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At least 289 records · Page 16

An Analysis of the Role of Safety Nets in the National Airspace System

Safe operations of aircraft in the National Airspace System (NAS) may be attributed to many factors, including the application of a variety of safety nets (SNs) as a last line of defense. In preparation for the Next Generation Air Transportation System (NextGen), a review of Aviation Safety Reporting System (ASRS) reports for incidents with positive outcomes was conducted to investigate the importance of current safety nets. The examination of positive outcomes not only shows what went wrong, but also what went right to prevent accidents and “save the day.” More than 400 incident reports for 2015 from the voluntary ASRS reporting database were studied in detail to create event sequence diagrams (ESDs), illustrating the effectiveness of SNs. The developed ESDs are considered top-level, representative models and are limited with respect to being reliably quantitative because they are based on only reports from a single year. The ESDs could offer insights into human systems integration research, such as strategically using technologies as SNs without human interface or alleviating human workload with new technologies to provide resilient recovery from off-nominal conditions ensuring flight safety.

Geuther, Steven↗

Evaluation of a Dispatcher's Route Optimization Decision Aid to Avoid Aviation Weather Hazards

This document describes the results and analysis of the formal evaluation plan for the Honeywell software tool developed under the NASA AWIN (Aviation Weather Information) 'Weather Avoidance using Route Optimization as a Decision Aid' project. The software tool aims to provide airline dispatchers with a decision aid for selecting optimal routes that avoid weather and other hazards. This evaluation compares and contrasts route selection performance with the AWIN tool to that of subjects using a more traditional dispatcher environment. The evaluation assesses gains in safety, in fuel efficiency of planned routes, and in time efficiency in the pre-flight dispatch process through the use of the AWIN decision aid. In addition, we are interested in how this AWIN tool affects constructs that can be related to performance. The construct of Situation Awareness (SA), workload, trust in an information system, and operator acceptance are assessed using established scales, where these exist, as well as through the evaluation of questionnaire responses and subject comments. The intention of the experiment is to set up a simulated operations area for the dispatchers to work in. They will be given scenarios in which they are presented with stored company routes for a particular city-pair and aircraft type. A diverse set of external weather information sources is represented by a stand-alone display (MOCK), containing the actual historical weather data typically used by dispatchers. There is also the possibility of presenting selected weather data on the route visualization tool. The company routes have not been modified to avoid the weather except in the case of one additional route generated by the Honeywell prototype flight planning system. The dispatcher will be required to choose the most appropriate and efficient flight plan route in the displayed weather conditions. The route may be modified manually or may be chosen from those automatically displayed.

Dorneich, Michael C.↗

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Kirlik, Alex↗

Flight Deck Interval Management Avionics: Eye-Tracking Analysis

Interval Management (IM) is one NexGen method for achieving airspace efficiencies. In order to initiate IM procedures, Air Traffic Control provides an IM clearance to the IM aircraft's pilots that indicates an intended spacing from another aircraft (the target to follow - or TTF) and the point at which this should be achieved. Pilots enter the clearance in the flight deck IM (FIM) system; and once the TTF's Automatic Dependent Surveillance-Broadcast signal is available, the FIM algorithm generates target speeds to meet that IM goal. This study examined four Avionics Conditions (defined by the instrumentation and location presenting FIM information) and three Notification Methods (defined by the visual and aural alerts that notified pilots to IM-related events). Current commercial pilots flew descents into Dallas/Fort-Worth in a high-fidelity commercial flight deck simulation environment with realistic traffic and communications. All 12 crews experienced each Avionics Condition, where order was counterbalanced over crews. Each crew used only one of the three Notification Methods. This paper presents results from eye tracking data collected from both pilots, including: normalized number of samples falling within FIM displays, normalized heads-up time, noticing time, dwell time on first FIM display look after a new speed, a workload-related metric, and a measure comparing the scan paths of pilot flying and pilot monitoring; and discusses these in the context of other objective (vertical and speed profile deviations, response time to dial in commanded speeds, out-of-speed-conformance and reminder indications) and subjective measures (workload, situation awareness, usability, and operational acceptability).

Latorella, Kara↗

Study of Fallout Metrics for Contamination Analysis

A challenge present in assessing contamination accumulation on many missions is predicting fallout during ground processing given the multiple and various orientations possible for surfaces such as optics and instruments. The best practice assumption has been to quantify particle build up on vertical surfaces as approximately 1/10 that of horizontal surfaces. This fractional relation is important when considering contamination allocations necessary to meet cleanliness requirements since spacecraft can be in many orientations during integration and testing. There is insufficient data to provide confidence in the 1/10 approximation, yet its use can have a significant effect on mission end of life contamination level predictions, leading to expenditures of precious resources to meet mission requirements. A study was conducted to compare and analyze the fallout in horizontal and vertical orientations. Silicon wafers were deployed in four different facilities. Data sets from a long term deployment of wafers were analyzed from a cleanroom facility housing integration of the James Webb Space Telescope (JWST) as well as from a shorter term deployment of wafers in three cleanroom facilities at Goddard Space Flight Center with lower activity. There are many variables influencing the relationship between fallout on vertical and horizontal wafers, including wafer position with respect to air flow, air changes in the facility, duration of exposure, and activity workload. The goal of this continuing study is to develop a tool to inform particulate accumulation predictions for future projects.

