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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Irradiation Assessment of a Lightweight Industrial Robot - Towards Faster, Safer and Sooner Waste Decommissioning - 20317

Robotic systems have been successfully applied in the nuclear industry for several decades as a safe approach to minimize the exposure dose of human operators. As nuclear waste management and decommissioning gathers pace, there is an emerging interest integrating modern off-the-shelf industrial robots in nuclear robotic systems which make use of complex electronics and software to improve functionality over traditional machines. The use of the industrial robots will significantly increase the pace of development of automated waste management systems at a reduced cost, and although these off-the-shelf robots are proven robust in typical industrial environments, performance in radioactive environments is less clear. This paper investigates the performance degradation of a lightweight industrial robot (KUKA iiwa 7 LBR 800) in a controlled radiation field, aiming to simulate conditions in highly radioactive nuclear waste handling facilities. The degradation of the industrial robot's performance is identified while measuring the air kerma dose-tolerance of sensitive components, via a systematic experimental methodology. The experience from this experiment has demonstrated the significant capabilities of industrial robots, which tolerated a large gamma dose of 164 Gy before a system failure. Future tests are planned, aiming to enable faster, safer and sooner waste management and decommissioning using complex robotic systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2018

Autonomous Coordinated Airspace Services for Terminal and Enroute Operations with Wind Errors

As novel uses of the airspace continue to multiply, there is increasing demand for access to high-density terminal areas around major airports. Since the predicted demand for urban-air-mobility and urban-package-delivery is very high, and the interactions between these different types of aircraft and missions will be extremely complex, increasingly autonomous systems will be required to manage safety and efficiency. This paper presents the current status of an autonomous safety system designed to ensure safe and efficient trajectories for aircraft in terminal airspace, the Terminal Advanced Airspace Concept. Previous papers have demonstrated the efficacy of this algorithm for handling commercial arrivals into a complex metroplex when there is no uncertainty present. This study extends that work to demonstrate the performance of the algorithm under high levels of uncertainty.

terminal operations↗
NASA NTRS2012

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

Shih, Ann T.↗
NASA NTRS1991

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design.

Malin, Jane T.↗
NASA NTRS2004

Integrated Risk Management Within NASA Programs/Projects

As NASA Project Risk Management activities continue to evolve, the need to successfully integrate risk management processes across the life cycle, between functional disciplines, stakeholders, various management policies, and within cost, schedule and performance requirements/constraints become more evident and important. Today's programs and projects are complex undertakings that include a myriad of processes, tools, techniques, management arrangements and other variables all of which must function together in order to achieve mission success. The perception and impact of risk may vary significantly among stakeholders and may influence decisions that may have unintended consequences on the project during a future phase of the life cycle. In these cases, risks may be unintentionally and/or arbitrarily transferred to others without the benefit of a comprehensive systemic risk assessment. Integrating risk across people, processes, and project requirements/constraints serves to enhance decisions, strengthen communication pathways, and reinforce the ability of the project team to identify and manage risks across the broad spectrum of project management responsibilities. The ability to identify risks in all areas of project management increases the likelihood a project will identify significant issues before they become problems and allows projects to make effective and efficient use of shrinking resources. By getting a total team integrated risk effort, applying a disciplined and rigorous process, along with understanding project requirements/constraints provides the opportunity for more effective risk management. Applying an integrated approach to risk management makes it possible to do a better job at balancing safety, cost, schedule, operational performance and other elements of risk. This paper will examine how people, processes, and project requirements/constraints can be integrated across the project lifecycle for better risk management and ultimately improve the chances for mission success.

Connley, Warren↗
NASA NTRS2015

Why Don't They Just Give Us Money? Project Cost Estimating and Cost Reporting

Successful projects require an integrated approach to managing cost, schedule, and risk. This is especially true for complex, multi-year projects involving multiple organizations. To explore solutions and leverage valuable lessons learned, NASA's Virtual Project Management Challenge will kick off a three-part series examining some of the challenges faced by project and program managers when it comes to managing these important elements. In this first session of the series, we will look at cost management, with an emphasis on the critical roles of cost estimating and cost reporting. By taking a proactive approach to both of these activities, project managers can better control life cycle costs, maintain stakeholder confidence, and protect other current and future projects in the organization's portfolio. Speakers will be Doug Comstock, Director of NASA's Cost Analysis Division, Kristin Van Wychen, Senior Analyst in the GAO Acquisition and Sourcing Management Team, and Mary Beth Zimmerman, Branch Chief for NASA's Portfolio Analysis Branch, Strategic Investments Division. Moderator Ramien Pierre is from NASA's Academy for Program/Project and Engineering Leadership (APPEL).

Comstock, Douglas A.↗
NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
NASA NTRS1999

Managing Personal and Group Collections of Information

The internet revolution has dramatically increased the amount of information available to users. Various tools such as search engines have been developed to help users find the information they need from this vast repository. Users often also need tools to help manipulate the growing amount of useful information they have discovered. Current tools available for this purpose are typically local components of web browsers designed to manage URL bookmarks. They provide limited functionalities to handle high information complexities. To tackle this have created DIAMS, an agent-based tool to help users or groups manage their information collections and share their collections with other. the main features of DIAMS are described here.

