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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cyber100 Compass: Quantification of Cybersecurity Risks for Systems Transitioning to High Levels of Renewables (Final Report)

The shift to high levels of renewable deployment will entail a significant re-engineering of the grid. As investors, utilities, customers, and others prepare for clean energy transitions, there is need to understand how restructuring the grid to accommodate renewables will change the attack surface of the grid and accompanying cyber risk. However, today the cyber-physical risks associated with electric grids incorporating high levels of renewable deployment remain largely unknown. The Cyber100 Compass proof-of-concept application attempts to quantify future cyber-physical security risks by combining risk data gathered from subject matter experts (SMEs) with input from system planners about conditions they expect to be true about their electric systems in the future. Users provide data about their organization’s tolerance for risk; the value they place on avoiding the consequences of different cyber events; and conditions that they expect to be true on their systems at some point in the future. The SMEs provide baseline probabilities for different cyber events; the probability that an event will be low-, moderate-, or high-impact; and the amount by which user-identified conditions on their systems will change the likelihood of the cyber events. The application takes both the user and SME input and performs a series of Monte Carlo simulations to arrive at a quantification of risk.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Evaluating Faulty State Occurrence in Wildfire UAS Missions Using Markov Chains

As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.

risk analysis↗
NASA NTRSDate not supplied

Evaluating Faulty State Occurrence in Wildfire UAS Missions Using Markov Chains

As autonomous technology advances, unmanned aircraft systems are increasingly integrated into emergency response missions, such as wildfire response. These systems must be be safe with less risk than non-autonomous counter parts, yet quantifying the risk associated with present-day and future systems conventionally relies solely on expert opinion and little data. Instead, combining narrative mishap reports with probabilistic analysis can provide a method for evolutionary and timely risk analysis. In this paper, we present a framework for a data-driven probabilistic risk assessment style analysis, where hazard events and rates originate from documented UAS mishaps. The framework is applied to a UAS mapping mission in wildfire response, including a fault tree analysis, event tree analysis, and probabilistic analysis using Markov Chains. The analysis provides an enumeration of hazards in the system, hazard events that can lead to faults, the probability of a mission experiencing any fault, the probability of experiencing a specific fault, and the expected time spent until faulty states occur in present-day operations.

risk analysis↗
NASA NTRS2012

Impact of Satellite Atmospheric Motion Vectors In the GMAO GEOS-5 Global Data Assimilation System

The WMO and THORPEX co-sponsored fifth Workshop on the Impact of Various Observing Systems on Numerical Weather Prediction will be organized by the Expert Team on the Evolution of the Global Observing System in Sedona, Arizona, United States, from 22 to 25 May 2012. Participants are expected to come from all the major NWP centres which are active in the area of impact studies. The workshop will be conducted in English. As for the first four workshops it is planned to produce a workshop report to be published as a WMO Technical Report that will include the papers submitted by the participants. The previous four workshops in this series took place in Geneva {April 1997), Toulouse (March 2000), Alpbach (March 2004) and Geneva (May 2008). Results from Observing System Experiments (OSEs), both with global and regional aspects were presented and conclusions were drawn concerning the contributions of the various components of the observing system to the large scale forecast skill at short and medium range (Workshop Proceedings were published as WMO World Weather Watch Technical Reports TD No. 868, 1034, 1228 and 1450). Since then, some significant changes and developments have affected the global observing system and more efforts have been devoted to meso-scale observing and assimilation systems. There has also been a trend toward using techniques other than OSEs to document data impact, such as adjoint-based sensitivity to observations or ensemble-based sensitivity. Field experiments have been carried out, in particular through the THORPEX project, and the use of targeted data has been assessed.

