Prediction analysis and management decisions.
Prediction analysis techniques /PAT/ using statistical methods, computers, error analysis, etc, for system weight, performance and other parameter predictions in Apollo program
PROGRAM MANAGEMENT↗
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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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Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning
The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.
Otterstatter, Matthew R.↗
Interpretable boosted-decision-tree analysis for the Majorana Demonstrator
The Majorana Demonstrator is a leading experiment searching for neutrinoless double-beta decay with high purity germanium detectors (HPGe). Machine learning provides a new way to maximize the amount of information provided by these detectors, but the data-driven nature makes it less interpretable compared to traditional analysis. An interpretability study reveals the machine's decision-making logic, allowing us to learn from the machine to feedback to the traditional analysis. In this work, we have presented the first machine learning analysis of the data from the Majorana Demonstrator; this is also the first interpretable machine learning analysis of any germanium detector experiment. Two gradient boosted decision tree models are trained to learn from the data, and a game-theory-based model interpretability study is conducted to understand the origin of the classification power. By learning from data, this analysis recognizes the correlations among reconstruction parameters to further enhance the background rejection performance. By learning from the machine, this analysis reveals the importance of new background categories to reciprocally benefit the standard Majorana analysis. This model is highly compatible with next-generation germanium detector experiments like LEGEND since it can be simultaneously trained on a large number of detectors.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Architecting Space Exploration Campaigns: A Decision-Analytic Approach
This paper shows the benefits of Decision Analysis techniques for campaign design and evaluation. Important concepts of decision analysis are reviewed through the lens of designing a campaign to find exploitable equatorial water on Mars. The method developed herein is general to any search campaign. The paper concludes with a discussion of the challenges and opportunities in applying similar techniques to other types of campaigns.
campaigns↗
Data, Analysis, and Decision Tools for Evaluating the Circular Economy of Plastics
Presentation of analysis tools and methods for evaluating the circular economy of plastics.
analysis tools↗
The Aeronautical Data Link: Decision Framework for Architecture Analysis
A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.
Morris, A. Terry↗
A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production
A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Next Generation System Analysis Model Recently Added Features and Future Plans - Abstract
The Nuclear Waste Policy Act of 1982, as amended (NWPA 1982), established the federal government’s responsibility to accept spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from waste owners and generators for ultimate disposition. SNF generated by the current fleet of commercial nuclear reactors is being stored at the reactor sites in spent fuel pools (SFPs) and in dry independent spent fuel storage installations (ISFSIs). The US Department of Energy Office of Nuclear Energy (DOE-NE) is developing an Integrated Waste Management Program (IWMP) comprising a suite of options and supporting analyses to enable future informed choices. The IWMP is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWM system are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWM system. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. Recent major enhancements that have been implemented into NGSAM since NGSAM was last presented at the WM2019 conference include: • Tracking of railroad escort and buffer car acquisition. • Addition of heavy haul and barge routes for some sites, as well as support for user-defined inter-modal routes. • Updates to the logic that checks the thermal maps prior to package transport. • Addition of an allocation method that predicts when reactor sites will pack assemblies from their pools for dry storage and allocates packages to those reactor sites in the preceding periods, favoring direct transport packages and reducing the number of packages that reactor sites pack for dry storage at their ISFSIs. • Addition of reactor site family operational limits, which are used to limit the number of loads from the pool and from dry storage at a given reactor site per year. • Support has been added for multiple canister loading maps and packages having multiple compatible transportation overpacks. • Updates in the handling of non-commercial fuel, including a new database containing data to support the updates. • Support for repackaging at reactor sites. • Implementing additional output reports or modifying existing reports. • User edits can now be created and edited via the NGSAM website. • Ability to load packages for dry storage at ISF pools. • Same-type package blending at DOE sites. • Support for multi-mode transloading at reactor sites. These new features have improved NGSAM capabilities and/or