Wolfe, Shawn R.↗
DOE OSTI2024

Sierra/SD – Verification Test Manual – 5.22

Verification and validation (V&V) of scientific computing programs are important at Sandia National Labs due to the expanding role of computational simulation in managing the United States nuclear stockpile. The complexities of structural response calculations used to analyze physical problems, the varieties of codes applied to the calculations, and the importance of accurate predictions when assessing field conditions demand confidence in the consistency and accuracy of computer codes. Confidence in the accuracy of the predictions arising from computer simulations must ultimately be gained through verification and validation. The Sierra salinas structural dynamics analysis code, Sierra/SD, is used at the DOE Laboratories, and in several DOD projects. The roles of Sierra/SD in the qualification of weapon systems and components for normal and hostile environments throughout the Stockpile-to-Target Sequence include to, • Redesign weapon components. • Certify weapon components and systems for target environments such as hypersonic vehicles. • Certify that components will survive the thermal mechanical shock loads associated with hostile environments. • Evaluate current stockpile issues, including issues associated with uncertainty quantification. • Address many other problems that are encountered in stockpile management. The Sierra/SD verification plan is described, and an evolving set of key verification tests are described in detail. The verification tests ensure the correctness of the mathematics and numerical algorithms associated with functionality describing engineering phenomena. Development is in accordance with a set of tailored Software Quality Engineering (SQE) practices. SQE practices guide the overall verification and validation effort.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

New challenges for Life Sciences flight project management

Scientists have conducted studies involving human spaceflight crews for over three decades. These studies have progressed from simple observations before and after each flight to sophisticated experiments during flights of several weeks up to several months. The findings from these experiments are available in the scientific literature. Management of these flight experiments has grown into a system fashioned from the Apollo Program style, focusing on budgeting, scheduling and allocation of human and material resources. While these areas remain important to the future, the International Space Station (ISS) requires that the Life Sciences spaceflight experiments expand the existing project management methodology. The use of telescience with state-the-art information technology and the multi-national crews and investigators challenges the former management processes. Actually conducting experiments on board the ISS will be an enormous undertaking and International Agreements and Working Groups will be essential in giving guidance to the flight project management Teams forged in this matrix environment must be competent to make decisions and qualified to work with the array of engineers, scientists, and the spaceflight crews. In order to undertake this complex task, data systems not previously used for these purposes must be adapted so that the investigators and the project management personnel can all share in important information as soon as it is available. The utilization of telescience and distributed experiment operations will allow the investigator to remain involved in their experiment as well as to understand the numerous issues faced by other elements of the program The complexity in formation and management of project teams will be a new kind of challenge for international science programs. Meeting that challenge is essential to assure success of the International Space Station as a laboratory in space.

NASA Discipline General Space Life Sciences↗
DOE OSTI2023

Quantifying the effects of pressure management for the Williston basin Brine Extraction and Storage Test (BEST) site using machine learning

Active reservoir management (ARM) through brine extraction can reduce pressure buildup during large-scale implementation of carbon capture and storage (CCS) projects. This study used machine learning (ML)-assisted approaches to analyze bottomhole pressure (BHP) responses to various brine injection and extraction scenarios. Field monitoring data were collected over a 2-year operation period at two injection wells and one extraction well (about 400 meters away) as part of a Brine Extraction and Storage Test (BEST) in the North Dakota portion of the Williston Basin. Injection activities increased the BHPs at the injection wells by around 0.70 MPa (~100 psi) during the operation period. Extraction activities demonstrated the capability to decrease the BHPs at the injection wells by approximately 0.21–0.34 MPa (30–50 psi) depending on the ratio of the extraction and injection well flow rates (the “extraction ratio” – a normalization procedure used in the analysis). The pressure reduction provided by the extraction well equated to 30%–50% of the pressure buildup at the injection well. Furthermore, this work shows how ML analytics can play a key role in estimating reservoir pressure responses for complex injection and extraction activities during pressure management practices of CCS projects.

58 GEOSCIENCES↗
NASA NTRS2011

Software Health Management with Bayesian Networks

Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.

Mengshoel, Ole↗
NASA NTRS2002

Use of Traffic Intent Information by Autonomous Aircraft in Constrained Operations

This paper presents findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision-making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous flight management were compared under conditions of low and high operational complexity (traffic and airspace hazard density). The tactical mode was characterized primarily by the use of traffic state data for conflict detection and resolution and a manual approach to meeting operational constraints. The strategic mode involved the combined use of traffic state and intent information, provided the pilot an additional level of alerting, and allowed an automated approach to meeting operational constraints. Operational constraints applied in the experiment included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. The strategic operational mode was found to be effective in reducing unnecessary maneuvering in conflict situations where the intruder's intended maneuvers would resolve the conflict. Conditions of high operational complexity and vertical maneuvering resulted in increased proliferation of conflicts, but both operational modes exhibited characteristics of stability based on observed conflict proliferation rates of less than 30 percent. Scenario case studies illustrated the need for maneuver flight restrictions to prevent the creation of new conflicts through maneuvering and the need for an improved user interface design that appropriately focuses the pilot's attention on conflict prevention information. Pilot real-time assessment of maximum workload indicated minimal sensitivity to operational complexity, providing further evidence that pilot workload is not the limiting factor for feasibility of an en-route distributed traffic management system, even under highly constrained conditions.

