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First Annual Report: NASA-ONERA Collaboration on Human Factors in Aviation Accidents and Incidents

This is the first annual report jointly prepared by NASA and ONERA on the work performed under the agreement to collaborate on a study of the human factors entailed in aviation accidents and incidents particularly focused on consequences of decreases in human performance associated with fatigue. The objective of this Agreement is to generate reliable, automated procedures that improve understanding of the levels and characteristics of flight-crew fatigue factors whose confluence will likely result in unacceptable crew performance. This study entails the analyses of numerical and textual data collected during operational flights. NASA and ONERA are collaborating on the development and assessment of automated capabilities for extracting operationally significant information from very large, diverse (textual and numerical) databases much larger than can be handled practically by human experts. This report presents the approach that is currently expected to be used in processing and analyzing the data for identifying decrements in aircraft performance and examining their relationships to decrements in crewmember performance due to fatigue. The decisions on the approach were based on samples of both the numerical and textual data that will be collected during the four studies planned under the Human Factors Monitoring Program (HFMP). Results of preliminary analyses of these sample data are presented in this report.

Srivastava, Ashok↗

Lessons of History: Organizational Factors in Three Aviation Mishaps

This presentation examines organizational factors that contributed to three aircraft mishaps and provides analysis of lessons learned. Three historical aviation mishaps were studied from a human factors perspective, and organizational factors identified and analyzed. These case studies provide valuable lessons for understanding the interaction of people with aircraft systems and with each other during flight operations.

Merlin, Peter William↗

Human Health/Human Factors Considerations in Trans-Lunar Space

The human factors insights of how they are incorporated into the vehicle are crucial towards designing and planning the internal designs necessary for future spacecraft and missions. The adjusted mission concept of supporting the Asteroid Redirect Crewed Mission will drive some human factors changes on how the Orion will be used and will be reassessed so as to best contribute to missions success. Recognizing what the human factors and health functional needs are early in the design process and how to integrate them will improve this and future generations of space vehicles to achieve mission success and continue to minimize risks.

Moore, E. Cherice↗

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

Diverse vulnerabilities of Bangladesh's agricultural sector in 16 sub-regions are assessed using experiments designed to investigate climate impact factors in isolation and in combination. Climate information from a suite of global climate models (GCMs) is used to drive models assessing the agricultural impact of changes in temperature, precipitation, carbon dioxide concentrations, river floods, and sea level rise for the 2040-2069 period in comparison to a historical baseline. Using the multi-factor impacts analysis framework developed in Yu et al. (2010), this study provides new sub-regional vulnerability analyses and quantifies key uncertainties in climate and production. Rice (aman, boro, and aus seasons) and wheat production are simulated in each sub-region using the biophysical Crop Environment REsource Synthesis (CERES) models. These simulations are then combined with the MIKE BASIN hydrologic model for river floods in the Ganges-Brahmaputra-Meghna (GBM) Basins, and the MIKE21Two-Dimensional Estuary Model to determine coastal inundation under conditions of higher mean sea level. The impacts of each factor depend on GCM configurations, emissions pathways, sub-regions, and particular seasons and crops. Temperature increases generally reduce production across all scenarios. Precipitation changes can have either a positive or a negative impact, with a high degree of uncertainty across GCMs. Carbon dioxide impacts on crop production are positive and depend on the emissions pathway. Increasing river flood areas reduce production in affected sub-regions. Precipitation uncertainties from different GCMs and emissions scenarios are reduced when integrated across the large GBM Basins' hydrology. Agriculture in Southern Bangladesh is severely affected by sea level rise even when cyclonic surges are not fully considered, with impacts increasing under the higher emissions scenario.

Ruane, Alex C.↗

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha−x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

