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DOE OSTI2022

Modeling and Analysis of a Micro-reactor using the DireWolf Code Suite

Micro-reactors, specifically those cooled with heat pipes, are tightly coupled systems which require multi-physics tools to accurately model both steady-state and transient behavior. Idaho National Laboratory’s DireWolf code suite is tailor-built to model heat-pipe reactors. DireWolf’s ability to model the coupled steady-state behavior of a heat-pipe micro-reactor are demonstrated herein. The DireWolf modeling methodology is described, and a micro-reactor design is introduced. A full-core model is developed, and the steady-state coupled neutronics-thermal analysis is performed. Results of the analyses, including flux, power, and temperature distributions are presented and discussed. This is a Westinghouse Electric Company (WEC) led publication.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

CRiSPPy: An advanced hydropower scheduling tool for the Colorado River Storage Project

The Western Area Power Administration (WAPA) plays a vital role in delivering reliable and cost-effective hydroelectric power to millions of customers across the western United States. The Colorado River Storage Project (CRSP) carries out WAPA’s mission in Arizona, Utah, Colorado, New Mexico, Nevada, Wyoming and Texas. Achieving this mission requires effective management of the Colorado River system, and depends on the use of advanced analytical tools and modeling methodologies. For many years, CRSP has relied on the Generation and Transmission Maximization Superlite (GTMax SL) model for its mid-term and long-term hydroscheduling needs. However, the evolving energy market, power system operations, environmental rules, and hydrology conditions, coupled with advancements in computational capabilities, have necessitated the development of a more modern and robust solution. This report introduces the Colorado River Storage Project Python-based (CRiSPPy) model, a new, advanced hydropower scheduling tool developed to address CRSP ever-evolving challenges. CRiSPPy represents a significant leap forward in our ability to model and optimize the operation of the Colorado River system. It incorporates state-of-the-art optimization algorithms, enhanced data management capabilities, and an advanced graphical user interface, providing WAPA CRSP personnel with unprecedented insights and decision-making support. This document details the development, capabilities, and implementation of CRiSPPy. It is intended to serve as a comprehensive resource for WAPA staff, stakeholders, and anyone interested in the future of hydropower scheduling in the Colorado River Basin. We are confident that CRiSPPy will enhance WAPA's mission while adapting to the challenges of a dynamic and increasingly complex environment. The version of CRiSPPy described in this report is the version 2.3. New versions of CRiSPPy will be developed as the tool keeps evolving to address CRSP challenges.

13 HYDRO ENERGY↗

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↗

DOE OSTI2021

Experimental validation of an integrated modelling approach to neutron emission studies at JET

An integrated modelling methodology for the calculation of realistic plasma neutron sources for the JET tokamak has been developed. The computational chain comprises TRANSP plasma transport and DRESS neutron spectrum calculations, and their coupling to the MCNP neutron transport code, bridging plasma physics and neutronics. Here, we apply the developed methodology to the analysis of neutron emission properties of deuterium and helium plasmas at JET, and validate individual modelling steps against neutron diagnostic measurements. Two types of JET discharges are modelled—baseline-like and three-ion radio-frequency scenarios—due to their diversity in plasma heating, characteristics of the induced fast ion population, and the imprint of these on neutron emission properties. The neutron emission modelling results are quantitatively compared to the total neutron yield from fission chambers, neutron emissivity profiles from the neutron camera, neutron spectra from the time-of-flight spectrometer, and neutron activation measurements. The agreement between measured and calculated quantities is found to be satisfactory for all four diagnostic systems within the estimated experimental and computational uncertainties. Additionally, the effect of neutrons not originating from the dominating D(D, n) 3 He reactions is studied through modelling of triton burnup DT neutrons, and, in mixed D- 3 He plasmas, neutrons produced in the 9 Be(D, nγ) 10 B reaction on impurities. It is found that these reactions can contribute up to several percent to the total neutron yield and dominate the neutron activation of samples. Finally, the effect of MeV-range fast ions on the neutron activation of 115 In and 27 Al samples is measured and computationally validated.

