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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Alloy Design Workbench-Surface Modeling Package Developed

NASA Glenn Research Center's Computational Materials Group has integrated a graphical user interface with in-house-developed surface modeling capabilities, with the goal of using computationally efficient atomistic simulations to aid the development of advanced aerospace materials, through the modeling of alloy surfaces, surface alloys, and segregation. The software is also ideal for modeling nanomaterials, since surface and interfacial effects can dominate material behavior and properties at this level. Through the combination of an accurate atomistic surface modeling methodology and an efficient computational engine, it is now possible to directly model these types of surface phenomenon and metallic nanostructures without a supercomputer. Fulfilling a High Operating Temperature Propulsion Components (HOTPC) project level-I milestone, a graphical user interface was created for a suite of quantum approximate atomistic materials modeling Fortran programs developed at Glenn. The resulting "Alloy Design Workbench-Surface Modeling Package" (ADW-SMP) is the combination of proven quantum approximate Bozzolo-Ferrante-Smith (BFS) algorithms (refs. 1 and 2) with a productivity-enhancing graphical front end. Written in the portable, platform independent Java programming language, the graphical user interface calls on extensively tested Fortran programs running in the background for the detailed computational tasks. Designed to run on desktop computers, the package has been deployed on PC, Mac, and SGI computer systems. The graphical user interface integrates two modes of computational materials exploration. One mode uses Monte Carlo simulations to determine lowest energy equilibrium configurations. The second approach is an interactive "what if" comparison of atomic configuration energies, designed to provide real-time insight into the underlying drivers of alloying processes.

Abel, Phillip B.↗
NASA NTRS2009

System Modeling of Metabolic Heat Regenerated Temperature Swing Adsorption (MTSA) Subassembly for Prototype Design

This paper describes modeling methods for the three core components of a Metabolic heat regenerated Temperature Swing Adsorption (MTSA) subassembly: the sorbent bed, a sublimation (cooling) heat exchanger (SHX), and a condensing icing (warming) heat exchanger (CIHX). The primary function of the MTSA, removing carbon dioxide from a ventilation loop, is performed via the sorbent bed. The CIHX is used to heat the sorbent bed for desorption and to remove moisture from the ventilation loop while the SHX is alternately employed to cool the sorbent bed via sublimation of a spray of water at low pressure to prepare the reconditioned bed for the next cycle. This paper describes a system level model of the MTSA as developed in Thermal Desktop and SINDA/FLUINT including assumptions on geometry and physical phenomena, modeling methodology and relevant pa ra mete rizatio ns. Several areas of particular modeling interest are discussed. In the sorbent bed, capture of the translating CO2 saturation front and associated local energy and mass balance in both adsorbing and desorbing modes is covered. The CIHX poses particular challenges for modeling in SINDA/FLUINT as accounting for solids states in fluid submodels are not a native capability. Methods for capturing phase change and latent heat of ice as well as the transport properties across a layer of low density accreted frost are developed. This extended modeling capacity is applicable to temperatures greater than 258 K. To extend applicability to the minimum device temperature of 235 K, a method for a mapped transformation of temperatures from below the limit temperatures to some value above is given along with descriptions for associated material property transformations and the resulting impacts to total heat and mass transfer. Similar considerations are shown for the SHX along with assumptions for flow mechanics and resulting model methods for sublimation in a flow.

Bower, Chad↗
NASA NTRSDate not supplied

fmdtools Tutorial: Intro to Resilience Modelling, Simulation, and Visualization in Python With fmdtools

This workshop will cover the basics of using the fmdtools package for the simulation of hazardous scenarios for resilience simulation. The fmdtools simulation package is an open-source python toolkit for simulating the dynamic response of a system to internal and externally-driven hazardous scenarios, including faults and environmental conditions, that can be used to analyze the risks related to these hazards. Prior to the development of fmdtools, researchers had to either adapt an (often limited) propriety toolkit or develop their own design/simulation/analysis codes to develop their models of hazardous events, a significant technical burden to both (1) leveraging resilience modeling methodologies and (2) extending these methodologies with their own contributions. The fmdtools package provides a number of model constructs and simulation and analysis methods to enable the designer to focus to solely on their modeling case-study while still enabling a significant degree of model expressiveness and adaptability via Python-based model definition. This tutorial will present the setup of fmdtools and a high-level overview of its use, as well as some simple examples for understanding how to leverage its modelling, simulation, and analysis capabilities. Familiarity with jupyter notebook and basic python will be assumed.

