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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Exploring Methods to Collect and Analyze Data on Human Contributions to Aviation Safety: A Panel Discussion

Focusing on undesired operator behaviors is pervasive in system design and safety management cultures in aviation. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of aviation safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform safety-related decision making and policies depends upon identifying, collecting, and interpreting safety producing behaviors in addition to safety reducing behaviors. The panel will discuss opportunities and challenges in collecting and analyzing the largely unexploited data on desired, safety-producing operator behaviors.

aviation safety↗
DOE OSTI2025

Ten questions on building stock modeling to inform energy efficiency and sustainability

To enhance economic competitiveness and ensure energy efficiency, resilience, and security, cities and governments are adopting technologies and strategies to improve their existing building stocks. This approach aims to reduce energy use, improve energy affordability, and ensure a reliable power supply while safeguarding occupants during extreme weather events that may disrupt energy services. The effectiveness of these solutions will depend on building stock characteristics, use patterns, weather conditions, evolving technologies and their markets, and a city’s socio-economic conditions. This paper presents ten questions and answers that highlight the most important issues regarding the use of building stock modeling as a powerful tool to provide insights for informing stakeholders’ actions and decision-making on energy efficiency, costs reduction, and resilience of buildings in cities. Building stock modeling should build upon the fit-for-purpose framework, balancing the use case accuracy requirements, level of complexity, and needed resources (expertise, compute). The advancements in Artificial Intelligence (AI), the increasingly available open dataset of building stock in cities, and the more affordable powerful computing will accelerate the adoption of building stock modeling across scales by researchers and practitioners to inform decision making on sustainability and efficiency.

AI↗
NASA NTRS1997

Research Initiatives and Preliminary Results In Automation Design In Airspace Management in Free Flight

The NASA and the FAA have entered into a joint venture to explore, define, design and implement a new airspace management operating concept. The fundamental premise of that concept is that technologies and procedures need to be developed for flight deck and ground operations to improve the efficiency, the predictability, the flexibility and the safety of airspace management and operations. To that end NASA Ames has undertaken an initial development and exploration of "key concepts" in the free flight airspace management technology development. Human Factors issues in automation aiding design, coupled aiding systems between air and ground, communication protocols in distributed decision making, and analytic techniques for definition of concepts of airspace density and operator cognitive load have been undertaken. This paper reports the progress of these efforts, which are not intended to definitively solve the many evolving issues of design for future ATM systems, but to provide preliminary results to chart the parameters of performance and the topology of the analytic effort required. The preliminary research in provision of cockpit display of traffic information, dynamic density definition, distributed decision making, situation awareness models and human performance models is discussed as they focus on the theme of "design requirements".

Corker, Kevin↗
NASA NTRS2003

Native Peoples-Native Homelands Climate Change Workshop: Lessons Learned

The Native Peoples-Native Homelands Climate Change Workshop was held on October 28 through November 01,1998, as part of a series of workshops being held around the U.S. to improve the understanding of the potential consequences of climate variability and change for the Nation. This workshop was specifically designed by Native Peoples to examine the impacts of climate change and extreme weather variability on Native Peoples and Native Homelands from an indigenous cultural and spiritual perspective and to develop recommendations as well as identify potential response actions. The workshop brought together interested Native Peoples, representatives of Tribal governments, traditional elders, Tribal leaders, natural resource managers, Tribal College faculty and students, and climate scientists fiom government agencies and universities. It is clear that Tribal colleges and universities play a unique and critical role in the success of these emerging partnerships for decision-making in addition to the important education function for both Native and non-Native communities such as serving as a culturally-appropriate vehicle for access, analysis, control, and protection of indigenous cultural and intellectual property. During the discussions between scientists and policy-makers from both Native and non-Native communities, a number of important lessons emerged which are key to building more effective partnerships between Native and non-Native communities for collaboration and decision-making for a more sustainable future. This talk summarizes the key issues, recommendations, and lessons learned during this workshop.