Contamination↗

Controller Inhibition of Automated Conflict Resolutions in a Maximum NextGen Condition

With the continued projection of increases in air traffic density, operations in the National Airspace System are expected to exceed human capabilities in the near future. In order to address the bottleneck of human workload capacity, highly automated safety-critical systems are under development to support air traffic controllers. A human-in-the-loop experiment examined controllers transition through four NextGen automation stages: Current-Day, Minimum, Moderate, and Maximum. Maximum NextGen simulated a fully automated environment where the automation was responsible for detecting and resolving conflicts within simulation parameters in high-density airspace. By allocating these tasks to the automation, the controllers task changed. The human moved to primarily a supervisory position- typically only regaining control over separation assurance tasks during conflict situations deferred by the automation. While tasks were allocated a-priori between the controller and automated agent, controllers maintained authority to inhibit the automation from interacting with particular aircraft. Preliminary work is complete, where significant differences were found in inhibition frequency between simulation participants. However, the contexts in which the controllers inhibited the automation, and their reasons for doing so, remain unclear. This analysis attempts to identity factors contributing to human controllers inhibition of the automation in the Maximum NextGen condition.

adaptable automation↗

Analysis of the access patterns at GSFC distributed active archive center

The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational for more than two years. Its mission is to support existing and pre Earth Observing System (EOS) Earth science datasets, facilitate the scientific research, and test Earth Observing System Data and Information System (EOSDIS) concepts. Over 550,000 files and documents have been archived, and more than six Terabytes have been distributed to the scientific community. Information about user request and file access patterns, and their impact on system loading, is needed to optimize current operations and to plan for future archives. To facilitate the management of daily activities, the GSFC DAAC has developed a data base system to track correspondence, requests, ingestion and distribution. In addition, several log files which record transactions on Unitree are maintained and periodically examined. This study identifies some of the users' requests and file access patterns at the GSFC DAAC during 1995. The analysis is limited to the subset of orders for which the data files are under the control of the Hierarchical Storage Management (HSM) Unitree. The results show that most of the data volume ordered was for two data products. The volume was also mostly made up of level 3 and 4 data and most of the volume was distributed on 8 mm and 4 mm tapes. In addition, most of the volume ordered was for deliveries in North America although there was a significant world-wide use. There was a wide range of request sizes in terms of volume and number of files ordered. On an average 78.6 files were ordered per request. Using the data managed by Unitree, several caching algorithms have been evaluated for both hit rate and the overhead ('cost') associated with the movement of data from near-line devices to disks. The algorithm called LRU/2 bin was found to be the best for this workload, but the STbin algorithm also worked well.

Johnson, Theodore↗

Markov reward processes

Numerous applications in the area of computer system analysis can be effectively studied with Markov reward models. These models describe the behavior of the system with a continuous-time Markov chain, where a reward rate is associated with each state. In a reliability/availability model, upstates may have reward rate 1 and down states may have reward rate zero associated with them. In a queueing model, the number of jobs of certain type in a given state may be the reward rate attached to that state. In a combined model of performance and reliability, the reward rate of a state may be the computational capacity, or a related performance measure. Expected steady-state reward rate and expected instantaneous reward rate are clearly useful measures of the Markov reward model. More generally, the distribution of accumulated reward or time-averaged reward over a finite time interval may be determined from the solution of the Markov reward model. This information is of great practical significance in situations where the workload can be well characterized (deterministically, or by continuous functions e.g., distributions). The design process in the development of a computer system is an expensive and long term endeavor. For aerospace applications the reliability of the computer system is essential, as is the ability to complete critical workloads in a well defined real time interval. Consequently, effective modeling of such systems must take into account both performance and reliability. This fact motivates our use of Markov reward models to aid in the development and evaluation of fault tolerant computer systems.