fires↗

Calculation of Operations Efficiency Factors for Mars Surface Missions

The duration of a mission--and subsequently, the minimum spacecraft lifetime--is a key component in designing the capabilities of a spacecraft during mission formulation. However, determining the duration is not simply a function of how long it will take the spacecraft to execute the activities needed to achieve mission objectives. Instead, the effects of the interaction between the spacecraft and ground operators must also be taken into account. This paper describes a method, using "operations efficiency factors", to account for these effects for Mars surface missions. Typically, this level of analysis has not been performed until much later in the mission development cycle, and has not been able to influence mission or spacecraft design. Further, the notion of moving to sustainable operations during Prime Mission--and the effect that change would have on operations productivity and mission objective choices--has not been encountered until the most recent rover missions (MSL, the (now-cancelled) joint NASA-ESA 2018 Mars rover, and the proposed rover for Mars 2020). Since MSL had a single control center and sun-synchronous relay assets (like MER), estimates of productivity derived from MER prime and extended missions were used. However, Mars 2018's anticipated complexity (there would have been control centers in California and Italy, and a non-sun-synchronous relay asset) required the development of an explicit model of operations efficiency that could handle these complexities. In the case of the proposed Mars 2018 mission, the model was employed to assess the mission return of competing operations concepts, and as an input to component lifetime requirements. In this paper we provide examples of how to calculate the operations efficiency factor for a given operational configuration, and how to apply the factors to surface mission scenarios. This model can be applied to future missions to enable early effective trades between operations design, science mission planning, and spacecraft design.

Laubach, Sharon↗

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

ozone↗

What Factors Control the Trend of Increasing AAOD Over the United States in the Last Decade?

We examine the spatial and temporal trends of absorbing aerosol optical depth (AAOD) in the last decade over the United States (U.S.) observed by the Ozone Monitoring Instrument (OMI). Monthly average OMI AAOD has increased over broad areas of the central U.S. from 2005 to 2015, by up to a factor of 4 in some grid cells (~60 km resolution). The AAOD increases in all seasons, although the percentage increases are larger in summer (June-July-August) than in winter (December-January-February) by a factor of 3. Despite enhancements in AAOD, OMI AOD exhibits insignificant trend over most of the U.S. except parts of the central and western U.S., the latter which may partly be due to decreases in precipitation. Trends in AAOD contrast with declining trends in surface concentrations of black carbon (BC) aerosol. Interannual variability of local biomass burning emissions of BC may contribute to the positive trend in AAOD over the western U.S. Changes in both dust aerosol measured at the surface (in terms of concentration and size) and dust AAOD indicate distinct enhancements, especially over the central U.S. by 50-100%, which appears to be one of the major factors that impacts positive trends in AAOD.

Satellite retrieval↗

Atomic Scattering Factor of the ASTRO-H (Hitomi) SXT Reflector Around the Gold's L Edges

The atomic scattering factor in the energy range of 11.2 - 15.4 keV for the ASTRO-H Soft X-ray Telescope (SXT) is reported. The large effective area of the SXT makes use of photon spectra above 10 keV viable, unlike most other X-ray satellites with total-reflection mirror optics. Presence of gold's L-edges in the energy band is a major issue, as it complicates the function of the effective area. In order to model the area, the reflectivity measurements in the 11.2 - 15.4 keV band with the energy pitch of 0.4 - 0.7 eV were made in the synchrotron beam-line Spring-8 BL01B1. We obtained atomic scattering factors f1 and f2 by the curve fitting to the reflectivities of our witness sample. The edges associated with the L-I, II, and III transitions are identified, of which the depths are found to be roughly 60 shallower than those expected from the Henkes atomic scattering factor.

ASTRO-H Soft X-ray↗

Human Factors Virtual Analysis Techniques for NASA's Space Launch System Ground Support using MSFC's Virtual Environments Lab (VEL)

Using virtual environments to assess complex large scale human tasks provides timely and cost effective results to evaluate designs and to reduce operational risks during assembly and integration of the Space Launch System (SLS). NASA's Marshall Space Flight Center (MSFC) uses a suite of tools to conduct integrated virtual analysis during the design phase of the SLS Program. Siemens Jack is a simulation tool that allows engineers to analyze human interaction with CAD designs by placing a digital human model into the environment to test different scenarios and assess the design's compliance to human factors requirements. Engineers at MSFC are using Jack in conjunction with motion capture and virtual reality systems in MSFC's Virtual Environments Lab (VEL). The VEL provides additional capability beyond standalone Jack to record and analyze a person performing a planned task to assemble the SLS at Kennedy Space Center (KSC). The VEL integrates Vicon Blade motion capture system, Siemens Jack, Oculus Rift, and other virtual tools to perform human factors assessments. By using motion capture and virtual reality, a more accurate breakdown and understanding of how an operator will perform a task can be gained. By virtual analysis, engineers are able to determine if a specific task is capable of being safely performed by both a 5% (approx. 5ft) female and a 95% (approx. 6'1) male. In addition, the analysis will help identify any tools or other accommodations that may to help complete the task. These assessments are critical for the safety of ground support engineers and keeping launch operations on schedule. Motion capture allows engineers to save and examine human movements on a frame by frame basis, while virtual reality gives the actor (person performing a task in the VEL) an immersive view of the task environment. This presentation will discuss the need of human factors for SLS and the benefits of analyzing tasks in NASA MSFC's VEL.