integrated modelling↗

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.↗

DOE OSTI2021

Impact of size and thermal gradient on supercooling of phase change materials for thermal energy storage

Phase change material based thermal energy storage has many current and potential applications in the heating and cooling of buildings, battery and electronics thermal management, thermal textiles, and dry cooling of power plants. However, connecting lab scale thermal data obtained with differential scanning calorimetry (DSC) to the performance of large-scale practical systems has been a major challenge primarily due to the dependence of supercooling on the size and temperature gradient of the system. Here we show how a phase change material’s supercooling behavior can be characterized experimentally using common lab scale thermal analysis techniques. We then develop a statistics based theoretical model that uses the lab-scale data on small samples to quantitatively predict the supercooling performance for a general thermal energy storage application of any size, including also allowing for the possibility of temperature gradients. Finally, we validate the modeling methodology by comparing to experimental results for solid-solid phase change in neopentyl glycol, which shows how the model successfully predicts the changes in supercooling temperature across a large range of cooling rates (2 orders of magnitude) and volumes (3 orders of magnitude). By accounting for thermal gradients, the model avoids ~2x error incurred by lumped approximations.

36 MATERIALS SCIENCE↗

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↗

DOE OSTI2023

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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.↗

DOE OSTI2025

Predicting Multicomponent Aqueous Phase Adsorption Equilibria of Organic Acids Using the Generalized Brunauer–Emmett–Teller Isotherm Model

Here, to support process development of adsorptive separation of organic acids, this work presents a thermodynamic modeling methodology to predict multicomponent aqueous phase organic acid adsorption equilibria from single-component adsorption isotherms using the generalized Brunauer–Emmett–Teller isotherm model (gBET). With the organic acid fugacities rigorously accounting for the aqueous phase organic acid solution chemistry and solution nonideality, gBET precisely represents the single-component adsorption isotherms and accurately predicts the binary and ternary mixed-acid adsorption equilibria for the ranges of initial pH (∼3–7), acid concentration (100–400 mmol/L), and temperature (298.15–328.15 K) with less than 10% average absolute relative deviation. In addition, gBET with pH-independent parameters provides insights into the underlying adsorption phenomena, including the adsorbate loadings and compositions in the monolayer and subsequent layers under varying initial pH, temperature, concentration, and composition. The gBET model predictions outperform the predictions from the overloading model and the Ideal Dilute Solution Theory.

09 BIOMASS FUELS↗

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.↗

DOE OSTI2021

Stochastic parametric skeletal dosimetry model for humans: General approach and application to active marrow exposure from bone-seeking beta-particle emitters

The objective of this study is to develop a skeleton model for assessing active marrow dose from bone-seeking beta-emitting radionuclides. This article explains the modeling methodology which accounts for individual variability of the macro- and microstructure of bone tissue. Bone sites with active hematopoiesis are assessed by dividing them into small segments described by simple geometric shapes. Spongiosa, which fills the segments, is modeled as an isotropic three-dimensional grid (framework) of rod-like trabeculae that “run through” the bone marrow. Randomized multiple framework deformations are simulated by changing the positions of the grid nodes and the thickness of the rods. Model grid parameters are selected in accordance with the parameters of spongiosa microstructures taken from the published papers. Stochastic modeling of radiation transport in heterogeneous media simulating the distribution of bone tissue and marrow in each of the segments is performed by Monte Carlo methods. Model output for the human femur at different ages is provided as an example. The uncertainty of dosimetric characteristics associated with individual variability of bone structure was evaluated. An advantage of this methodology for the calculation of doses absorbed in the marrow from bone-seeking radionuclides is that it does not require additional studies of autopsy material. The biokinetic model results will be used in the future to calculate individual doses to members of a cohort exposed to 89,90 Sr from liquid radioactive waste discharged to the Techa River by the Mayak Production Association in 1949–1956. Further study of these unique cohorts provides an opportunity to gain more in-depth knowledge about the effects of chronic radiation on the hematopoietic system. In addition, the proposed model can be used to assess the doses to active marrow under any other scenarios of 90 Sr and 89 Sr intake to humans.

59 BASIC BIOLOGICAL SCIENCES↗

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↗