Maynard, Nancy G.↗
DOE OSTI2022

Optimal economic dispatch policy for prosumer with energy storage considering self-consumption demand

This paper analyzed the effects of self-consumption demand on the joint economic dispatch of prosumers (energy consumers who are also producers), particularly for prosumers with both energy storage and distributed energy sources (DERs). Studies in the existing literature on the economic dispatch scheduling policy of energy storage, mostly from the perspective of electricity merchants, do not address the impacts of self-consumption demand. However, due to the intermittent and high levels of uncertainty regarding DERs generation and the dynamic demand of the prosumer, production and consumption are not always simultaneous; there are two possible scenarios in each period depending on whether DERs generation can meet prosumers' self-consumption or not. Incorporating the self-consumption demand will pose modeling challenges since these two scenarios cannot occur simultaneously in each period, and different scenarios require different decisions for prosumers. Further, this paper analyzed the two scenarios separately to find the optimal storage scheduling strategy, and the results were combined to get the optimal global solution. We focused on prosumers' economic decision-making while considering self-consumption demand and the physical constraints of a battery based on dynamic programming. Our study showed that the feasible state of charge (SOC) range of storage can be segmented into several sub-ranges by SOC reference points under the above two scenarios. As a result, a prosumer's optimal scheduling can be uniquely and conveniently selected based on the sub-ranges within which the current SOC falls. The results, therefore, provided multistage decision-making guidance for prosumers with energy storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1986

Project analysis and integration area

The objective of the Project Analysis and Integration Area (PA&I) is to support the planning, analysis, integration, and decision making activities of the Flat-plate Solar Array FSA) Project. Accordingly, PA&I supports the Project by developing and documenting Project plans based, in part, on the technical and economic assessments performed by PA&I of the various technical options. Goals for module technical performance and costs, derived from National Photovoltaics Program goals, are established by PA&I for each of the major technical activities in the Project. Assessments of progress toward achievement of goals are made to guide decision making within the Project.

Source record↗
NASA NTRS2016

Predicting Real-Time Safety of the National Airspace System

To gain the situational awareness necessary for informed decision making regarding avoidance of airspace hazards, each operator must consolidate operations-relevant information from disparate sources and apply extensive domain knowledge to correctly interpret not just the current state of the NAS but forecast its (combined) evolution over the duration of the operation. This time- and workload-intensive process is periodically repeated throughout the operation so that changes can be managed in a timely manner.The imprecision, inaccuracies, inconsistency, and incompleteness of the incoming data further challenges the process. To facilitate informed decision making, this paper presents a model-based framework for the textitautomated real-time monitoring and prediction of possible effects of airspace hazards on the safety of the National Airspace System (NAS). First, hazards to flight are identified and transformed into sms, that is, quantities of interest that could be evaluated based on available data and are predictive of an unsafe event. The sms and associated thresholds that specify when an event transitions from emphsafe to emphunsafe are combined with models of airspace operations and aircraft dynamics. The framework can include any hazard to flight that can be modeled quantitatively. Models can be detailed and complex, or they can be considerably simplifed, as appropriate to the application. Real-time NAS safety monitoring and prediction begins with an estimate of the state of the NAS using the dynamic models. Given the state estimate and a probability distribution of future inputs to the NAS, we can then predict the evolution of the NAS - the future state - and the occurrence of hazards and unsafe events. The entire probability distribution of airspace sms is computed, not just point estimates, without significant assumptions regarding the distribution type andor parameters. We demonstrate our overall approach through a simulated scenario in which we predict the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress. Predictions accounting for common sources of uncertainty are included and it is shown how the predictions improve in time, become more confident, and change dynamically as new information is made available to the prediction algorithm.

safety↗
DOE OSTI2025

Foveal vision reduces neural resources in agent-based game learning

Efficient processing of information is crucial for the optimization of neural resources in both biological and artificial visual systems. In this paper, we study the efficiency that may be obtained via the use of a fovea. Using biologically-motivated agents, we study visual information processing, learning, and decision making in a controlled artificial environment, namely the Atari Pong video game. We compare the resources necessary to play Pong between agents with and without a fovea. Our study shows that a fovea can significantly reduce the neural resources, in the form of number of neurons, number of synapses, and number of computations, while at the same time maintaining performance at playing Pong. To our knowledge, this is the first study in which an agent must simultaneously optimize its visual system, along with its decision making and action generation capabilities. That is, the visual system is integral to a complete agent.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Long-Term Health Metric Development Effort