Smith, R. M.↗

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

It is essential to provide adequate carbon dioxide (CO2) washout in a space suit to reduce the risks associated with manned operations in space suits. Symptoms of elevated CO2 levels range from reduced cognitive performance and headache to unconsciousness and death at high levels of CO2. Because of this, NASA imposes limits on inspired CO2 levels for space suits when they are used in space and for ground testing. Testing and/or analysis must be performed to verify that a space suit meets CO2 washout requirements. Testing for developmental space suits has traditionally used an oronasal mask that collects CO2 samples at the left and rights sides of the mouth. Testing with this mask resulted in artificially elevated CO2 concentration measurements, which is most likely due to the dead space volume at the front of the mask. The mask also extends outward and into the supply gas stream, which may disrupt the washout effect of the suit supply gas. To mitigate these problems, a nasal cannula was investigated as a method for measuring inspired CO2 based on the assumptions that it is low profile and would not interfere with the designed suit gas flow path, and it has reduced dead space. This test series compared the performance of a nasal cannula to the oronasal mask in the Mark III space suit. Inspired CO2 levels were measured with subjects at rest and at metabolic workloads of 1000, 2000, and 3000 BTU/hr. Workloads were achieved by use of an arm ergometer or treadmill. Test points were conducted at air flow rates of 2, 4, and 6 actual cubic feet per minute, with a suit pressure of 4.3 psid. Results from this test series will evaluate the accuracy and repeatability across subjects of the nasal cannula collection method, which will provide rationale for using a nasal cannula as the new method for measuring inspired CO2 in a space suit. Proper characterization of sampling methods and of suit CO2 washout capability will better inform requirements definition and verification techniques for future CO2 washout limits in space suits

Meginnis, I↗

Automated Euler and Navier-Stokes Database Generation for a Glide-Back Booster

The past two decades have seen a sustained increase in the use of high fidelity Computational Fluid Dynamics (CFD) in basic research, aircraft design, and the analysis of post-design issues. As the fidelity of a CFD method increases, the number of cases that can be readily and affordably computed greatly diminishes. However, computer speeds now exceed 2 GHz, hundreds of processors are currently available and more affordable, and advances in parallel CFD algorithms scale more readily with large numbers of processors. All of these factors make it feasible to compute thousands of high fidelity cases. However, there still remains the overwhelming task of monitoring the solution process. This paper presents an approach to automate the CFD solution process. A new software tool, AeroDB, is used to compute thousands of Euler and Navier-Stokes solutions for a 2nd generation glide-back booster in one week. The solution process exploits a common job-submission grid environment, the NASA Information Power Grid (IPG), using 13 computers located at 4 different geographical sites. Process automation and web-based access to a MySql database greatly reduces the user workload, removing much of the tedium and tendency for user input errors. The AeroDB framework is shown. The user submits/deletes jobs, monitors AeroDB's progress, and retrieves data and plots via a web portal. Once a job is in the database, a job launcher uses an IPG resource broker to decide which computers are best suited to run the job. Job/code requirements, the number of CPUs free on a remote system, and queue lengths are some of the parameters the broker takes into account. The Globus software provides secure services for user authentication, remote shell execution, and secure file transfers over an open network. AeroDB automatically decides when a job is completed. Currently, the Cart3D unstructured flow solver is used for the Euler equations, and the Overflow structured overset flow solver is used for the Navier-Stokes equations. Other codes can be readily included into the AeroDB framework.

Chaderjian, Neal M.↗

MEASURE: An integrated data-analysis and model identification facility

The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.

Singh, Jaidip↗

Decision paths in complex tasks

Complex real world action and its prediction and control has escaped analysis by the classical methods of psychological research. The reason is that psychologists have no procedures to parse complex tasks into their constituents. Where such a division can be made, based say on expert judgment, there is no natural scale to measure the positive or negative values of the components. Even if we could assign numbers to task parts, we lack rules i.e., a theory, to combine them into a total task representation. We compare here two plausible theories for the amalgamation of the value of task components. Both of these theories require a numerical representation of motivation, for motivation is the primary variable that guides choice and action in well-learned tasks. We address this problem of motivational quantification and performance prediction by developing psychophysical scales of the desireability or aversiveness of task components based on utility scaling methods (Galanter 1990). We modify methods used originally to scale sensory magnitudes (Stevens and Galanter 1957), and that have been applied recently to the measure of task 'workload' by Gopher and Braune (1984). Our modification uses utility comparison scaling techniques which avoid the unnecessary assumptions made by Gopher and Braune. Formula for the utility of complex tasks based on the theoretical models are used to predict decision and choice of alternate paths to the same goal.