Gelaro, Ronald↗
NASA NTRS2006

NASA Exploration Launch Projects Overview: The Crew Launch Vehicle and the Cargo Launch Vehicle Systems

The U.S. Vision for Space Exploration (January 2004) serves as the foundation for the National Aeronautics and Space Administration's (NASA) strategic goals and objectives. As the NASA Administrator outlined during his confirmation hearing in April 2005, these include: 1) Flying the Space Shuttle as safely as possible until its retirement, not later than 2010. 2) Bringing a new Crew Exploration Vehicle (CEV) into service as soon as possible after Shuttle retirement. 3) Developing a balanced overall program of science, exploration, and aeronautics at NASA, consistent with the redirection of the human space flight program to focus on exploration. 4) Completing the International Space Station (ISS) in a manner consistent with international partner commitments and the needs of human exploration. 5) Encouraging the pursuit of appropriate partnerships with the emerging commercial space sector. 6) Establishing a lunar return program having the maximum possible utility for later missions to Mars and other destinations. In spring 2005, the Agency commissioned a team of aerospace subject matter experts to perform the Exploration Systems Architecture Study (ESAS). The ESAS team performed in-depth evaluations of a number of space transportation architectures and provided recommendations based on their findings? The ESAS analysis focused on a human-rated Crew Launch Vehicle (CLV) for astronaut transport and a heavy lift Cargo Launch Vehicle (CaLV) to carry equipment, materials, and supplies for lunar missions and, later, the first human journeys to Mars. After several months of intense study utilizing safety and reliability, technical performance, budget, and schedule figures of merit in relation to design reference missions, the ESAS design options were unveiled in summer 2005. As part of NASA's systems engineering approach, these point of departure architectures have been refined through trade studies during the ongoing design phase leading to the development phase that begins in 2008. Comprehensive reviews of engineering data and business assessments by both internal and independent reviewers serve as decision gates to ensure that systems can fully meet customer and stakeholder requirements. This paper provides the current CLV and CaLV configuration designs and gives examples of the progress being made during the first year of this significant effort. Safe, reliable, cost-effective space transportation systems are a foundational piece of America s future in space and the next step in realizing the plan for revitalizing lunar capabilities on the passageway to the human exploration of Mars. While building on legacy knowledge and heritage hardware for risk reduction, NASA will apply lessons learned from developing these new launch vehicles to the growth path for future missions. The elements for mission success and continued U.S. leadership in space have been assembled over the past year. As NASA designs and develops these two new systems over the next dozen years, visible progress, such as that reported in this paper, may sustain the national will to stay the course across political administrations and weather the inevitable trials that will be experienced during this challenging endeavor.

Snoddy, Jimmy R.↗
DOE OSTI2024

Protection of 100% Inverter-dominated Power Systems with Grid-Forming Inverters and Protection Relays – Gap Analysis and Expert Interviews

This report summarizes a gap analysis resulting from a literature review and expert interviews conducted by subject matter experts from Sandia National Laboratory, Siemens, and the Electric Power Research Institute (EPRI) in Spring 2023. The gap analysis consists of two main parts: The fault-ride through (FRT) behavior of grid-forming (GFM) inverter-based resources (IBR) and the response of state-of-the-art protection relays to the fault currents and voltages from GFM IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles

Conventional physics-based modeling is a time-consuming bottleneck in control design for complex nonlinear systems like autonomous underwater vehicles (AUVs). In contrast, purely data-driven models, require a large number of observations and lack operational guarantees for safety-critical systems. Data-driven models leveraging available partially characterized dynamics have potential to provide reliable systems models in a typical data-limited scenario for high value complex systems, thereby avoiding months of expensive expert modeling time. In this work we explore this middle-ground between expert-modeled and pure data-driven modeling. We present control-oriented parametric models with varying levels of domain-awareness that exploit known system structure and prior physics knowledge to create constrained deep neural dynamical system models. We employ universal differential equations to construct data-driven blackbox and graybox representations of the AUV dynamics. In addition, we explore a hybrid formulation that explicitly models the residual error related to imperfect graybox models. We compare the prediction performance of the learned models for different distributions of initial conditions and control inputs to assess their suitability for control.