INTRODUCTION Probabilistic Risk Assessment (PRA) is a methodology applied when high-stakes decisions need to be made about complex systems. PRA often uses risk minimization to aid decision making, such as when establishing vehicle requirements or resource allocations. The NASA Human System Risk Board (HSRB) maintains the human spaceflight risk postures, many of which have in-mission medical outcomes, but the full risk set also includes performance and Long-Term Health (LTH) outcomes. An effort is underway to determine the dependencies between LTH risk outcomes and mission characteristics and to identify metrics for quantifying LTH outcomes. The LTH metrics will be incorporated into future PRA tools currently under development to support crew health and performance decision making. LONG-TERM HEALTH (LTH) RISK LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. LTH outcomes include the time and interventions needed for the astronaut to return to preflight physiological states after experiencing spaceflight hazards and recovery from any in-mission medical events that persist into the post-flight timeframe. It includes chronic complications that may arise due to experiencing in-flight medical conditions or injuries and medical conditions that occur later in life with a higher probability of occurrence or with more severity because of their spaceflight exposure. Finally, LTH outcomes can also include a reduction in life expectancy due to spaceflight exposures. Eighteen of the HSRB risks contain an LTH component, each with a unique incidence rate and consequence severity. ON-GOING LTH METRIC DEVELOPMENT EFFORTS Based on guidance from a stakeholder workshop held on June 1, 2023, only LTH outcomes with causes tied to spaceflight experience that are significantly different from normal healthy aging and which can be affected by changes in in-mission resources are targeted for inclusion within the PRA modeling efforts. Current on-going efforts include a sensitivity analysis of potential in-flight medical conditions to determine which conditions may persist into post-flight and how the consequences may be affected by in-mission medical resources. Also underway is determination of differences in the time for a return to preflight physiological baselines when in-flight countermeasures are available versus when they are not. Analyses performed with publicly available astronaut data and collaborations with the Lifetime Surveillance of Astronaut Health team are being designed to understand which LTH outcomes differ significantly from natural healthy aging. Information exchanges are also occurring with LTH risk custodians to understand how they quantify outcomes. FUTURE PLANS Risk characteristics will be determined for each LTH risk that meets our inclusion criteria and the dependencies of their outcomes to in-mission resources and mission characteristics will be established. The individual risks will be integrated together into one or more high level LTH metrics for inclusion in the PRA tool, so that LTH risks can be considered along with in-mission risks during crew health and performance system decision support trade studies.

B. E. Lewandowski↗
DOE OSTI2024

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗
NASA NTRS2006

NASA's M and S Accreditation Process Plan and Specification for Space Exploration

NASA's Exploration Systems Mission Directorate (ESMD) is implementing a management approach for modeling and simulation (M&S) that will provide decision-makers information on the model's fidelity, credibility, and quality. This information will allow the decision-maker to understand the risks involved in using a model's results in the decision-making process. This presentation will discuss NASA's overall approach to achieving formal accreditation of its models or simulations supporting space exploration. The development of a formal Accreditation Plan is a key component in the preliminary activities for modeling and simulation (M&S) assessment. This presentation will describe NASA's process for identifying risks associated with M&S use and the associated M&S assessments that will dictate the level of data certification and M&S verification and validation (V&V) activities required to support the decision-making process. The M&S Accreditation Plan and Report templates for ESMD will also be illustrated.

