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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 NTRS2017

An ISRU Propellant Production System to Fully Fuel a Mars Ascent Vehicle

In-Situ Resource Utilization (ISRU) will enable the long term presence of humans beyond low earth orbit. Since 2009, oxygen production from the Mars atmosphere has been baselined as an enabling technology for Mars human exploration by NASA. However, using water from the Martian regolith in addition to the atmospheric CO2 would enable the production of both liquid Methane and liquid Oxygen, thus fully fueling a Mars return vehicle. A case study was performed to show how ISRU can support NASA's Evolvable Mars Campaign (EMC) using methane and oxygen production from Mars resources. A model was built and used to generate mass and power estimates of an end-to-end ISRU system including excavation and extraction water from Mars regolith, processing the Mars atmosphere, and liquefying the propellants. Even using the lowest yield regolith, a full ISRU system would weigh 1.7 mT while eliminating the need to transport 30 mT of ascent propellants from earth.

Mars Surface↗
NASA NTRS2018

Survey of Methods to Predict Controller Workload for Real-Time Monitoring of Airspace Safety

The Real Time Safety Monitoring (RTSM) approach allows for assessment and prediction of the safety margin in the National Airspace System (NAS) to help preempt incidents and accidents, rather than having to reactively mitigate them. In RTSM, the NAS is modeled using state variables, and safety metrics are defined in terms of these state variables. The safety metrics have been classified as weather-related, airspace-related, and human-related. Many of the formulated human-related safety metrics need an estimate of the controller workload for their computation. However, this computation is not trivial. Hence, in this report, we perform a literature survey to identify the different factors that enable the computation of controller workload and categorize these factors. Next, we describe studies undertaken to determine a minimal set of factors that pro- vide a correct assessment of controller workload. Lastly, we survey approaches for evaluating how well the selected factors correlate with the controllers' subjective assessment of their workload. Based on this survey, we present factors beneficial to computing and predicting controller workload in real time, and discuss the status of data sources necessary for these computations.

National Airspace System↗
NASA NTRSDate not supplied

Developing Mission Segment-Specific Clinical Data for Impact

Space exploration missions represent a significant future objective for NASA’s human spaceflight operations for the near and long term. By operating missions during longer periods and over further distances, NASA’s mission planning models, hardware systems, and medical capabilities will be stretched beyond their original design constraints. The necessity of medical training and medical supply manifesting for such missions is likely to become incredibly intricate as trade-space analysis is performed over varying mission profiles. For this purpose, IMPACT was created to extend and improve the Integrated Medical Model (IMM) which is used for International Space Station (ISS) medical predications and consists of a probabilistic risk assessment tool that simulates missions to calculate risks given the constraints on crew complement, mission duration and activity (such as Extravehicular Activities), power, communication, mass, volume, and evacuation consideration as well as to predict mission outcomes. Currently, the medical evidence used to support IMPACT remains static, addressing risks of a medical condition and the impacts of the condition during spaceflight only, but is only calculated for a small number of mission parameters. Extended missions will consist of new and varied living environments, changing gravitational loads, and dynamic working requirements. Medical risks are not typically constant but will change depending upon the physical and physiological environment of the body during all phases of a mission. Risks are likely to shift during different mission segments, and understanding how components of a mission profile change risks will assist mission planners to increase chances for mission success.

Christopher Zahner↗
NASA NTRS2000

Research into the effects of astronaut motion on the spacecraft: a review

The paper reviews the research that has been undertaken to understand and quantify the disturbance effects of the astronaut's motion inside and outside the spacecraft on the vehicle's attitude and acceleratory environment. In early investigations, the dynamic interaction of astronauts, modeled as point masses, and the spacecraft, modelled as a rigid body, was analyzed. Through ground-based experiments and the modeling of astronaut-induced forces and moments as stochastic processes, it became possible to estimate the magnitude and energy content of the loads produced by the astronaut. The first experiment in space to measure the astronaut-induced disturbances was conducted on the Skylab orbital station. Loads generated while performing routine operations were measured on board the Space Shuttle in 1994 and on the space station Mir in 1996-1997. c 2001 Elsevier Science Ltd. All rights reserved.

