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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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At least 883 records · Page 49

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NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗

NASA NTRS2018

Mobile Device Application for Monitoring Cyanobacteria Harmful Algal Blooms Using Sentinel-3 Satellite Ocean and Land Colour Instruments

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Harmful Algal Bloom↗

NASA NTRSDate not supplied

Reflectivity Control Device (RCD) Roll Momentum Management for Solar Cruiser and Beyond

Reflectivity control devices (RCDs), thin film optical devices that are actuated (by application of a voltage across the device) to control the reflection of sunlight on their surfaces, can effectively enable roll momentum management (MM) of a solar sail operating in deep space, outside any magnetic field. This enables solar sails to maintain adequate attitude control in these challenging environments without sacrificing mission life by using expendables. They were planned and developed for use on Solar Cruiser, operating sunward of the Sun-Earth Lagrange Point 1 (sub-L1) in a propulsion-intensive artificial halo orbit. Located in pairs of panels near the distal end of each of four booms, each articulated at a slight angle out of the sail plane to produce a force tangent to the sail at a large moment arm, the RCDs provide roll torque capabilities by using simple switching logic to determine which panels should be activated (voltage applied) to produce torque in the desired direction. The performance capabilities and constraints of these devices across a range of operating conditions, namely sun-relative attitude, is well characterized, granting designers insight on how to properly size the system and optimize the system and component designs to maximize roll torque per unit area. With an informed design, RCDs can be very effective actuators for managing roll momentum with minimal detrimental system impacts (mass, power, complexity, etc.) on Solar Cruiser and other future deep space solar sail missions.

Andrew F Heaton↗

NASA NTRS2024

Looking to the Future: A Call to Action for Advanced GNC Algorithm Verification and Validation

Future space systems will rely on autonomous Guidance, Navigation, and Control (GNC) functions to efficiently manage safe and precise self-directed operations in uncertain complex environments. Fundamentally, the GNC system plays a key role in mission performance and safety because it computes the ideal trajectory (Guidance), determines the actual trajectory (Navigation), and executes the ideal trajectory (Control) of a vehicle’s position and attitude. Our current GNC systems are highly automated and already have a high degree of complexity. As missions become more ambitious, GNC systems for launch vehicles and space platforms (e.g., spacecraft, probes, and landers) will require higher levels of performance and autonomous operation than previously encountered, for example, this includes GNC for optimizing aerodynamic and/or propulsion performance during planetary entry. This GNC Verification and Validation (V&V) paper highlights concerns with what undoubtedly will be a trend towards increased complexity as fully autonomous GNC systems are developed for future space missions. Clearly, complex GNC systems pose challenges in the prelaunch V&V phase, which is a relatively expensive part of a mission’s life cycle. Essentially the V&V phase is focused on checking that the system effectively meets all the design and operational requirements for the mission. The authors of this paper (i.e., the Inter-Agency Working Group of GNC subject matter experts) focused on this fundamental question over the past few years: Will the GNC engineering community of practice be sufficiently prepared to perform the necessary V&V on evolving GNC architectures that are driven by very demanding requirements for autonomy, resiliency, reconfigurability, adaptability, and mission cost-benefit balance? It is the viewpoint of our Inter-Agency team that the GNC V&V approaches and processes needed to address the next generation of complex GNC systems, which likely will employ various forms of modern GNC technology, are not currently established to the level the community will need in the future. While researchers and practitioners have made some progress in developing new GNC V&V methods for modern GNC systems, a good deal of work remains to be done to codify such methods in a comprehensive and systematic manner. Thus, the Inter-Agency team’s partner organizations [the National Aeronautics and Space Administration (NASA), the European Space Agency (ESA), the National Centre for Space Studies (CNES), the German Aerospace Center (DLR), the French Aerospace Lab (ONERA), and ISAE-SUPAERO] have conducted preliminary investigations into advancing GNC V&V techniques, which resulted in the identification of the need for education, new V&V tools, and benchmark problems for the GNC community. The necessary proactive steps to be taken to meet the challenges and fill the gaps in GNC V&V are summarized in this paper. The first steps include identifying advanced analysis tools, developing a GNC V&V roadmap, and expanding education and training programs for GNC practitioners. This paper is a call to action and proposes a comprehensive set of recommended actions for all our stakeholders: space agencies, researchers, and industry.

Samir Bennani↗

NASA NTRSDate not supplied

An in-Time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.