Daniel Hulse↗
NASA NTRS2011

Reference Management Methodologies for Large Structural Models at Kennedy Space Center

There have been many challenges associated with modeling some of NASA KSC's largest structures. Given the size of the welded structures here at KSC, it was critically important to properly organize model struc.ture and carefully manage references. Additionally, because of the amount of hardware to be installed on these structures, it was very important to have a means to coordinate between different design teams and organizations, check for interferences, produce consistent drawings, and allow for simple release processes. Facing these challenges, the modeling team developed a unique reference management methodology and model fidelity methodology. This presentation will describe the techniques and methodologies that were developed for these projects. The attendees will learn about KSC's reference management and model fidelity methodologies for large structures. The attendees will understand the goals of these methodologies. The attendees will appreciate the advantages of developing a reference management methodology.

Jones, Corey↗
NASA NTRSDate not supplied

Implementing Artificial Thinking Autonomy with Model-Based System Engineering

Complex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration. The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities. This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy. This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.

Artificial Thought↗
NASA NTRS2010

Waterhammer Testing and Modeling of the Ares I Upper Stage Reaction Control System

NASA's Ares I rocket is the agency's first step in completing the goals of the Constellation Program, which plans to deliver a new generation of space explorers into low earth orbit for future missions to the International Space Station, the moon, and other destinations within the solar system. Ares I is a two-stage rocket topped by the Orion crew capsule and its service module. The launch vehicle's First Stage is a single, five-segment reusable solid rocket booster (RSRB), derived from the Space Shuttle Program's four segment RSRB. The vehicle's Upper Stage, being designed at Marshall Space Flight Center (MSFC), is propelled by a single J-2X Main Engine fueled with liquid oxygen and liquid hydrogen. During active Upper Stage flight of the Ares I launch vehicle, the Upper Stage Reaction Control System (US ReCS) will perform attitude control operations for the vehicle. The US ReCS will provide three-axis attitude control capability (roll, pitch, and yaw) for the Upper Stage while the J-2X is not firing and roll control capability while the engine is firing. Because of the requirements imposed upon the system, the design must accommodate rapid pulsing of multiple thrusters simultaneously to maintain attitude control. In support of these design activities and in preparation for Critical Design Review, analytical models of the US ReCS propellant feed system have been developed using the Thermal Hydraulic Library of MSC.EASY5 v.2008, herein referred to as EASY5. EASY5 is a commercially available fluid system modeling package with significant history of modeling space propulsion systems. In Fall 2009, a series of development tests were conducted at MSFC on a cold-flow test article for the US ReCS, herein referred to as System Development Test Article (SDTA). A subset of those tests performed were aimed at examining the effects of waterhammer on a flight-representative system and to ensure that those effects could be quantified with analytical models and incorporated into the design of the flight system. This paper presents an overview of the test article and the test approach, along with a discussion of the analytical modeling methodology. In addition, the results of that subset of development tests, along with analytical model pre-test predictions and post-test model correlations, will also be discussed in detail.

Williams, J. Hunter↗
NASA NTRS2000

An Unsteady Long Bearing Squeeze Film Damper Model: Circular Centered Orbits - Part 1

This paper, the first of a two-part series, presents results of an unsteady rotordynamic analysis of a long-bearing squeeze film damper executing circular centered orbits using a fluid circuit approach. A series of nodes and branches represent the geometry of the flow circuit. The mass and momentum conservation equations are solved to predict the pressure distribution in the squeeze film. The motion of the bearing is simulated by the variation of geometry within the flow path. The modeling methodology is benchmarked against published experimental long-bearing squeeze film damper test results. The model provides good agreement with the experimental damping coefficient.