improve the user experience with the model and will be discussed in more detail. The initial NGSAM requirements for advanced reactor fuels, reprocessing, treatment, and conditioning are preliminary and are described at a high level in this paper: analysts will provide more specific requirements to the NGSAM team in the future. Additionally, there are many data needs associated with modeling advanced reactors in NGSAM, but many of the data or plans are still in progress and/or yet to be fully defined. However, this document describes an initial exploration of the data relevant to this program. Advanced reactor data will likely require revision as concepts evolve and new considerations are made. This is a technical paper that does not take into account contractual limitations or obligations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). For example, under the provisions of the Standard Contract, spent nuclear fuel in multi-assembly canisters is not an acceptable waste form, absent a mutually agreed to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract governs the obligations of the parties, and this paper in no manner supersedes, overrides, or amends the Standard Contract. This paper reflects technical work which could support future decision making by DOE. No inferences should be drawn from this paper regarding future actions by DOE, which are limited both by the terms of the Standard Contract and Congressional appropriations for the Department to fulfill its obligations under the Nuclear Waste Policy Act including licensing and construction of a spent nuclear fuel repository.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Transmission Bearing Damage Detection Using Decision Fusion Analysis
A diagnostic tool was developed for detecting fatigue damage to rolling element bearings in an OH-58 main rotor transmission. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting bearing surface fatigue pitting damage. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from tests performed in the NASA Glenn 500 hp Helicopter Transmission Test Stand. Data was collected during experiments performed in this test rig when two unanticipated bearing failures occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears duplex ball bearings and spiral bevel pinion triplex ball bearings in a main rotor transmission.
Dempsey, Paula J.↗
Spiral Bevel Gear Damage Detection Using Decision Fusion Analysis
A diagnostic tool for detecting damage to spiral bevel gears was developed. Two different monitoring technologies, oil debris analysis and vibration, were integrated using data fusion into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual monitoring technologies. This diagnostic tool was evaluated by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Rigs. Data was collected during experiments performed in this test rig when pitting damage occurred. Results show that combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spiral bevel gears.
Dempsey, Paula J.↗
Development of Fuzzy Logic and Soft Computing Methodologies
Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be, driven by a quest to progress from perceptions to measurements. Pursuit of this aim has led to brilliant successes. But alongside the successes stand problems whose solutions are not in sight. Representative of such problems is the problem of automation of driving in city traffic. In this case, as in many others, what can be done with ease by humans - without any measurements and a computations - is an intractable task for machines.
Zadeh, L. A.↗
Choosing the Best Modeling Platform for Radiological Risk Assessment Models - 20468
Radiological risk assessments, in the form of performance or safety assessments, are often required under regulations or guidance for remediation of contaminated land, decommissioning of contaminated buildings or structures, and radioactive waste disposal. These risk assessments are usually supported by fate and transport models that address decay and ingrowth of radionuclides, as well as their movement through engineered systems and the natural environment. These models are often projected thousands, or more, years into the future, largely because the radioactive species change through decay and ingrowth, and hence the magnitude of the radioactive effect changes with time. There are many computer codes that are available to address this type of modeling. They range from addressing specific pathways or processes such as infiltration of water, groundwater, surface water, air, biota, diffusion and advection of water and gases, to those that try to couple all processes together to evaluate the impact of fate and transport through the entire system to places in space and time to which access is assumed. These different types of codes are sometimes separated with the monikers process-level and systems-level codes, although it is often not clear that this separation does justice to the capabilities of the many codes that are available to evaluate fate and transport of radionuclides. The focus of this paper is the latter group of modeling codes. Several systems level modeling codes exist and are used. There are differences between these codes in terms of utility, flexibility, complexity and cost. The purpose of this paper is to compare a few of these codes in the context of work currently being performed by the International Atomic Energy Agency (IAEA) Modeling and Data for Radiological Impact Assessments (MODARIA) II Working Group 1 (WG1). The MODARIA II WG1's main focus is how stakeholder engaged decision analysis can, or should, be applied to radiological contamination problems so that better, longstanding, sustainable, solutions are reached. However, the WG1 also recognizes the potential impact of the modeling tools that are chosen to address radiological risk, which is often a primary objective of decision making for radiological problems. Other objectives might also be important, such as constraining costs, obtaining financing, minimizing impact on ecosystems, saving cultural resources, saving jobs, farmland, environmental justice, etc., in a full decision analysis for a given radiological contamination problem, but none of these other objectives have the same types of complex modeling needs as minimize radiological dose. Consequently, a further focus of WG1 is to evaluate the potential impacts on decision making of the choice of fate and transport, and risk assessment, modeling codes that are used to support decision making. The WG1 will produce a report at the end of 2020 that will focus on an approach to effective decision making and stakeholder engagement. The report will also consider the role that performance assessment modeling should play in the decision-making process, including the impact of the choice of modeling tools or computer codes on risk-informed decision making. Several sites around the World have been made available by Member States for these model comparisons, and several modeling tools have been considered. However, the focus of this paper is on two of the sites, one in Belgium and one in Ukraine, and on three of the tools: NORMALYSA (NORM And Legacy Site Assessment); GoldSim{sup C}, and AMBER{sup C}. The final report from this working group will also cover other modeling tools, including RESRAD, and PC-Cream{sup R}. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Systems Maintenance Automated Repair Tasks (SMART)
SMART is a uniform automated discrepancy analysis and repair-authoring platform that improves technical accuracy and timely delivery of repair procedures for a given discrepancy (see figure a). SMART will minimize data errors, create uniform repair processes, and enhance the existing knowledge base of engineering repair processes. This innovation is the first tool developed that links the hardware specification requirements with the actual repair methods, sequences, and required equipment. SMART is flexibly designed to be useable by multiple engineering groups requiring decision analysis, and by any work authorization and disposition platform (see figure b). The organizational logic creates the link between specification requirements of the hardware, and specific procedures required to repair discrepancies. The first segment in the SMART process uses a decision analysis tree to define all the permutations between component/ subcomponent/discrepancy/repair on the hardware. The second segment uses a repair matrix to define what the steps and sequences are for any repair defined in the decision tree. This segment also allows for the selection of specific steps from multivariable steps. SMART will also be able to interface with outside databases and to store information from them to be inserted into the repair-procedure document. Some of the steps will be identified as optional, and would only be used based on the location and the current configuration of the hardware. The output from this analysis would be sent to a work authoring system in the form of a predefined sequence of steps containing required actions, tools, parts, materials, certifications, and specific requirements controlling quality, functional requirements, and limitations.
Schuh, Joseph↗
Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool
This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.
Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
Spiral-Bevel-Gear Damage Detected Using Decision Fusion Analysis
Helicopter transmission integrity is critical to helicopter safety because helicopters depend on the power train for propulsion, lift, and flight maneuvering. To detect impending transmission failures, the ideal diagnostic tools used in the health-monitoring system would provide real-time health monitoring of the transmission, demonstrate a high level of reliable detection to minimize false alarms, and provide end users with clear information on the health of the system without requiring them to interpret large amounts of sensor data. A diagnostic tool for detecting damage to spiral bevel gears was developed. (Spiral bevel gears are used in helicopter transmissions to transfer power between nonparallel intersecting shafts.) Data fusion was used to integrate two different monitoring technologies, oil debris analysis and vibration, into a health-monitoring system for detecting surface fatigue pitting damage on the gears.
Dempsey, Paula J.↗
Risk-based analysis and decision making in multi-disciplinary environments
Explore the source record for details and available documents.
risk technology decision-making↗
Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis
A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.
Dempsey, Paula J.↗
Risk-based analysis and decision making in multi-disciplinary environments
A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.
technology↗