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NASA NTRS2010

Achieving a Risk-Informed Decision-Making Environment at NASA: The Emphasis of NASA's Risk Management Policy

This slide presentation reviews the evolution of risk management (RM) at NASA. The aim of the RM approach at NASA is to promote an approach that is heuristic, proactive, and coherent across all of NASA. Risk Informed Decision Making (RIDM) is a decision making process that uses a diverse set of performance measures along with other considerations within a deliberative process to inform decision making. RIDM is invoked for key decisions such as architecture and design decisions, make-buy decisions, and budget reallocation. The RIDM process and how it relates to the continuous Risk Management (CRM) process is reviewed.

Dezfuli, Homayoon↗

DOE OSTI2024

Opportunities and Challenges in the Visualization of Energy Scenarios for Decision-Making: Preprint

Scenario studies are a technique for representing a range of possible complex decisions through time, and analyzing the impact of those decisions on future outcomes of interest. It is common to use scenarios as a way to study potential pathways towards future build-out and decarbonization of energy systems. The results of these studies are often used by diverse energy system stakeholders - such as community organizations, power system utilities, and policymakers - for decision-making using data visualization. However, the role of visualization in facilitating decision-making with energy scenario data is not well understood. In this work, we review visualization designs employed in energy scenario studies found in the literature and publicly accessible online sources. We discuss the effectiveness of existing techniques particularly in regards to decision-making, and present opportunities and challenges in the visualization of energy system scenario data.

decision-making↗

NASA NTRS2019

Tactical Scientific Decision-Making during Crewed Astrobiology Mars Missions

The limitations placed upon human explorers on the surface of Mars will necessitate a methodology for scientific exploration that is different from standard approaches to terrestrial fieldwork and prior crewed exploration of the Moon. In particular, the data transmission limitations and communication latency between Earth and Mars create a unique situation for surface crew in contact with a terrestrial science team. The BASALT research program simulated a series of extravehicular activities (EVAs) in Mars analog terrains under various Mars-relevant bandwidth and latency conditions to investigate how best to approach this problem. Here we discuss tactical decision-making under these conditions, that is, how the crew on Mars interacts with a team of scientists and support personnel on Earth to collect samples of maximum scientific interest. We describe the strategies, protocols, and tools tested in BASALT EVAs and give recommendations on how best to conduct human exploration of Mars with support from Earth-based scientists. We find that even with scientists supporting them, the crew performing the exploration must be trained in the appropriate scientific disciplines in order to provide the terrestrial scientists with enough information to make decisions, but that with appropriate planning and structure, and tools such as a ‘‘dynamic leaderboard,’’ terrestrial scientists can add scientific value to an EVA, even under Mars communication latency

Decision-making↗

DOE OSTI2020

Panel Session 132: Risk-Informed Approach for Decision Making in WM, D and D and SNF Management: Reasonable Assurance for Safety

Mr. Larry Camper organized a panel of experts to discuss approaches to better make risk-informed decisions in waste management, decommissioning, and the management of Spent Nuclear Fuel (SNF). The audience heard the perspectives from four panelists that addressed issues ranging from the technical basis used to make risk-informed decisions to for developing cleanup criteria and promulgating regulations and safety standards both domestically and abroad. A summary of each of the presentations given by the panelists is provided herein. This WMS BOD featured panel focused on the Risk-Informed Approach for Decision Making in WM, D and D and SNF Management and the Reasonable Assurance for Safety. The panelists addressed and discussed with the audience different approaches used for decision-making, summarizing ongoing probabilistic vs. deterministic approaches, including IAEA graded approach, and discussed policies/approaches to achieve reasonable assurance for safety rather than using absolute assurance. Panelists with presentations: Risk-Informed Decision Making - More than a Motto? (Paul Black); NRC Staff Perspective on Risk-Informed Approach and Reasonable Safety Assurance in D and D and LLW (Rateb (Boby) Abu Eid); Risk-Informed Decision-Making and Illustrative National Academies Studies (Charles Ferguson); IAEA's Revised Safety Guidance on Remediation (Michelle Roberts); NDA Radioactive Waste Strategy - A Risk Informed Approach (James McKinney)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Variational Information Planning for Sequential Decision Making

We consider the setting of sequential decision making where, at each stage, potential actions are evaluated based on expected reduction in posterior uncertainty, given by mutual information (MI). As MI typically lacks a closed form, we propose an approach which maintains variational approximations of, both, the posterior and MI utility. Our planning objective extends an established variational bound on MI to the setting of sequential planning. The result, variational information planning (VIP), is an efficient method for sequential decision making. We further establish convexity of the variational planning objective and, under conditional exponential family approximations, we show that the optimal MI bound arises from a relaxation of the well-known exponential family moment matching property. Here, we demonstrate VIP for sensor selection, experiment design, and active learning, where it meets or exceeds methods requiring more computation, or those specialized to the task.

Pacheco, Jason↗

NASA NTRS1977

A queueing model of pilot decision making in a multi-task flight management situation

Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.