Schallhorn, P. A.↗
NASA NTRS2016

Microgravity-Driven Optic Nerve/Sheath Biomechanics Simulations

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Current thinking suggests that the ocular changes observed in VIIP syndrome are related to cephalad fluid shifts resulting in altered fluid pressures [1]. In particular, we hypothesize that increased intracranial pressure (ICP) drives connective tissue remodeling of the posterior eye and optic nerve sheath (ONS). We describe here finite element (FE) modeling designed to understand how altered pressures, particularly altered ICP, affect the tissues of the posterior eye and optic nerve sheath (ONS) in VIIP. METHODS: Additional description of the modeling methodology is provided in the companion IWS abstract by Feola et al. In brief, a geometric model of the posterior eye and optic nerve, including the ONS, was created and the effects of fluid pressures on tissue deformations were simulated. We considered three ICP scenarios: an elevated ICP assumed to occur in chronic microgravity, and ICP in the upright and supine positions on earth. Within each scenario we used Latin hypercube sampling (LHS) to consider a range of ICPs, ONH tissue mechanical properties, intraocular pressures (IOPs) and mean arterial pressures (MAPs). The outcome measures were biomechanical strains in the lamina cribrosa, optic nerve and retina; here we focus on peak values of these strains, since elevated strain alters cell phenotype and induce tissue remodeling. In 3D, the strain field can be decomposed into three orthogonal components, denoted as first, second and third principal strains. RESULTS AND CONCLUSIONS: For baseline material properties, increasing ICP from 0 to 20 mmHg significantly changed strains within the posterior eye and ONS (Fig. 1), indicating that elevated ICP affects ocular tissue biomechanics. Notably, strains in the lamina cribrosa and retina became less extreme as ICP increased; however, within the optic nerve, the occurrence of such extreme strains greatly increased as ICP was elevated (Fig. 2). In particular, c. 48 of simulations in the elevated ICP condition showed peak strains in the optic nerve that exceeded the strains expected on earth. Such extreme strains are likely important, since they represent a larger signal for mechano-responsive resident cells [2]. The models predicted little to no anterior motion of the prelaminar neural tissue (optic nerve swelling, or papilledema, secondary to axoplasmic stasis), typically seen with elevated ICP. Specialized FE models to capture axoplasmic stasis would be required to study papilledema. These results suggest that the most notable effect of elevated ICP may occur via direct optic nerve loading, rather than through connective tissue deformation. These FE models can inform the design of future studies designed to bridge the gap between biomechanics and pathophysiological function in VIIP.

biomechanics↗
NASA NTRS1994

An error covariance model for sea surface topography and velocity derived from TOPEX/POSEIDON altimetry

In order to facilitate the use of satellite-derived sea surface topography and velocity oceanographic models, methodology is presented for deriving the total error covariance and its geographic distribution from TOPEX/POSEIDON measurements. The model is formulated using a parametric model fit to the altimeter range observations. The topography and velocity modeled with spherical harmonic expansions whose coefficients are found through optimal adjustment to the altimeter range residuals using Bayesian statistics. All other parameters, including the orbit, geoid, surface models, and range corrections are provided as unadjusted parameters. The maximum likelihood estimates and errors are derived from the probability density function of the altimeter range residuals conditioned with a priori information. Estimates of model errors for the unadjusted parameters are obtained from the TOPEX/POSEIDON postlaunch verification results and the error covariances for the orbit and the geoid, except for the ocean tides. The error in the ocean tides is modeled, first, as the difference between two global tide models and, second, as the correction to the present tide model, the correction derived from the TOPEX/POSEIDON data. A formal error covariance propagation scheme is used to derive the total error. Our global total error estimate for the TOPEX/POSEIDON topography relative to the geoid for one 10-day period is found tio be 11 cm RMS. When the error in the geoid is removed, thereby providing an estimate of the time dependent error, the uncertainty in the topography is 3.5 cm root mean square (RMS). This level of accuracy is consistent with direct comparisons of TOPEX/POSEIDON altimeter heights with tide gauge measurements at 28 stations. In addition, the error correlation length scales are derived globally in both east-west and north-south directions, which should prove useful for data assimilation. The largest error correlation length scales are found in the tropics. Errors in the velocity field are smallest in midlatitude regions. For both variables the largest errors caused by uncertainty in the geoid. More accurate representations of the geoid await a dedicated geopotential satellite mission. Substantial improvements in the accuracy of ocean tide models are expected in the very near future from research with TOPEX/POSEIDON data.

