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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

Elgin, Peter D.↗
NASA NTRS1994

Shared Problem Models and Crew Decision Making

The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

Orasanu, Judith↗
DOE OSTI2020

Regulatory Decision-Making Process Using 'Weight of Evidence: An Evidence Integration Approach' by the State of Washington at the Hanford Site - 20163

Performance Assessment and Environmental Impact Statement Modeling, Human and Ecological Risk Assessments are the tools used by the Washington State Department of Ecology (Ecology) to make regulatory decisions for permitting and cleanup. These efforts all inherently have large amounts of uncertainty no matter how many alternative approaches are attempted. Professional feedback from tribal governments, stakeholders, federal and state regulators, the public and independent peer review groups are taken into account in this process of informed decision making. The process also includes full evaluation of the comments and the associated reviews made by the various peer review groups such as the Low -Level Waste Disposal Facility Federal Review Group (DOE order 435.1) and the Nuclear Regulatory Commission (NRC). The evolution of technology has produced quicker and more efficient fate and transport modeling tools with related quantification of uncertainties and their significance. Groundwater and vadose zone models have been expanded across the entire Hanford site. Many of the technical approaches identified in the Washington State Regulations are updated using current knowledge to better understand the complexities of the Hanford Site using the latest state of the art tools for risk assessment and modeling. More emphasis and time are directed on defining uncertainty and then managing the uncertainty. One added tool is to run sensitivity cases based on informed decision making. The weight of evidence approach considers all relevant information in an integrative assessment that takes into account the kinds of evidence available, the quality and quantity, the uncertainty and error associated with each type, and how they fit together. Evidence of integration involves looking at systematic reviews and evaluating their strengths and weaknesses. In conclusion, Ecology, Washington State's lead regulatory agency at the Hanford site, has had to modify its site closure approach compared to the rest of the state. A more holistic approach dealing with the Hanford site as an integrated system has evolved leading to a defensible informed approach for regulatory closure decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Integrated Risk-Informed Decision-Making for an ALMR PRISM

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2002

Innovation, Technology and Decision Making: A Perspective for Strategic Action in Firms

Innovation, technology, and the making of decisions are tightly intertwined in what can generally be called, strategic decision making. Although true for all firms, it is especially true in innovative, high technology firms that operate in a turbulent, fast moving environment where strategic decisions must be made accurately and quickly to survive. This paper looks at some factors reported in the literature that affect how and why the strategic decision process is so important, especially in companies in fast-moving, competitive environments. The work of several prominent authors who looked critically at past theory and research, and the current state of knowledge and practice, provides a perspective of how firms make strategic decisions.

Mulenburg, Gerald M.↗
DOE OSTI2016

Effects of Gain/Loss Framing in Cyber Defense Decision-Making

Cyber defense requires decision making under uncertainty. Yet this critical area has not been a strong focus of research in judgment and decision-making. Future defense systems, which will rely on software-defined networks and may employ ‘moving target’ defenses, will increasingly automate lower level detection and analysis, but will still require humans in the loop for higher level judgment. We studied the decision making process and outcomes of 17 experienced network defense professionals who worked through a set of realistic network defense scenarios. We manipulated gain versus loss framing in a cyber defense scenario, and found significant effects in one of two focal problems. Defenders that began with a network already in quarantine (gain framing) used a quarantine system more than those that did not (loss framing). We also found some difference in perceived workload and efficacy. Alternate explanations of these findings and implications for network defense are discussed.

cyber security↗
DOE OSTI2023

Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making

One of the great challenges with decision making tasks on real world systems is the fact that data is sparse and acquiring additional data is expensive. In these cases, it is often crucial to make a model of the environment to assist in making decisions. At the same time, limited data means that learned models are erroneous, making it just as important to equip the model with good predictive uncertainties. In the context of learning sequential decision making policies, these uncertainties can prove useful for informing which data to collect for the greatest improvement in policy performance \citep{mehta2021experimental, mehta2022exploration} or informing the policy about unsure regions of state and action space to avoid during test time \citep{yu2020mopo}. Additionally, assuming that realistic samples of the environment can be drawn, an adaptable policy can be trained that attempts to make optimal decisions for any given possible instance of the environment \citep{ghosh2022offline, chen2021offline}. In this work, we examine the so-called ``probabilistic neural network'' (PNN) model that is ubiquitous in model-based reinforcement learning (MBRL) works. We argue that while PNN models may have good marginal uncertainties, they form a distribution of non-smooth transition functions. Not only are these samples unrealistic and may hamper adaptability, but we also assert that this leads to poor uncertainty estimates when predicting multiple step trajectory estimates. To address this issue, we propose a simple sampling method that can be implemented on top of pre-existing models.We evaluate our sampling technique on a number of environments, including a realistic nuclear fusion task, and find that, not only do smooth transition function samples produce more calibrated uncertainties, but they also lead to better downstream performance for an adaptive policy.