Walden, R. S.↗

NASA NTRS2024

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗

DOE OSTI2015

A paradigm shift: an introduction to structured decision making for sustainable waste management and remediation - 15649

transport of contaminants and human health risk assessment. Most often these modeling activities are carried out in a conservative fashion, usually beyond even the conservatism that is built into the associated regulations and guidance. Decisions are aimed primarily at compliance with regulatory objectives, rather than optimization. This leads to unnecessarily costly remediation and under-utilization of the nation's relatively few radioactive waste disposal facilities. Risk assessment decisions under CERCLA and RCRA might seem to perform better, but if anything this is because the focus is on shorter-term decision-making because long term fate and transport modeling is not considered necessary in most cases. However, some more complex contamination problems suffer from the same basic issues as radioactive waste disposal in terms of the need for complex fate and transport modeling and subsequent risk assessment. At least CERCLA addresses optimization in the feasibility study, but it does not address how to perform that optimization in the face of uncertainty or stakeholders who have different competing objectives. Other environmental issues that fall outside the realm of DOE Orders, NRC regulations, and regulations such as CERCLA and RCRA, have found a different path towards effective decision-making. This includes land reuse and watershed management decisions, for which there is a focus on sustainability and on stakeholder involvement throughout the decision making process. EPA is using 'structured decision analysis' to achieve the primary goal of maximizing societal welfare. These same tools and approaches can be brought into environmental and waste management decisions that need to be made by DOE. Structured decision analysis provides a formal process for capturing not only the science side of the problem, but also the costs and value judgments of the stakeholders, to reach an optimal solution. But this approach requires a paradigm shift within the DOE and NRC environmental and waste management programs. That is, it requires a willingness to engage a new approach that will provide a path towards effective optimization in the decision-making process for the complex environmental problems faced by DOE and NRC. Because of the current nature of problem solving for these types of problems, which involves many layers of conservatism, this structured decision analysis path towards optimization will also realize substantial cost savings for these programs, while maintaining or improving defensibility and transparency in the decision making process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

A framework for guiding sustainability assessment and on-farm strategic decision making

Responding to future challenges and societal needs, various actions are taken in agriculture to evolve towards more sustainable farming practices. These actions imply strategic choices and suppose adequate sustainability assessments to identify, measure, evaluate and communicate sustainable development. However, literature is scarce on the link between strategic decision making and sustainability assessment. As questions emerge on how, what and when to measure, the objective of this paper is to construct a framework for guiding sustainability assessment and on-farm strategic decision making. Qualitative research on own experiences from the past and a recent project revealed four categories of actual needs farmers, advisors and experts have regarding sustainability assessment: context, flexibility, focus on farm and farmer and communication. These stakeholders' needs are then incorporated into a two-dimensional framework that marries the intrinsic complexity of sustainability assessment tools and the time frame of strategic decision making. The framework allows a farm-specific and flexible approach leading to harmonized actions towards sustainable farming. As this framework is mainly a procedural instrument to guide the use of sustainability assessment tools within strategic decision making, it fits to incorporate, even guide, future research on sustainability assessment tools themselves and on their adoption on farms. - Highlights: • How to link sustainability assessment and on-farm strategic decision making is unclear. • Two-dimensional framework incorporating stakeholders' needs regarding sustainability assessment • Linking complexity of sustainability assessment tools and the time frame of strategic decision making • Farm-specific and flexible approach to harmonize action towards sustainable farming.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Data-driven optimal charging decision making for connected and automated electric vehicles: A personal usage scenario

This study introduces an optimal charging decision making framework for connected and automated electric vehicles under a personal usage scenario. This framework aims to provide charging strategies, i.e. the choice of charging station and the amount of charged energy, by considering constraints from personal daily itineraries and existing charging infrastructure. A data-driven method is introduced to establish a stochastic energy consumption prediction model with consideration of realistic uncertainties. This is performed by analyzing a large scale electric vehicle data set. A real-time updating method is designed to construct this prediction model from new consecutive data points in an adaptive way for real-world applications. Based on this energy cost prediction framework from real electric vehicle data, multistage optimal charging decision making models are introduced, including a deterministic model for average outcome decision making and a robust model for safest charging strategies. A dynamic programming algorithm is proposed to find the optimal charging strategies. Detailed simulations and case studies demonstrate the performance of the proposed algorithms to find optimal charging strategies. They also show the potential capability of connected and automated electric vehicles to reduce the range anxiety and charging infrastructure dependency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Distributionally Robust Decision Making Leveraging Conditional Distributions

Distributionally robust optimization (DRO) is a powerful tool for decision making under uncertainty. It is particularly appealing because of its ability to leverage existing data. However, many practical problems call for decision-making with some auxiliary information, and DRO in the context of conditional distributions is not straightforward. We propose a conditional kernel distributionally robust optimization (CKDRO) method that enables robust decision making under conditional distributions through kernel DRO and the conditional mean operator in the reproducing kernel Hilbert space (RKHS). In particular, we consider problems where there is a correlation between the unknown variable y and an auxiliary observable variable x. Given past data of the two variables and a queried auxiliary variable, CKDRO represents the conditional distribution P(y|x) as the conditional mean operator in the RKHS space and quantifies the ambiguity set in the RKHS as well, which depends on the size of the dataset as well as the query point. To justify the use of RKHS, we demonstrate that the ambiguity set defined in RKHS can be viewed as a ball under a metric that is similar to the Wasserstein metric. The DRO is then dualized and solved via a finite dimensional convex program. The proposed CKDRO approach is applied to a generation scheduling problem and shows that the result of CKDRO is superior to common benchmarks in terms of quality and robustness.