Tsaoussi, Lucia S.↗
NASA NTRS2017

Magnetic Shield Design Modeling and Validation on SWOT Spacecraft Applied to Mars Flux Pinning Orbiting Sample Design

A modeling methodology was developed for use on the Surface Water and Ocean Topography (SWOT) mission for the computational modeling and design of a magnetic shield for a 63 A-sq m source. Shield options were modeled and tested across various design parameters and validated with measurement. Measurement results fell within 10% of simulation in most cases of concern with sources of error well understood. These methods results informed a subsequent modeling activity for a future Mars Sample Return (MSR) mission concept with stringent magnetic cleanliness requirements to retain geologic integrity of the samples. One option for capturing the sample from orbit requires rare earth magnets in close proximity to the Martian samples. Magnetic modeling with a finite-element method solver estimated the magnetic environment and established the need for shielding. Further modeling then determined the shielding necessary to meet magnetic requirements, followed by the design of a mass-optimized solution.

Gonzales, Edward↗
NASA NTRS1994

Towards an integral computer environment supporting system operations analysis and conceptual design

VITROCISET has in house developed a prototype tool named System Dynamic Analysis Environment (SDAE) to support system engineering activities in the initial definition phase of a complex space system. The SDAE goal is to provide powerful means for the definition, analysis, and trade-off of operations and design concepts for the space and ground elements involved in a mission. For this purpose SDAE implements a dedicated modeling methodology based on the integration of different modern (static and dynamic) analysis and simulation techniques. The resulting 'system model' is capable of representing all the operational, functional, and behavioral aspects of the system elements which are part of a mission. The execution of customized model simulations enables: the validation of selected concepts with respect to mission requirements; the in-depth investigation of mission specific operational and/or architectural aspects; and the early assessment of performances required by the system elements to cope with mission constraints and objectives. Due to its characteristics, SDAE is particularly tailored for nonconventional or highly complex systems, which require a great analysis effort in their early definition stages. SDAE runs under PC-Windows and is currently used by VITROCISET system engineering group. This paper describes the SDAE main features, showing some tool output examples.

Barro, E.↗
NASA NTRS2003

An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design

Crucial to an efficient aircraft simulation-based design is a robust data modeling methodology for both recording the information and providing data transfer readily and reliably. To meet this goal, data modeling issues involved in the aircraft multidisciplinary design are first analyzed in this study. Next, an XML-based. extensible data object model for multidisciplinary aircraft design is constructed and implemented. The implementation of the model through aircraft databinding allows the design applications to access and manipulate any disciplinary data with a lightweight and easy-to-use API. In addition, language independent representation of aircraft disciplinary data in the model fosters interoperability amongst heterogeneous systems thereby facilitating data sharing and exchange between various design tools and systems.

Lin, Risheng↗
NASA NTRS2010

Modeling Of Metabolic Heat Regenerated Temperature Swing Adsorption (MTSA) Subassembly For Prototype Design

This paper describes modeling methods for the three core components of a Metabolic heat regenerated Temperature Swing Adsorption (MTSA) subassembly: a sorbent bed, a sublimation (cooling) heat exchanger (SHX), and a condensing icing (warming) heat exchanger (CIHX). The primary function of the MTSA, removing carbon dioxide from a space suit Portable Life Support System (PLSS) ventilation loop, is performed via the sorbent bed. The CIHX is used to heat the sorbent bed for desorption and to remove moisture from the ventilation loop while the SHX is alternately employed to cool the sorbent bed via sublimation of a spray of water at low pressure to prepare the reconditioned bed for the next cycle. This paper describes subsystem heat a mass transfer modeling methodologies relevant to the description of the MTSA subassembly in Thermal Desktop and SINDA/FLUINT. Several areas of particular modeling interest are discussed. In the sorbent bed, capture of the translating carbon dioxide (CO2) front and associated local energy and mass balance in both adsorbing and desorbing modes is covered. The CIHX poses particular challenges for modeling in SINDA/FLUINT as accounting for solids states in fluid submodels are not a native capability. Methods for capturing phase change and latent heat of ice as well as the transport properties across a layer of low density accreted frost are developed. This extended modeling capacity is applicable to temperatures greater than 258 K. To extend applicability to the minimum device temperature of 235 K, a method for a mapped transformation of temperatures from below the limit temperatures to some value above is given along with descriptions for associated material property transformations and the resulting impacts to total heat and mass transfer. Similar considerations are given for the SHX along with functional relationships for areal sublimation rates as limited by flow mechanics in t1he outlet duct.