O'Neil, David↗
DOE OSTI2021

Implication of production tax credit on economic dispatch for electricity merchants with storage and wind farms

The production tax credit (PTC) promotes wind energy development, reduces power generation costs, and can affect merchants’ joint economic dispatch, particularly for electricity merchants with both energy storage and wind farms. Two common PTC policies are studied – in the first policy, a wind farm receives PTC by selling wind generation to the market and its storage can be used to store energy from the wind generation and energy purchased from the grid but the energy released from the storage cannot receive PTC; in the second policy, the energy released from the storage can also qualify for PTC but purchasing energy from the grid is not allowed. We then employ dynamic programming to study merchants' optimal decision-making while considering PTC and the physical characteristics of storage systems. We analytically show that the state of charge (SOC) range can be segmented into different regions by SOC reference points under two PTC policies. The merchant's optimal action can be conveniently and uniquely determined based on the region within which the current SOC falls. Moreover, this study illustrates that PTC could substantially alter the optimal scheduling policy structures by affecting reference points and their relationships. The results showed that the frequencies for charging and discharging storage decisions decreased with an increase in PTC subsidy. Last, we confirm that, although the first policy allows merchants to buy electricity from the market, the second policy can bring more profits when the PTC is large at the current PTC rates. Furthermore, the findings can provide multistage decision-making guidance to electricity merchants in the wholesale power market.

17 WIND ENERGY↗
DOE OSTI2024

Entropy removal of medical diagnostics

Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy of clinical situations using diagnostic variables (true and false positives and negatives, respectively). Decision tree representations of medical decision-making tools can be generated using diagnostic variables found in literature and entropy removal can be calculated for these tools. This concept of clinical entropy removal has significant potential for further use to bring forth healthcare innovation, such as quantifying the impact of clinical guidelines and value of care and applications to Emergency Medicine scenarios where diagnostic accuracy in a limited time window is paramount. This analysis was done for 623 diagnostic tools and provided unique insights into their utility. For studies that provided detailed data on medical decision-making algorithms, bootstrapped datasets were generated from source data to perform comprehensive machine learning analysis on these algorithms and their constituent steps, which revealed a novel and thorough evaluation of medical diagnostic algorithms.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Cape Hatteras Ecological Conservation: Delineating Shoreline and Mapping Change Along the Cape Hatteras National Seashore for Coastline Management and Transportation Corridor Adaptation Strategies

The National Park Service at Cape Hatteras National Seashore works to protect North Carolina’s Outer Banks where frequent storms bring heavy winds and flooding, leading to overwash events on the main highway, North Carolina Highway 12. Shorelines are susceptible to erosion directly affecting transportation and housing infrastructures. Storm events can disrupt transportation on NC-12 and ferry service from Ocracoke Island to Hatteras Island, leaving inhabitants stranded on Ocracoke Island for indefinite amounts of time. The National Park Service’s current decision-making practices involve mitigating infrastructure damage by enlisting the help of North Carolina’s Department of Transportation and finding ways to relocate this infrastructure, as well as dredging and sediment placement that support beach nourishment efforts. Our NASA DEVELOP team partnered with the National Park Service to explore the use of optical data to delineate shoreline and map coastline change from 2014 to 2024. We used Earth observations collected by Landsat 8 Operational Land Imager, Landsat 9 Operational Land Imager-2, and Sentinel-2 MultiSpectral instrument to support decision-making related to prioritizing strategic planning for transportation corridor adaptations including potential relocation of infrastructure, and beach nourishment efforts. We derived coastline maps by consolidating images from each year to create composite images for winter and summer coastline seasonal oscillation patterns. The results highlight shoreline loss over the ~10-year study period, and the difference in shoreline inundation in the winter and summer seasons. These observations create a better understanding of successful mitigation efforts and allow the National Park Service to continue to focus on plans for infrastructure updates.