Chen, Yuxiao↗

DOE OSTI2025

First-of-a-Kind Risk-Informed Digital Twin for Operational Decision Making

A digital twin (DT) is a digital model or a collection of models of a physical entity. DTs in the nuclear arena can be used from plant design through decommissioning. Decisions are typically a priori or made offline. Risk-informed decision making is identifying what can go wrong, its frequency, and the consequences of its failure. Ideally risk-informed decision making reflects the current state of the plant and provides a decision in real time. Traditionally, probabilistic risk assessments (PRAs) evaluate the failures of safety systems, the risk of core damage, and the offsite dose as the consequence. However, this DT evaluates the decisions on the control side rather than the protection side. It uses the same risk methods to probabilistically inform the decision-making process but in a different way. Rather than evaluating the risk of core damage, this DT evaluates the likelihood of avoiding a trip set point while maintaining plant safety. Performance-based assessments are identified via its probabilistic evaluation of operational alternatives based on system status. Because the purpose of the control system is to maintain system variables within prescribed operating ranges, upsets or challenges that can exceed a trip set point resulting in a plant transient and a challenge to plant mitigating systems based on actual plant conditions, are evaluated to safely maintain the plant within the operating ranges. The probabilistic portion of the model is autonomously and automatically adjusted, and the metric of interest (i.e. likelihood of avoiding a trip set point) is recalculated. The digital representation of the physical system (i.e. the DT) performs a deterministic performance–based assessment of the probabilistically identified alternatives identified to validate the probabilistic assessment. A decision-making algorithm selects the appropriate option based on the probabilistic and deterministic assessments and transmits a control signal to a component(s) to initiate a corrective action or informs an operator of its decision.

digital twin↗

NASA NTRS1990

Distributed decision-making for space operations

A programmatic and technical perspective in the context of future space applications is presented, that includes some of the management challenges that arise as the decision-making process becomes increasingly more decentralized. Three challenges are discussed: (1) the degree to which the planners must communicate with each other and with those who are seeking space operations resources, (2) the collection, management, employment and dissemination of the information needed to make decisions, and (3) the challenges connected with schedule integration. The technical perspective presented leads to recommended adaptations to the normal scheduling algorithms that retain the 'degrees of freedom' in the planning result. It is shown that these adaptations are specific technical responses to the programmatic challenges discussed.

Hornstein, Rhoda Shaller↗

DOE OSTI2014

Decision making based on optical excitation transfer via near-field interactions between quantum dots

Optical near-field interactions between nanostructured matters, such as quantum dots, result in unidirectional optical excitation transfer when energy dissipation is induced. This results in versatile spatiotemporal dynamics of the optical excitation, which can be controlled by engineering the dissipation processes and exploited to realize intelligent capabilities such as solution searching and decision making. Here, we experimentally demonstrate the ability to solve a decision making problem on the basis of optical excitation transfer via near-field interactions by using colloidal quantum dots of different sizes, formed on a geometry-controlled substrate. We characterize the energy transfer behavior due to multiple control light patterns and experimentally demonstrate the ability to solve the multi-armed bandit problem. Our work makes a decisive step towards the practical design of nanophotonic systems capable of efficient decision making, one of the most important intellectual attributes of the human brain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1979

Monitoring and decision making by people in man machine systems

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Johannsen, G.↗

NASA NTRS1988

Hierarchical neural networks for autonomous data analysis and decision making

A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

Eberlein, Susan↗

NASA NTRS1993

Criteria for assessing problem solving and decision making in complex environments

Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.

Orasanu, Judith↗

DOE OSTI2016

Value of Information in Fuel Cycle Decision-making

Transitions between nuclear fuel cycles with uncertain key parameters (e.g., SNF and HLW disposal costs, fast reactor capital costs) have been examined using a decision-making under uncertainty methodology. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision-tree. The framework of this methodology allows for interpretation using a real options valuation or game theoretic approach, reviewed in. The work presented here extends the decision-making under uncertainty framework to calculate the value of information, which may be used to inform a game against nature. These games against nature have been applied to resource allocation problems, where scarce resources are allocated to maximize expected payoffs. More broadly, the value of developing alternative technologies may be considered under the same framework, where an investment portfolio for technology deployment may be developed. Here, the value of information is taken as the value of reducing uncertainty in key parameters, and these values may be substituted for the traditional payoff matrix when considering allocating scarce resources. Games against nature may provide a unique perspective on R and D funding decisions when considering transitions between nuclear fuel cycles. By determining the value of reducing uncertainties (of gaining information on probability distributions) scarce resources may be allocated in such a way to maximize their utility. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