Wing, David J.↗
NASA NTRS2002

Monitor and control software for ground systems in the Deep Space Network

Currently, the NMC is being utilized for 24/7 operations at the three main DSN complexes supporting all of the major spacecraft supported and managed by JPL. A portable version of NMC is being exercised in a Compatibility Test Trailer for off-site monitor and control. Remote monitoring of the three complexes at JPL is accomplished as part of the NMC infrastructure.

monitor and control infrastructure spacecraft oper↗
DOE OSTI2024

Unpinning the Lynchpin: Development of a system to introduce redundancy at Department of Energy laboratories

The United States Department of Energy (DOE) laboratory system employs over 78,000 people and had a budget of $8.1 billion for Fiscal Year 2023 (FY23). This diverse workforce includes employees at all levels from operational support staff to senior level management. Together, the labs take on incredibly complex and unique technical challenges in an attempt to address fundamental National and global needs. These technical challenges often require specialized training such that only a single person is truly capable of completing specific tasks. With the modern competitive environment, and an aging workforce, the risk of technical capability loss is highly probable with potentially severe impact. An online survey of Lawrence Livermore National Laboratories (LLNL) employees, a typical DOE lab, found that of responders with greater than 10 years of experience, 100% of respondents felt burnt out, 40% felt they were not paid fairly, and 50% believe that not enough is done by leadership to retain them as an employee. Couple that to an aging workforce, and the risk of losing institutional knowledge due to single point of failure, or lynchpin, is significant. There is a need for a system which reduces the risk of operational and technical losses due to lynchpin employees leaving the organization. A mitigation of this risk would lead to the successful transfer of knowledge from one generation to the next, improving the rate of development and minimizing general risk of mistakes.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1994

The Design Manager's Aid for Intelligent Decomposition (DeMAID)

Before the design of new complex systems such as large space platforms can begin, the possible interactions among subsystems and their parts must be determined. Once this is completed, the proposed system can be decomposed to identify its hierarchical structure. The design manager's aid for intelligent decomposition (DeMAID) is a knowledge based system for ordering the sequence of modules and identifying a possible multilevel structure for design. Although DeMAID requires an investment of time to generate and refine the list of modules for input, it could save considerable money and time in the total design process, particularly in new design problems where the ordering of the modules has not been defined.

Rogers, James L.↗
DOE OSTI2024

Building Performance Software: Portfolio-Level Capabilities and Applications

Navigating the broad and rapidly evolving market landscape of software solutions is complex whether you are a sustainability leader, building owner, energy manager, or building engineer with energy and greenhouse gas (GHG) emissions reduction goals for a portfolio of buildings. The Department of Energy’s Better Buildings partners have noted this complexity and the associated lack of publicly available information. In response, this report reviews the ecosystem of environmental, social, and governance (ESG), energy management information systems (EMIS), and decarbonization software with the goal of orienting prospective users to current offerings. Organizations can utilize this guidance to determine the specific capabilities needed to support decarbonization efforts and procure appropriate software to streamline the GHG emissions reduction process. In this paper, we refer to “decarbonization software” as the category of software that meets an organization’s needs for decarbonization planning, implementation, and tracking. This software may have a heritage in ESG or EMIS, or it may be an entirely new product. This report offers a snapshot of today’s rapidly evolving decarbonization software capabilities, along with guidance for procuring and utilizing it that will remain relevant despite any future software changes. Exploratory research was conducted on over 100 software providers, and interviews were held with 28 of them. Note that inclusion in this report does not indicate an endorsement, nor does a product’s absence from this report indicate a lack of suitability

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

EMASS (trademark): An expandable solution for NASA space data storage needs

The data acquisition, distribution, processing, and archiving requirements of NASA and other U.S. Government data centers present significant data management challenges that must be met in the 1990's. The Earth Observing System (EOS) project alone is expected to generate daily data volumes greater than 2 Terabytes (2 x 10(exp 12) Bytes). As the scientific community makes use of this data, their work will result in larger, increasingly complex data sets to be further exploited and managed. The challenge for data storage systems is to satisfy the initial data management requirements with cost effective solutions that provide for planned growth. The expendable architecture of the E-Systems Modular Automated Storage System (EMASS(TM)), a mass storage system which is designed to support NASA's data capture, storage, distribution, and management requirements into the 21st century is described.

Peterson, Anthony L.↗