Ella Haugen↗
DOE OSTI2025

Economic Evaluation of Modernization Expenditures for Electric Utility Distribution Systems: A Guide for Utility Regulators

Cost-effectiveness evaluation of potential grid modernization solutions is integral to integrated distribution system planning (IDSP). This report synthesizes and updates prior cost-effectiveness approaches identified by the U.S. Department of Energy for grid modernization investments, incorporating multi-objective decision-making. The structure of the report follows the IDSP process, from identifying objectives and priorities to prioritizing grid solutions. The report details two methods for conducting initial cost-effectiveness screening of individual and interdependent grid components: (1) Lowest Reasonable Cost and (2) Benefit-Cost Analysis. Drawing on solutions that passed the initial cost-effectiveness screen, the utility prioritizes grid solutions based on policy objectives and priorities, regulatory compliance, operational efficiencies, and other factors to develop a portfolio of distribution solutions. The utility uses multi-objective decision-making to assess each proposed expenditure against each objective and respective metric. The utility applies a weighting factor, reflecting the priority ranking of the objective, to the total numerical “score” based on the contribution of the proposed solution to addressing each objective. Ultimately, the utility ranks each expenditure from highest to lowest priority using the final score for each solution as well as its cost. The report includes examples of emerging best practices for states and utilities and a cost-effectiveness process checklist.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

Performance Effects of Display Incogruity in a Digital and Analog Clock Reading Task

In an era of increasing automation, it is important to design displays and input devices that minimize human error. In this context, information concerning the human response to the detection of incongruous information is important. Such incongruous information can be operationalized as unexpected (perhaps erroneous) information on which a decision by the human or operation by an automated system is based. In the aviation environment, decision making when faced with inadequate, incomplete, or incongruous information may occur in a failure scenario. An additional challenge facing the human operator in automated environments is maintaining alertness or vigilance. The vigilance issue is of particular concern as a factor that may interact with performance when faced with inadequate, incomplete, or incongruous information. From the literature on eye-scan behavior we know that the time spent looking at a particular display or indicator is a function of the type of information one is trying to discern from the display. For example, quick glances are all it takes for confirming that an indicator is in a normal position or range, whereas a continuous look of several seconds may be required for confirmation that a complex control input is having the desired effect. Important to consider is that while an extended look takes place, visual input from other sources may be missed. Much like an extended look, the interpretation of incongruous information may require extra time. The present experiment was designed to explore the performance consequences of a decision making task when incongruous information was presented. For this experiment a display incongruity was created on a subset of trials of a clock reading laboratory task. Display incongruity was made possible through presentation of 'impossible' times (e.g. 1:65 or 11:90). Subjects made 'same' 'different' decisions and keyboard responses to pairings of Analog-Analog (AA), Digital-Digital (DD), and Analog- Digital (AD), display combinations. For trials during which display incongruities were not presented, based on prior research comparing digital and analog clock displays, it would be expected that the Digital-Digital condition would result in the shortest response times and the Analog-Analog and Analog-Digital conditions would have longer response times. The performance consequence expected on trials with incongruous times would be very long response times.

J. Raymond Comstock, Jr.↗
NASA NTRSDate not supplied

Expanding Our Understanding of What Constitutes a Safety-Relevant Occurrence

Focusing on undesired operator behaviors is pervasive in system design and safety management cultures. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. The study of human contributions to safety represents a vast and largely unexplored opportunity to learn. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform system design, safety-related decision making and policies depends upon identifying, collecting, and interpreting safety producing behaviors in addition to safety reducing behaviors.

Jon B Holbrook↗
NASA NTRSDate not supplied

The NASA DEVELOP Model of Community Science & Engagement: Localizing Earth Science Information

The NASA DEVELOP Program conducts 10 week feasibility studies that apply Earth observation data to address community priorities and support informed decision making. Part of NASA’s Earth Action Capacity Building Program, DEVELOP builds skills in both participants ( recent graduates, and early/transitioning career professionals), who work on small interdisciplinary project teams, and partner organizations (state and local governments, federal agencies, non profit and for profit organizations, universities, and international organizations) that work closely with DEVELOP to design the project. Projects address a wide variety of environmental issues, such as disaster risk and resilience, air pollution, and the impact of urban development, with a growing number of projects exploring how satellite data can help inform decision making around environmental injustices. A subset of DEVELOP partner organizations are local municipalities or community led non profits, with the co production model serving as an effective engagement tool and an introduction for communities to engage in Earth science research and become familiar with satellite remote sensing. This presentation will highlight the DEVELOP co production model, community project use cases, and lessons learned in partnering with local communities.

Michael Pazmino↗