Offline Reinforcement Learning↗
DOE OSTI2017

'A Good Decision Is Based On Information, Not On Numbers' - A Process For National Strategic Decision Making - 17203

Waste management decision making is the process used by waste owners to determine and justify choices in across the lifecycle of a waste (from the manner of generation or retrieval to final disposition). In the UK, waste owners in the nuclear industry are obligated, by their environmental permits and authorisations, to demonstrate the application of robust and well-underpinned decision making processes for waste management. This is captured through the requirement for waste owners to demonstrate the identification and implementation of Best Available Technique (BAT). The National Waste Programme (NWP), led by LLW Repository Ltd, is a UK wide programme which leads the implementation of the UK National Strategy for the management of solid LLW from the nuclear industry [1] and which aims to deliver a self-sustaining culture for optimised management of Low Level Waste (LLW) in the UK. Recognising the requirement on waste owners, the NWP has - in conjunction with appointed contractors - led the development and publication of national strategic optioneering studies (so-called national strategic BAT studies) to support waste owners. Recognising the benefits that this approach to optioneering and strategic decision making could have for other waste producers, this paper provides an overview of the process used for the development of the suite of national strategic BAT assessments for the NWP. It details: the main phases of the process, the key features of each process phase, the benefits of the approach and key learning from its deployment in practice. Note: The legislative regime in England and Wales requires the identification and application of BAT. There is an equivalent regime in Scotland known as Best Practicable Environmental Option (BPEO) and Best Practicable Means (BPM). The requirements are comparable across the two legislative regimes and, for the purposes of simplicity, the term BAT will be utilised in this paper. The approach and outcomes of the national strategic optioneering process described are applicable across the UK. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1994

Situational Variables in Expert Pilot Decision Making

In traditional laboratory studies of decision making, the experimenter structures the problem, defines the goal and specifies available information. In contrast, when people make decisions in non-laboratory environments characterized as complex, dynamic and consequential, they must first identify the problem and determine what information and responses are relevant. The present research was designed to investigate which situational aspects are important to experienced pilots making aviation decisions. Twenty-eight professional pilots were asked to sort descriptions of 22 aircraft incidents into piles involving similar types of major decisions. Preliminary analyses suggest four underlying variables: time pressure, risk level, available resources, and certainty of goal attainment.

Fischer, Ute↗
DOE OSTI2016

A Paradigm Shift continued: An Application of Structured Decision Making for Sustainable Waste Management - 16486

Structured decision making presents an opportunity for DOE and others engaged in solving complex environmental and waste management problems to find solutions that are stakeholder engaged and cost effective. This approach represents a paradigm shift that was introduced in a series of papers and a panel session at the WM2015 Symposium. The advantages of structured decision making over less formal approaches to decision making include technical defensibility, traceability and transparency. Structured decision making also overcomes the limitations of misapplication of conservatism in modeling, addresses stakeholder concerns and competing objectives directly, and provides a formal method through which internal and external stakeholders are encouraged to collectively and carefully consider all relevant attributes of solving complex problems. The first requirement of this paradigm shift is a realization and recognition that the problems faced are inherently decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Structured decision making is, very simply, formalized common sense. The formalities include: framing the problem; identification of objectives and measures for valuing those objectives; costs or values associated with those objectives; management options or alternatives for taking action that are tied directly to the objectives; and, science-based models to evaluate the options. Decision analysis is used to evaluate objectives and choose management options by balancing probability and consequence. The science-based models are built probabilistically based on expectation and uncertainty, and costs and value judgments are used to fulfill addressing stakeholder concerns. Consequently, this approach avoids misplaced conservatism in science-based modeling and properly places values in the objectives component of a decision model. This approach honestly addresses uncertainty and value judgments and balances these competing components to find the most effective decision. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is used to support an application of this paradigm shift towards structured decision making. In this application objectives and management options for a waste disposal problem at the Los Alamos National Laboratory are identified, and features, events and processes are described and defined to form the basis of a conceptual site model. This establishes the decision model structure. Objectives are addressed through the three pillars of sustainability - economic, environmental, and social - and also address regulatory concerns or constraints. Management options include removal of waste to another location and engineering designs for leaving waste in place. Using structured decision making, the relationship between objectives, management options, and the conceptual site model is made clear, and leads to a comprehensive, defensible, transparent and traceable approach to effective decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1994

Decision Making in Action

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Orasanu, Judith↗
NASA NTRS1995

Decision Making in the Airplane

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Orasanu, Judith↗
DOE OSTI2018

On the application of the expected log-likelihood gain to decision making in molecular replacement

Molecular-replacement phasing of macromolecular crystal structures is often fast, but if a molecular-replacement solution is not immediately obtained the crystallographer must judge whether to pursue molecular replacement or to attempt experimental phasing as the quickest path to structure solution. The introduction of the expected log-likelihood gain has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is the log-likelihood gain on intensity expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error and the measurement errors in the data. It is shown how the eLLG may be used to answer the question 'can I solve my structure by molecular replacement?'. However, this is only the most obvious of the applications of the eLLG. It is also discussed how the eLLG may be used to determine the search order and minimal data requirements for obtaining a molecular-replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement and likelihood-guided model pruning.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Evaluation of NASA-sponsored research on capital investment decision making in the civil aviation industry

Significant findings of three studies undertaken to provide the NASA Aircraft Energy Efficiency (ACEE) Office with information regarding how aircraft manufacturers and commercial airlines make investment decisions concerning the acquisition of new and derivative technology are analyzed and their general implications explored. Topics discussed include: the market for airline aircraft, factors affecting the corporate decision making process of air transport manufacturers, and flight equipment purchasing practices of representative air carriers.

Donovan, D. J.↗