Searcy, Brittani↗

Increased Operational Availability and Simplified Operations Using Dither Gyro Scale Factor Calibration

The traditional approach to on-orbit gyro scale factor calibration has been to perform large angle rotations about each gyro axis. The maneuvers require the science instruments to be taken offline, reducing operational availability and require a significant amount of interaction from the ground. To increase operational availability and to reduce the burden on mission operators, a novel approach to gyro scale factor calibration was developed, modeled and successfully demonstrated on the Geostationary Operational Environmental Satellite (GOES-16) to estimate gyro scale factor errors to within 1500 parts per million (ppm) without taking the science instruments offline.

Reth, Alan D.↗

On the Development of Shell Buckling Knockdown Factors for Stiffened Metallic Launch Vehicle Cylinders

From the 1920s to the early 1970s, many shell buckling experiments were conducted in an effort to understand the complex buckling behavior exhibited by thin-walled cylindrical shells, to provide data to correlate with new shell stability theories, and provide design guidelines. Typically, the experiments yielded buckling loads that were substantially lower than the corresponding analytical predictions, which were based on simplified linear bifurcation analyses of geometrically perfect shells with nominal dimensions and idealized boundary conditions. The seminal works by von Kármán and Tsien, by Donnell and Wan, and by Koiter identified small deviations from the idealized geometry of a shell, known as initial geometric imperfections, as a primary source of the discrepancy between corresponding analytical predictions and experimental results. However, the computational tools and capabilities at that time could not perform the nonlinear analyses needed to assess the effects of these imperfections on the buckling behavior of thin-walled shells. Thus, buckling design allowables were determined by establishing lower bounds to test data. Specifically, empirical design factors, that have become known as knockdown factors, were determined and were to be used in conjunction with linear bifurcation analyses for simply supported shells; that is, these empirical factors were used to "knock down" the value of the unconservative simplified analytical prediction. This approach to shell buckling design has proved satisfactory for most design purposes and remains prominent in industry practice, as evidenced by the extensive use of the NASA space vehicle design criteria and recommendations. Unfortunately, the current design guidelines have not been updated since they were first published in the late 1960s and may not be able to take full advantage of modern materials, precision manufacturing processes, and new structural concepts.

Hilburger, Mark W.↗

The Collection of Human Factors Incident Reports via UAS Pilot Focus Groups

There is a need for incident data relevant to the operation of civilian unmanned aircraft systems (UAS) in the National Air Space (NAS). Currently, the tightly-restricted civilian UAS industry has produced relatively few incident reports that shed light on the human factors of UAS operations. An exploratory study is being conducted to examine the feasibility of using the critical incident technique (Flanagan, 1954) to collect reports from UAS pilots. The information is being used to identify areas where human factors guidelines will be of assistance. Experienced UAS pilots are participating in small focus groups in which they are prompted to describe critical incidents that either reveal a system flaw, or highlight a case where the human operator contributed to system resilience or mission success. To date, 90 incidents have been reported by UAS pilots. The de-identified incidents are being analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot in dealing with the incident..

Hobbs, Alan↗

Emissions Relationships Among Western Forest Fire Plumes: I. Emission Factors Free from Mixing Errors

Previous studies of emission factors from biomass burning are prone to largeerrors since they ignore the interplay of mixing and varying pre-fire backgroundCO2 levels. Such complications severely affected our studies of 446 forest fireplume samples measured in the Western US by the science teams of NASAsSEAC4RS and ARCTAS airborne missions. Consequently we propose a MixedEffects Regression Emission Technique (MERET) to check techniques like theNormalized Emission Ratio Method (NERM), where use of sequentialobservations cannot disentangle emissions and mixing. We also evaluate asimpler consensus technique. All techniques relate emissions to fuel burnedusing C burn = Δ Ctot added to the fire plume, where ≈ Ctot (CO2 + CO). Mixed-effectsregression can estimate pre-fire background values of Ctot (indexed byobservation j) simultaneously with emissions factors indexed by individual species i, δέλτα-xi (Cburn )i,j., MERET and consensus require more than twoemissions indicators. Our studies excluded samples where exogenous CO orCH4 might have been fed into a fire plume, mimicking emission.We sought to let the data on 13 gases and particulate properties suggest clustersof variables and plume types, using non-negative matrix factorization (NMF).While samples were mixtures, the NMF unmixing suggested purer burn types.Particulate properties (bscat, babs, SSA, AÅE) and gas-phase emissions were interrelated.Finally, we sought a simple categorization useful for modeling ozone productionin plumes. Two kinds of fires produced high ozone: those with large fuel nitrogenas evidenced by remnant CH3CN in the plumes, and also those from veryintense large burns. Fire types with optimal ratios of delta-NOydelta-HCHO associate with the highest additional ozone per unit Cburn, Perhaps theseplumes exhibit limited NOx binding to reactive organics. Perhaps these plumesexhibit limited NOx binding to reactive organics.