Skylab Project↗
DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Cooperative control of visual displays for telemanipulation

Two cooperative control schemes for telerobot visual displays are addressed. In the first scheme, on-the-screen visual enhancements such as reference lines indicating the vertical height of the robot hand, a stick figure model of the robot hand, and its projection on the horizontal grid plane are constructed by the interactive cooperation between the human operator and the telerobotic system, and then superimposed on the video screen. Experimental results with a five-degree-of-freedom robot and a frame grabber indicate that superimposition of visual enhancements on the video screen greatly improves telemanipulation task performance. In the second scheme, the position and orientation of an object on video screens are determined interactively; these then assist the telerobotic system in executing the human operator's task-level commands autonomously.

Kim, Won S.↗
NASA NTRS1992

Computer aided systems human engineering: A hypermedia tool

The Computer Aided Systems Human Engineering (CASHE) system, Version 1.0, is a multimedia ergonomics database on CD-ROM for the Apple Macintosh II computer, being developed for use by human system designers, educators, and researchers. It will initially be available on CD-ROM and will allow users to access ergonomics data and models stored electronically as text, graphics, and audio. The CASHE CD-ROM, Version 1.0 will contain the Boff and Lincoln (1988) Engineering Data Compendium, MIL-STD-1472D and a unique, interactive simulation capability, the Perception and Performance Prototyper. Its features also include a specialized data retrieval, scaling, and analysis capability and the state of the art in information retrieval, browsing, and navigation.

Boff, Kenneth R.↗
NASA NTRS1993

Space Station Freedom: a unique laboratory for gravitational biology research

The advent of Space Station Freedom (SSF) will provide a permanent laboratory in space with unparalleled opportunities to perform biological research. As with any spacecraft there will also be limitations. It is our intent to describe this space laboratory and present a picture of how scientists will conduct research in this unique environment we call space. SSF is an international venture which will continue to serve as a model for other peaceful international efforts. It is hoped that as the human race moves out from this planet back to the moon and then on to Mars that SSF can serve as a successful example of how things can and should be done.

NASA Program Life Sciences Management↗
NASA NTRS2009

Implications of Advanced Crew Escape Suit Transpiration for the Orion Program

Human testing was conducted to more fully characterize the integrated performance of the Advanced Crew Escape Suit (ACES) with liquid cooling provide by an Individual Cooling Unit (ICU) across a broad range of environmental conditions and metabolic rates. Together with a correlation for the ACES Liquid Cooling Garment as a function of inlet temperature, metabolic rate, and crew size, a reasonably conservative correlation for core temperature was achieved for the human thermal model applied to the ACES with ICU cooling. A key observation for this correlation was accounting for transpiration of evaporated sweat through the Gortex(Registered TradeMark) liner of the ACES indicated by as much as 0.6 lbm of sweat evaporated over the course of the 1 hour test profile, most of which could not be attributed to respiration or head sweat evaporation of the crew. Historically it has been assumed that transpiration was not an important design feature of the ACES suit. The correlated human thermal model will show transpiration to be highly useful in hot survival situations for the Orion Program when adequate liquid cooling is not available.

Bue, Grant↗
NASA NTRS2016

Simulation and Flight Test Data Collection Review for Supporting Phase 1 Detect and Avoid MOPS

RTCA Special Committee 228 is a consortium of government, industry, and academic organizations tasked to develop minimum operational performance standards for UAS detect and avoid systems. The UAS in the NAS (National Airspace System) project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. Over the past 3 years, the project has executed a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. The purpose of this briefing is to summarize the models developed and data collected to overcome UAS integration barriers, so UAS can remain well clear of all traffic.

Santiago, Confesor↗
NASA NTRS1997

Human-Centered Technologies and Procedures for Future Air Traffic Management

The use of various methodologies to predict the impact of future Air Traffic Management (ATM) concepts and technologies is explored. The emphasis has been on the importance of modeling coordination and cooperation among multiple agents within this system, and on understanding how the interactions among these agents will be influenced as new roles, responsibilities, procedures and technologies are introduced. To accomplish this, we have been collecting data on performance under the current air traffic management system, identifying critical problem areas and looking for examples suggestive of general approaches for solving such problems. Using the results of these field studies, we have developed a set of concrete scenarios centered around future designs, and have studied performance in these scenarios with a set of 40 controllers, dispatchers, pilots and traffic managers.