IASMS↗

NASA NTRSDate not supplied

An In-time Aviation Safety Management System Concept of Operations and Modernization of the National Airspace System

Airspace↗

DOE OSTI2022

Flexible Financial Credit Agreements: Blockchain

Flexible Financial Credit Agreements is a broad term used to describe a suite of solar products with innovative features not currently offered in traditional solar financing programs. This brief focuses on blockchain, which is a highly secure, decentralized cryptographic technology that verifies transactional data and stores it on all participating computers in an immutable ledger. Blockchain is best known for its first application in the creation of Bitcoin cryptocurrency, but its principles offer a basis for innovation in a variety of industries where the complexity of transactional data is better suited for secure, decentralized management.

blockchain↗

DOE OSTI2023

Enabling Interconnected Science Workflows through an Adapter Approach

The INTERSECT Software framework project aims to create an open federated library that connects, coordinates, and controls systems in the scientific domain. It features the Adapter, a flexible and extensible interface inspired by the Adapter design pattern in object-oriented programming. By utilizing Adapters, the INTERSECT SDK enables effective communication and coordination within a diverse ecosystem of systems. This adaptability facilitates the execution of complex operations within the framework, promoting collaboration and efficient workflow management in scientific research. Additionally, the generalizability of Adapters and their patterns enhances their utility in other scientific software projects and challenges.

McGaha, Jesse↗

NASA NTRS2010

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗

NASA NTRS1995

Software Transition Project Retrospectives and the Application of SEL Effort Estimation Model and Boehm's COCOMO to Complex Software Transition Projects

The Multimission Image Processing Subsystem (MIPS) at the Jet Propulsion Laboratory (JPL) has managed transitions of application software sets from one operating system and hardware platform to multiple operating systems and hardware platforms. As a part of these transitions, cost estimates were generated from the personal experience of in-house developers and managers to calculate the total effort required for such projects. Productivity measures have been collected for two such transitions, one very large and the other relatively small in terms of source lines of code. These estimates used a cost estimation model similar to the Software Engineering Laboratory (SEL) Effort Estimation Model. Experience in transitioning software within JPL MIPS have uncovered a high incidence of interface complexity. Interfaces, both internal and external to individual software applications, have contributed to software transition project complexity, and thus to scheduling difficulties and larger than anticipated design work on software to be ported.

SEL Boehm COCOMO↗

NASA NTRS2003

Developing Visualization Techniques for Semantics-based Information Networks

Information systems incorporating complex network structured information spaces with a semantic underpinning - such as hypermedia networks, semantic networks, topic maps, and concept maps - are being deployed to solve some of NASA s critical information management problems. This paper describes some of the human interaction and navigation problems associated with complex semantic information spaces and describes a set of new visual interface approaches to address these problems. A key strategy is to leverage semantic knowledge represented within these information spaces to construct abstractions and views that will be meaningful to the human user. Human-computer interaction methodologies will guide the development and evaluation of these approaches, which will benefit deployed NASA systems and also apply to information systems based on the emerging Semantic Web.

Keller, Richard M.↗

DOE OSTI2020

Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins

In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

A data analysis method to rapidly characterize gallium concentration in plutonium matrices using LIBS

The processing of actinide samples is a complex and costly endeavor that requires compositional analysis at various stages. Laser-induced breakdown spectroscopy (LIBS) has been used to analyze actinide-containing samples in many nuclear applications including waste management, fuel processing and forensics. The LIBS spectrum obtained from actinide materials are generally extremely complex, exhibiting many thousands of strong emission lines. This makes it difficult to identify other elements within the sample of interest, given the rich and dominant actinide spectrum. Here, in this article, we describe a recent effort to identify and quantify impurities and alloying constituents in plutonium matrices using a hand-held LIBS instrument that is used to rapidly and efficiently measure an emission spectrum from a material sample. We tabulate the emission line positions and intensities of plutonium. We report the development of machine-learning software that can identify gallium and quantify its concentration in plutonium matrices. This work has the potential to provide a rapid and nearly non-destructive technique that allows more confidence in characterizing the composition of materials that are present within complex actinide associated targets. We describe how our LIBS measurements and data analysis methods have successfully quantified the gallium concentration in a variety of samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Examining the Changing Roles and Responsibilities of Humans in Envisioned Future In-Time Aviation Safety Management Systems

Advances in technology are enabling new concepts of operations that will trans-form aviation including increasingly autonomous capabilities to handle evolving complex dynamic ecosystems like those associated with Advanced Aerial Mobility. A major challenge is how to ensure today’s safety levels are maintained as the system scales for rapid detection and timely mitigation of safety issues. NASA has developed a concept of operation for In-Time Aviation Safety Management Systems (IASMS) that represents a system-of-system perspective on interconnected capabilities needed to proactively reduce risk in complex operational environments where unknown hazards may exist. As a result, NASA research priorities include under-standing how the balance between humans and automation changes in such envisioned systems, which may lead to novel human-machine interaction paradigms and human-autonomy teaming for informed contingency management.