Bower, Chad E.↗
NASA NTRS2017

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics↗
NASA NTRSDate not supplied

A Solar Sail Shape Modeling Approach for Attitude Control Design and Analysis

Solar sails operating in the space environment experience deformations in sail shape that result in relatively large disturbance torques which dictate the required performance of the spacecraft attitude control and momentum management systems. These deformations are driven by thermal loads on the booms (due to uneven solar heating), manufacturing and assembly tolerances, and variations in membrane tension. The Solar Cruiser spacecraft utilizes a four-quadrant sail design with four 30-meter length booms and four triangular sail membranes, creating a square sail structure of >1600 m2. Medium-fidelity mesh models were developed based on a characteristic deformed shape. A series of parametric studies were conducted using this shape paradigm to determine worst-case deformed sail shapes which produce bounding disturbance torques. A large database of shapes was produced, and the forces and moments induced by each individual shape were calculated using a Rios-Reyes reduced order generalized sail model [1]. Two were selected as reference worst-case shapes for the Solar Cruiser mission: one which produced the highest pitch/yaw root-sum-squared (RSS) torque, and one which produced the highest roll torque. The results showed that the worst-case shapes at high solar incidence angles induce significantly higher (2-10x) disturbance torques than an ideal, flat-plate sail. Even with considerable safety margins, assuming an ideal sail is unlikely to sufficiently bound the disturbances, which is critical when designing the attitude control system and sizing actuators. Accurate sail shape modeling methodologies should therefore be employed on future solar sail missions. References [1] L. Rios-Reyes and D. J. Scheeres, “Generalized Model for Solar Sails,” Journal of Spacecraft and Rockets, Vol. 42, Jan. 2005, pp. 182–185, 10.2514/1.9054.

Solar Sail↗
NASA NTRS1989

Performance evaluation of automated manufacturing systems using generalized stochastic Petri Nets

The main objective of this research is to develop a generic modeling methodology with a flexible and modular framework to aid in the design and performance evaluation of integrated manufacturing systems using a unified model. After a thorough examination of the available modeling methods, the Petri Net approach was adopted. The concurrent and asynchronous nature of manufacturing systems are easily captured by Petri Net models. Three basic modules were developed: machine, buffer, and Decision Making Unit. The machine and buffer modules are used for modeling transfer lines and production networks. The Decision Making Unit models the functions of a computer node in a complex Decision Making Unit Architecture. The underlying model is a Generalized Stochastic Petri Net (GSPN) that can be used for performance evaluation and structural analysis. GSPN's were chosen because they help manage the complexity of modeling large manufacturing systems. There is no need to enumerate all the possible states of the Markov Chain since they are automatically generated from the GSPN model.

Al-Jaar, Robert Y.↗
NASA NTRS1993

Cognitive engineering models in space systems

NASA space systems, including mission operations on the ground and in space, are complex, dynamic, predominantly automated systems in which the human operator is a supervisory controller. Models of cognitive functions in complex systems are needed to describe human performance and form the theoretical basis of operator workstation design, including displays, controls, and decision aids. Currently, there several candidate modeling methodologies. They include the Rasmussen abstraction/aggregation hierarchy and decision ladder, the goal-means network, the problem behavior graph, and the operator function model. The research conducted under the sponsorship of this grant focuses on the extension of the theoretical structure of the operator function model and its application to NASA Johnson mission operations and space station applications. The initial portion of this research consists of two parts. The first is a series of technical exchanges between NASA Johnson and Georgia Tech researchers. The purpose is to identify candidate applications for the current operator function model; prospects include mission operations and the Data Management System Testbed. The second portion will address extensions of the operator function model to tailor it to the specific needs of Johnson applications. At this point, we have accomplished two things. During a series of conversations with JSC researchers, we have defined the technical goal of the research supported by this grant to be the structural definition of the operator function model and its computer implementation, OFMspert. Both the OFM and OFMspert have matured to the point that they require infrastructure to facilitate use by researchers not involved in the evolution of the tools. The second accomplishment this year was the identification of the Payload Deployment and Retrieval System (PDRS) as a candidate system for the case study. In conjunction with government and contractor personnel in the Human-Computer Interaction Lab, the PDRS was identified as the most accessible system for the demonstration. Pursuant to this a PDRS simulation was obtained from the HCIL and an initial knowledge engineering effort was conducted to understand the operator's tasks in the PDRS application. The preliminary results of the knowledge engineering effort and an initial formulation of an operator function model (OFM) are contained in the appendices.

Mitchell, Christine M.↗
NASA NTRS1995

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

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

Degani, Asaf↗