Shaw Cortez, Wenceslao E.↗
DOE OSTI2023

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1988

Electronic data generation and display system

The Electronic Data Generation and Display System (EDGADS) is a field tested paperless technical manual system. The authoring provides subject matter experts the option of developing procedureware from digital or hardcopy inputs of technical information from text, graphics, pictures, and recorded media (video, audio, etc.). The display system provides multi-window presentations of graphics, pictures, animations, and action sequences with text and audio overlays on high resolution color CRT and monochrome portable displays. The database management system allows direct access via hierarchical menus, keyword name, ID number, voice command or touch of a screen pictoral of the item (ICON). It contains operations and maintenance technical information at three levels of intelligence for a total system.

Wetekamm, Jules↗
NASA NTRS2011

Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing

Systems analysis of a planetary entry (SAPE), descent, and landing (EDL) is a multidisciplinary activity in nature. SAPE improves the performance of the systems analysis team by automating and streamlining the process, and this improvement can reduce the errors that stem from manual data transfer among discipline experts. SAPE is a multidisciplinary tool for systems analysis of planetary EDL for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. It performs EDL systems analysis for any planet, operates cross-platform (i.e., Windows, Mac, and Linux operating systems), uses existing software components and open-source software to avoid software licensing issues, performs low-fidelity systems analysis in one hour on a computer that is comparable to an average laptop, and keeps discipline experts in the analysis loop. SAPE uses Python, a platform-independent, open-source language, for integration and for the user interface. Development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE currently includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and interface for structural sizing.

Samareh, Jamshid A.↗
NASA NTRS2013

Exploring Mission Concepts with the JPL Innovation Foundry A-Team

The JPL Innovation Foundry has established a new approach for exploring, developing, and evaluating early concepts called the A-Team. The A-Team combines innovative collaborative methods with subject matter expertise and analysis tools to help mature mission concepts. Science, implementation, and programmatic elements are all considered during an A-Team study. Methods are grouped by Concept Maturity Level (CML), from 1 through 3, including idea generation and capture (CML 1), initial feasibility assessment (CML 2), and trade space exploration (CML 3). Methods used for each CML are presented, and the key team roles are described from two points of view: innovative methods and technical expertise. A-Team roles for providing innovative methods include the facilitator, study lead, and assistant study lead. A-Team roles for providing technical expertise include the architect, lead systems engineer, and integration engineer. In addition to these key roles, each A-Team study is uniquely staffed to match the study topic and scope including subject matter experts, scientists, technologists, flight and instrument systems engineers, and program managers as needed. Advanced analysis and collaborative engineering tools (e.g. cost, science traceability, mission design, knowledge capture, study and analysis support infrastructure) are also under development for use in A-Team studies and will be discussed briefly. The A-Team facilities provide a constructive environment for innovative ideas from all aspects of mission formulation to eliminate isolated studies and come together early in the development cycle when they can provide the biggest impact. This paper provides an overview of the A-Team, its study processes, roles, methods, tools and facilities.

Team Eureka↗
NASA NTRSDate not supplied

Task Load Management in Earth Independent Medical Operations

BACKGROUND: Medical care in spaceflight carries a high task load and can easily overwhelm a small crew. Present day operations in low Earth orbit (LEO) offload most medical tasks to ground teams in mission control. This team includes dozens of flight surgeons, specialists, and engineers and supports the on-orbit crew in monitoring environmental systems, tracking medications, guiding procedures, providing expert advice, and many other tasks. However, the physical limitations of the speed of light and technical limitations of bandwidth, channel capacity, and signal processing mean that missions beyond LEO cannot rely on this level of telemedical support. The further we travel from Earth the more these tasks will fall on the shoulders of the crew and the greater the risk of task saturation to the wellbeing of the crew and the success of the mission. Exploration class space crews will need progressively more robust systems for managing task load as they progress further out in space. OVERVIEW: Medical task management systems will need to assist with two broad categories of tasks; cognitively intensive tasks and procedure execution tasks. In both cases the goal is for the systems to operate in the background with minimal human-in-the-loop intervention. To accomplish this such systems will need to be designed with careful consideration for human factors and human systems integration to maximize efficiency, minimize alarm fatigue, and avoid inadvertently increasing task loads. Finally, the key domains of space medicine tasking can be used to map present day and near future technologies to the areas where they are best suited to support and identify gaps which can be targeted for research and development. DISCUSSION: Task load is a major challenge for Earth Independent Medical Operations to overcome. It will require careful coordination between experts in a variety of fields paying attention to human factors and human systems integration as well as technical and medical expertise. If done well medical task management systems can handle many of the tasks currently run by humans in mission control and enable human crews to maintain terrestrial standards of care in the extraterrestrial environment.