plumes↗

Influential Factors for Liquid Acquisition Device Screen Selection for Cryogenic Propulsion Systems

This paper presents the influential factors which govern screen selection for liquid acquisition devices (LADs) operating in microgravity conditions for future in-space cryogenic propulsion engines and cryogenic propellant depots. Space flight requirements, which include mass flow rate, acceleration level and direction, and thermal environment, dictate screen selection for a particular mission. The five influential factors include bubble point pressure, flow-through-screen pressure drop, wicking rate, screen compliance, and material compatibility. Governing equations and analytical models for these parameters are developed from first principles. A comprehensive survey of the historical data on coarser LAD meshes over four decades of work is conducted, and liquid hydrogen data for finer Dutch Twill meshes (325 x 2300, 450 x 2750, 510 x 3600) from recently concluded experiments is also presented to validate analytical models. Each of these parameters is measurable from ground based tests, making it facile to predict flight system performance. Therefore analytical models in this paper will be valuable for future LAD designs for both cryogenic and storable propulsion systems. Additionally, analysis will be given on the impact of the factors on liquid hydrogen systems.

Fuel Depot↗

NASA Marshall Space Flight Center Human Factors Engineering Analysis of Various Hatch Sizes and Associated Safety Impacts

The NASA Docking System (NDS) is a 31.5-inch (800-millimeter)-diameter circular hatch for astronauts to pass through when docked to other pressurized elements in space or for surface egress. The NDS is utilized on the Orion Spacecraft and has been implemented as the International Docking System Standard (IDSS). The EV74 Human Factors Engineering (HFE) Team at NASA’s Marshall Space Flight Center (MSFC) conducted human factors analyses with various hatch shapes and sizes to accommodate for all astronaut anthropometries, task comfort, and task safety. The 32-inch hatch is too small and a bigger hatch size would better accommodate most astronauts and prove to be safer for daily pass-throughs. To conduct human factors analyses, four participants were gathered based on anthropometry: 1st female, 5th female, 95th male, and 99th male.

Andrews, Tanya C.↗

Casper-1, Part 6: Uncertainty Quantification, Factor Effects, and Outlier Analysis for an On-Board Airplane Trajectory Prediction Function

This report presents data analysis results for a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of onboard energy state and automation mode prediction functions for terminal area arrival and approach phases of flight over a wide range of conditions. In particular, the results include quantification of energy state (i.e., altitude and airspeed) prediction performance, models for prediction performance as a function of initial energy state (i.e., initial altitude, airspeed, and weight) and weather factors, and analysis of outlier prediction performance. Wind speed, wind direction, and wind gradient were found to be major factors in energy state prediction performance. Initial energy and gust intensity were also significant factors in airspeed prediction performance. Furthermore, the results suggest that errors in automation mode prediction may be a major contributor to outlier prediction performance.

Torres-Pomales, Wilfredo↗

NASA Marshall Space Flight Center Human Factors Engineering Analysis of Various Hatch Sizes

The NASA Docking System (NDS) is a 31.4961-inch (800 mm) diameter circular hatch for astronauts to pass through when docked to other pressurized elements in space or for entrance or egress on surface environments. The NDS is utilized on the Orion Spacecraft and has been implemented as the International Docking System Standard (IDSS). The EV74 Human Factors Engineering (HFE) Team at NASA’s Marshall Space Flight Center (MSFC) conducted human factors analyses with various hatch shapes and sizes to accommodate for all astronaut anthropometries and daily task comfort. It is believed that the hatch, approximately 32 inches, is too small, and a bigger hatch size would better accommodate most astronauts. In order to conduct human factors analyses, four participants were gathered based on anthropometry percentiles: 1st female, 5th female, 95th male, and 99th male.

Andrews, Tanya↗