Smith, Philip↗
NASA NTRS2023

A Pilot Project for Quantifying the Effect of Medical Provider Knowledge, Skills, and Abilities on Outcomes for Spaceflight Using a Probabilistic Risk Assessment Tool

In order to enable the future of long-duration deep space exploration we must confront the uncertainty in medical risk. Limitations of communication, resupply, and evacuation in deep space will require a high degree of crew autonomy and accurate risk assessment will be critical to ensure adequate crew training and medical system design. To address this, NASA’s Human Research Program Exploration Medical Capability Element has developed the Informing Mission Planning via Analysis of Complex Tradespaces Tool (IMPACT). IMPACT is a suite of tools that can provide evidence-based, data-driven trade space assessments between available medical resources in the mass- and volume-constrained environment of a deep space exploration vehicle. In the current model, medical conditions either can or cannot be treated based on the availability of medical system resources and equipment. However, medical outcomes often depend just as much on the knowledge, skills, and abilities (KSA) of the provider operating the system. This paper presents a method for modeling and quantifying the effect of medical officer KSA on medically relevant mission risk outcomes during spaceflight.

capabilities↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada: (CY2017 January 2017–December 2017, Rev. 0)

Corrective Action Unit (CAU) 98: Frenchman Flat on the Nevada National Security Site was the location of 10 underground nuclear tests. CAU 98 underwent a series of investigations and actions in accordance with the Federal Facility Agreement and Consent Order to assess contamination of groundwater by radionuclides from the tests. A Closure Report completed that process in 2016 and called for long-term monitoring, use restrictions (URs), and institutional controls to protect the public and environment from potential exposure to contaminated groundwater. Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2017. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. The 86,000-picocuries-per-liter (pCi/L) tritium concentration in one of the wells is about 12 percent higher than measured in 2016 but is over an order of magnitude less than the peak value measured in the well in 1980. The concentration in the other source/plume well is lower than measured in 2016. The water-level monitoring network includes 16 wells. Depth to water measured in 2017 is generally consistent with recent measurements for most wells. Water-level declines differing from long-term trends were observed in four wells. Three of these (WW-4, WW-4A, and WW-5B) are water-supply wells that experienced increases in pumping during the year. No definitive cause for the sharp decline in the fourth well (ER-5-3-2) in 2016 is known as yet. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

CY2018 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2018–December 2018, Revision 1)

Corrective Action Unit (CAU) 98: Frenchman Flat on the Nevada National Security Site was the location of 10 underground nuclear tests. CAU 98 underwent a series of investigations and actions in accordance with the Federal Facility Agreement and Consent Order to assess contamination of groundwater by radionuclides from the tests. A Closure Report completed that process in 2016 and called for long-term monitoring, use restrictions (URs), and institutional controls to protect the public and environment from potential exposure to contaminated groundwater. Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2018. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2018 as compared to measurements in 2017. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2018 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, despite small increases in measured water levels in 2018. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2018. Rising water-level trends continue to be observed in two relatively deep wells (ER-5-3 deep piezometer and ER-5-4-2), and also in former supply Well WW-5A. The current supply wells exhibit relatively erratic water levels associated with pumping activities. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CY2019 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2019–December 2019), Revision 1

Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2019. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2019 as compared to measurements in 2018. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2019 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, though changes from 2018 to 2019 are minimal. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2019. Rising water-level trends continue to be observed in Well ER-5-3 deep piezometer and former water supply Well WW-5A. Water supply Well WW-5B experienced a rise in water level as a result of an absence of pumping in the first part of the year (due to a mechanical problem), whereas water levels declined in WW-4 and WW-4A in response to greater pumping in 2019. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

A control theory model for human decision making

The optimal control model for pilot-vehicle systems has been extended to handle certain types of human decision tasks. The model for decision making incorporates the observation noise, optimal estimation, and prediction concepts that form the basis of the model for control behavior. Experiments are described for the following task situations: (1) single decision tasks; (2) two decision tasks; and (3) simultaneous manual control and decision tasks. Using fixed values for model parameters, single-task and two-task decision performance scores to within an accuracy of 10 percent can be predicted. The experiment on simultaneous control and decision indicates the presence of task interference in this situation, but the results are not adequate to allow a conclusive test of the predictive capability of the model.

Levison, W. H.↗