Dana Levin↗
DOE OSTI2025

Root cause analysis of a molten salt pump in FLUSTFA

The primary salt pump installed in the high-temperature FLUoride Salt Test Facility (FLUSTFA) was successfully operated for some time, but later ceased operation. To understand what occurred, a Root Cause Analysis (RCA) was performed. Steps taken to try to get the pump operational include adjusting the shaft position, increasing the heating power of the tape heaters on the pump volute, and manually rotating the pump shaft. While removing the insulation, corrosion was noted on the outside of the pump volute, and decolorization of the insulation and tape heaters was observed. Significant corrosion products were also observed in the pump itself and the piping connected to the pump. The nitrogen cover gas was maintained from before salt was introduced into the loop until the pump was dismounted and continues to be maintained even after the pump was removed. After considering probable scenarios, causes were assigned and corrective actions were developed to prevent those causes. Then, the RCA was presented to an advisory committee for review, the “Review Committee,” consisting of experts in large molten salt systems: Brandon Haugh, David Holcomb, Kevin Robb, and Vicente Rojas. As a result, the advisory committee provided comprehensive feedback, which have been incorporated into a revised RCA. Findings have then been summarized and reported in this publication.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks

Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (NoNs). Population growth has enhanced transportation demand while urbanization and climate change have intensified urban floods. However, despite the clear need to develop actionable insights for improving the resilience of critical urban lifelines, the theory and methods remain underdeveloped. Furthermore, as infrastructure systems become more intelligent, security experts point to the growing threat of targeted cyber-physical attacks during natural hazards. Here we develop a hypothesis-driven resilience framework for urban transport NoNs, which we demonstrate on the London Rail Network (LRN). We find that topological attributes designed for maximizing efficiency rather than robustness render the network more vulnerable to compound natural-targeted disruptions including cascading failures. Our results suggest that an organizing principle for post-disruption recovery may be developed with network science principles. Our findings and frameworks can generalize to urban lifelines and more generally to real-world spatial networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data-driven Optimal Control Strategy for Virtual Synchronous Generator via Deep Reinforcement Learning Approach

This paper aims at developing a data-driven optimal control strategy for virtual synchronous generator (VSG) in the scenario where no expert knowledge or requirement for system model is available. Firstly, the optimal and adaptive control problem for VSG is transformed into a reinforcement learning task. Specifically, the control variables, i.e., virtual inertia and damping factor, are defined as the actions. Meanwhile, the active power output, angular frequency and its derivative are considered as the observations. Moreover, the reward mechanism is designed based on three preset characteristic functions to quantify the control targets: (1) maintaining the deviation of angular frequency within special limits; (2) preserving well-damped oscillations for both the angular frequency and active power output; (3) obtaining slow frequency drop in the transient process. Next, to maximize the cumulative rewards, a decentralized deep policy gradient algorithm, which features model-free and faster convergence, is developed and employed to find the optimal control policy. With this effort, a data-driven adaptive VSG controller can be obtained. By using the proposed controller, the inverter-based distributed generator can adaptively adjust its control variables based on current observations to fulfill the expected targets in model-free fashion. Finally, simulation results validate the feasibility and effectiveness of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