more capable science mission in 2025, with both missions being part of the TES-n/NOW heritage flight series. The first rapid technology demonstration flight, TES-16/DWTS-A, will demonstrate a single DWTS instrument in an approximately 2U payload volume. With an estimated power consumption of 50 watts, the instrument will maintain the imaging sensor plane at 80K during instrument performance evaluation periods using an integrated Stirling cryocooler. Data from DWTS will be captured and processed via a NOW-designed custom data interface unit before being transmitted via S-band radio back to select ground stations, with instrument command and control maintained via L-band global-coverage radio. The subsequent TES-17/DWTS-B mission will be a dedicated science mission tasked with validating the instrument’s full altitude coverage capabilities, currently estimated from 20 to 200 km during both day and night. This new atmospheric observational capability will come from a single small satellite equipped with three DWTS imagers, each hosting a different gas cell chemistry, to form a complete instrument. The intention of this flight series, and one of NASA’s interests in this instrument, is not only to advance Earth atmospheric dynamics, but to advance a Martian atmospheric study instrument as well (Colaprete, Gordley, et al) which, if successful, would greatly further understanding of Martian atmospheric dynamics. This document describes the flight series in detail, including challenges facing the TES-16 flight tests and the projected challenges and application of Mars study. Additional detail regarding the possible applications of a Cognitive Communication technique in current flight development by NOW collaborators at the NASA Glenn Research Center is also discussed, including the implications of using an automated User Initiated Service (UIS) protocol to maximize the data collected per orbit.

DWTS Nano-satellite TES-n↗

NASA NTRSDate not supplied

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

NASA NTRSDate not supplied

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

machine learning↗

NASA NTRS1999

Principal Investigator-in-a-Box

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Young, Laurence R.↗