Galanter, Eugene↗

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scheduling↗

An empirically derived figure of merit for the quality of overall task performance

The need to develop an operationally relevant figure of merit for the quality of performance of a complex system such as an aircraft cockpit stems from a hypothesized dissociation between measures of performance and those of workload. Performance can be measured in terms of time, errors, or a combination of these. In most tasks performed by expert operators, errors are relatively rare and often corrected in time to avoid consequences. Moreover, perfect performance is seldom necessary to accomplish a particular task. Moreover, how well an expert performs a complex task consisting of a series of discrete cognitive tasks superimposed on a continuous task, such as flying an aircraft, does not depend on how well each discrete task is performed, but on their smooth sequencing. This makes the amount of time spent on each subtask of paramount importance in measuring overall performance, since smooth sequencing requires a minimum amount of time spent on each task. Quality consists in getting tasks done within a crucial time interval while maintaining acceptable continuous task performance. Thus, a figure of merit for overall quality of performance should be primarily a measure of time to perform discrete subtasks combined with a measure of basic vehicle control. Thus, the proposed figure of merit requires doing a task analysis on a series of performance, or runs, of a particular task, listing each discrete task and its associated time, and calculating the mean and standard deviation of these times, along with the mean and standard deviation of tracking error for the whole task. A set of simulator data on 30 runs of a landing task was obtained and a figure of merit will be calculated for each run. The figure of merit will be compared for voice and data link, so that the impact of this technology on total crew performance (not just communication performance) can be assessed. The effect of data link communication on other cockpit tasks will also be considered.

Lemay, Moira↗

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

Sensitivity Analysis of Situational Awareness Measures

A great deal of effort has been invested in attempts to define situational awareness, and subsequently to measure this construct. However, relatively less work has focused on the sensitivity of these measures to manipulations that affect the SA of the pilot. This investigation was designed to manipulate SA and examine the sensitivity of commonly used measures of SA. In this experiment, we tested the most commonly accepted measures of SA: SAGAT, objective performance measures, and SART, against different levels of SA manipulation to determine the sensitivity of such measures in the rotorcraft flight environment. SAGAT is a measure in which the simulation blanks in the middle of a trial and the pilot is asked specific, situation-relevant questions about the state of the aircraft or the objective of a particular maneuver. In this experiment, after the pilot responded verbally to several questions, the trial continued from the point frozen. SART is a post-trial questionnaire that asked for subjective SA ratings from the pilot at certain points in the previous flight. The objective performance measures included: contacts with hazards (power lines and towers) that impeded the flight path, lateral and vertical anticipation of these hazards, response time to detection of other air traffic, and response time until an aberrant fuel gauge was detected. An SA manipulation of the flight environment was chosen that undisputedly affects a pilot's SA-- visibility. Four variations of weather conditions (clear, light rain, haze, and fog) resulted in a different level of visibility for each trial. Pilot SA was measured by either SAGAT or the objective performance measures within each level of visibility. This enabled us to not only determine the sensitivity within a measure, but also between the measures. The SART questionnaire and the NASA-TLX, a measure of workload, were distributed after every trial. Using the newly developed rotorcraft part-task laboratory (RPTL) at NASA Ames Research Center, each pilot flew eight trials, four using SAGAT and four using performance measures. Each set of four trials differed by level of visibility as well. The flight paths were very similar in appearance and hazard number, allowing comparison between flight paths. The pilots were tasked with flying along a road at an assigned altitude and speed while avoiding any hazards that they happened upon. The attempt here was not to find a single best measure of SA, but rather to begin an investigation of the sensitivity of common measures of SA. Upon completion of this study, its results, in combination with future studies, should allow us to develop an empirically based taxonomy of SA measures and the contexts for their appropriate use.

Shively, R. J.↗

MSL Telecom Automated Anomaly Detection

The Mars Science Laboratory (MSL) Telecom Operations Team at the Jet Propulsion Laboratory (JPL) has implemented a machine learning system in order to automate the anomaly detection process as a part of daily operations. Machine learning enables reliable detection of anomalies in Telecom-related telemetry and automated reporting of Telecom subsystem status, resulting in an 90% reduction in team workload and improved anomaly detection reliability. At present, machine learning methods are used to detect: 1. Anomalous long-term trends in telemetry data 2. Anomalous time-domain evolution of telemetry values Both types of anomalies pose their own unique challenges that are addressed in different ways. In the first case, long term trending of daily minima, maximum, and mean telemetry values in temperatures, currents, voltages, and radio frequency (RF) power levels is used in addition to hard threshold safety checks to look for changes in long-term equipment health and performance. Long-term trending methods allow for ordinary seasonal variations in these quantities caused by temperature changes over the course of the Martian year while allowing operators to determine whether current performance remains in line with historical values from previous years. Changes in long-term trends can provide important insights into the health and status of the rover's on-board systems as well as valuable early warning if subtle degradation begins to take hold. But while trending of daily statistics is valuable, it does not detect anomalies in the short-term time evolution of data over the course of minutes or hours during a day, and this task is handled with short-term shape analysis. Principal components analysis (PCA) has been found to provide robust detection of short-term anomalies, and several examples of the use of PCA to detect actual anomalous events will be provided here. In using PCA, we use both the percentage of explained variance and also a log likelihood test on the PCA expansion coefficients to flag telemetry data for human review. Previous work in the field of spacecraft anomaly detection includes [1] for MSL and [2] for some other JPL missions.

Mukai, Ryan↗

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.↗