Lawrence Prinzel↗

DOE OSTI2021

Winning Asset Management Improvement Team: Maintenance Planning and Scheduling in a Highly Regulated Environment

The Y-12 National Complex (Y-12) site has numerous aging facilities that are crucial to the Department of Energy and the national security strategy for the nation. Y-12’s commitment to safety and regulatory compliance is of the highest importance. The commitment to meet the national security mission also creates additional rigor and complexity to the everyday maintenance and planning process. Y-12 is a collection of many facilities, both old and new, nestled between two ridges in Oak Ridge, TN. Y-12 was made with the short-term focus of ending “The Great War” through the creation of the worlds’ first atomic bomb. Almost eighty (80) years have passed since the groundbreaking, with the mission of the site changing from decade to decade. While the mission has changed, the way Y-12 employees continuously meet the challenge has not. The site was created to react and overcome; Y-12 still takes pride in the ability to react and overcome. The difference is the site is no longer ignorant to the need for a better way to manage the aging facilities and infrastructure. Shear willpower and determination was once the way to reach the objectives, but as a wise man once said, “Work smarter, not harder.” The business case for change started within the senior leadership at Y-12. A team of managers sat down and dictated objectives to provide a clear scope for the maintenance planning and scheduling optimization team, to include our Eruditio integrated blended learning coaches. In addition to providing the direction, they also made themselves available for escalation of issues in the event the team ran in to road blocks.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Renewable energy and biological conservation in a changing world

Without a shift to renewable energy sources, climate change will have adverse effects on many terrestrial and aquatic species. On the other hand, replacing fossil fuels with renewable energy will have different effects on wildlife, some negative. To protect biota, while navigating the complexities surrounding the transition to renewable energy, will require sharing knowledge between energy experts and wildlife experts, as well as policy makers and resource managers. This special issue is intended to advance the conversation. Interactions between renewable energy facilities and fauna are complex. Each source of renewable energy has its own conservation concerns, and each presents its own set of opportunities for mitigation; Other concerns and mitigations are shared. In this overview, we review climate risks to biota, clarify the complementarities among renewables for the conservation community, and summarize research on energy effects on biota for the energy community. The papers invited for this special issue address fossil (coal, oil, natural gas) and renewable energy (terrestrial biomass energy, hydropower, marine-hydrokinetic energy, wind energy, solar energy) and affected fauna. Finally, we hope that the results of these studies, and others like them, set us on a path toward low-carbon energy systems that provide society with energy while protecting future biodiversity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

AI-Science for Performance Optimization and Diagnosis of Science Instrument Federations

Next generation of science workflows are expected to be executed over complex federations composed of supercomputers, science instruments, storage systems and networks, with new additions of the edge and cloud systems and services. The sheer complexity of these multi-domain federations makes it hard to manage them and optimize their performance, as small impedance mismatches (that can dynamically develop between systems) could drastically degrade the entire federation performance. Recent proliferation of Software Defined Everything (SDX) technologies combined with containerization frameworks provide custom instruments that can monitor and collect critical measurements at various levels to support diagnoses and performance optimization; but their data too enormous for human operators and analysts to process and generate decisions. Machine Learning (ML) methods that extract critical parameters, relationships and trends from the data offer general solutions. Artificial Intelligence (AI) and ML methods must be custom-developed for these problems based on solid, rigorous foundations, since black-box approaches are often ineffective and unsound.We propose to develop comprehensive AI-Science for the performance of science federations to (i) monitor and control storage, networks, experiments, and computing systems across multiple domains via softwarization layers, at speeds and scales orders of magnitude superior to current practice, (ii) optimally realize and orchestrate complex workflows with high performance by using dynamic state and performance estimation methods, and (iii) aggregate measurements across sites and time to develop infrastructure-level profiles, optimizations and diagnoses using AI-Science based on foundational principles from ML, game theory, and information fusion areas.

Rao, Nageswara↗

NASA NTRS2017

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

computational complexity↗