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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Enabling Cybersecurity, Situational Awareness and Resilience in Distribution Grids with High Penetration of Photovoltaics (CARE-PV) (Final Report)

Since legacy distribution systems have very limited visibility beyond the substation, high penetration of PV at the grid edge presents some unique operational challenges. One approach to address these challenges is to use information from advanced metering infrastructure (AMI) and µPMUs. However, exploiting this information is impacted by a number of factors, including multi-timescale measurements, volume of data generated, communication network impairments (e.g., information loss and latency) and susceptibility to cyber-attacks. Therefore, one of the critical tasks involved in the management of a distribution grid is to develop complete situational awareness by integrating cyber-security mechanisms with state estimation strategies and leveraging this situational awareness to assure energy services at strategic locations while exploiting AMI/PV inverter/ µPMU data. This CARE-PV project addresses the fundamental challenges in situational awareness and resilience to cyber and physical vectors by exploiting the synergy between innovative modeling, estimation, data analytics, testing and validation using smart PV inverters designed at K-State and facilities at NREL. Specifically, the project involved the development, testing and validation of the following novel enabling technologies: (Thrust 1) Resilience to cyber vectors that impact data integrity was addressed via a two-level defense strategy that combines cyber intrusion detection using self-learning, cooperative smart PV inverters, and a novel moving target defense framework to combat data integrity attacks. (Thrust 2) Resilience to cyber-physical vectors that impact situational awareness by limiting data availability was addressed via novel centralized and decentralized, sparsity-based static and dynamic state estimation approaches that enhance observability even when the underlying system is unobservable. (Thrust 3) Leveraging a unique probabilistic sensitivity analysis approach accompanied by one-of-a-kind dominant influencer set computation, the vulnerability of critical infrastructure at strategic locations was evaluated so that proactive PV-based control strategies can be used to support operations under normal/outage scenarios. These CARE-PV project innovations were demonstrated on both small-scale IEEE and larger utility-scale testbeds (Thrust 4). Feedback from Industry Advisory Board members was used to formulate a commercialization pathway for a subset of CARE-PV technologies. These CARE-PV technologies will ultimately lead to reliable and secure, large-scale integration of renewable energy and mitigate the risk of energy disruption resulting from cyber incidents and other emerging threats within the energy environment.

14 SOLAR ENERGY↗
DOE OSTI2025

Solar Decarbonization of Paraffin Dehydrogenation Through Particle Heat Carriers (Final Technical Report)

This project focuses on solutions to decarbonize high-temperature catalytic processes using solar thermal heat. The primary project goal is to show the validity of a moving packed bed reactor for propane dehydrogenation using catalyst particles as the heat carrier for the reaction, which can be heated by concentrated solar energy in a particle receiver. This concept, if further developed, may provide a cost-effective pathway for converting lower value gases to important chemical precursors for industrial materials using only renewable energy. The project was divided into six tasks. In Task 1, DFT calculations were performed to understand the role of Pt and Sn in the catalytic dehydrogenation reaction. In Task 2 chemical kinetics measurements were made for several catalyst formulations at high temperatures. In Task 3, the solar absorptance of catalyst particles was compared to the absorptance of commonly used materials in particle receivers. In Task 4, numerical models were developed which could predict performance of the complete system and predict specific temperatures in the system. In Task 5, a prototype system was designed, fabricated, and tested to show the validity of the concept. Task 6 concerned project management activities. Experiments with the prototype showed repeatable thermal performance at temperatures targeted for the reaction. A limited set of tests were done with active catalyst and propane dehydrogenation, showing conversion of propane to propylene with a range of conversions and selectivities. The results are promising, and the prototype designed was reliable during testing, and the team expects that further development of the prototype would yield improved results. A numerical model framework based on coupled fluid and particle mechanics was developed with high computational efficiency using GPU calculations. The model may prove highly useful for evaluating other high-temperature particle systems. However, it was determined that simpler porous media models were good fits for the needs of the current moving packed bed concept. Data showing strong solar absorption of the particles validates the plan of using existing solar particle receivers with only a change in the particle type. Catalyst investigation showed that Pt 1 Sn 3 is the most viable candidate for developing PtSn catalysts for high temperature propane dehydrogenation, considering the balance of activity, selectivity, and deactivation. This project completed an initial study of various factors needed to incorporate a moving bed catalytic reactor for propane dehydrogenation into a concentrated solar thermal particle system. Future developments may allow this technology to be scaled up and help to use solar thermal energy to decarbonize not only the propane dehydrogenation reaction, but other gas-solid catalytic reactions at similar temperatures.

14 SOLAR ENERGY↗
DOE OSTI2023

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts

MLCommons is an effort to develop and improve the artificial intelligence (AI) ecosystem through benchmarks, public data sets, and research. It consists of members from start-ups, leading companies, academics, and non-profits from around the world. The goal is to make machine learning better for everyone. In order to increase participation by others, educational institutions provide valuable opportunities for engagement. In this article, we identify numerous insights obtained from different viewpoints as part of efforts to utilize high-performance computing (HPC) big data systems in existing education while developing and conducting science benchmarks for earthquake prediction. As this activity was conducted across multiple educational efforts, we project if and how it is possible to make such efforts available on a wider scale. This includes the integration of sophisticated benchmarks into courses and research activities at universities, exposing the students and researchers to topics that are otherwise typically not sufficiently covered in current course curricula as we witnessed from our practical experience across multiple organizations. As such, we have outlined the many lessons we learned throughout these efforts, culminating in the need for benchmark carpentry for scientists using advanced computational resources. The article also presents the analysis of an earthquake prediction code benchmark while focusing on the accuracy of the results and not only on the runtime; notedly, this benchmark was created as a result of our lessons learned. Energy traces were produced throughout these benchmarks, which are vital to analyzing the power expenditure within HPC environments. Additionally, one of the insights is that in the short time of the project with limited student availability, the activity was only possible by utilizing a benchmark runtime pipeline while developing and using software to generate jobs from the permutation of hyperparameters automatically. It integrates a templated job management framework for executing tasks and experiments based on hyperparameters while leveraging hybrid compute resources available at different institutions. The software is part of a collection called cloudmesh with its newly developed components, cloudmesh-ee (experiment executor) and cloudmesh-cc (compute coordinator).

58 GEOSCIENCES↗
NASA NTRS1971

Hazard pay: An effective antagonist

Procedures for allocating hazardous pay to employees are outlined. According to the guidelines, only top level management can authorize hazardous tasks and decide if said task is indeed hazardous. The guidelines also state that hazardous jobs may be performed only if it is essential to finish a project and cannot be adequately safequarded.

Alexander, R. E.↗
NASA NTRS1979

Adaptive allocation of decisionmaking responsibility between human and computer in multitask situations

As human and computer come to have overlapping decisionmaking abilities, a dynamic or adaptive allocation of responsibilities may be the best mode of human-computer interaction. It is suggested that the computer serve as a backup decisionmaker, accepting responsibility when human workload becomes excessive and relinquishing responsibility when workload becomes acceptable. A queueing theory formulation of multitask decisionmaking is used and a threshold policy for turning the computer on/off is proposed. This policy minimizes event-waiting cost subject to human workload constraints. An experiment was conducted with a balanced design of several subject runs within a computer-aided multitask flight management situation with different task demand levels. It was found that computer aiding enhanced subsystem performance as well as subjective ratings. The queueing model appears to be an adequate representation of the multitask decisionmaking situation, and to be capable of predicting system performance in terms of average waiting time and server occupancy. Server occupancy was further found to correlate highly with the subjective effort ratings.

Chu, Y.-Y.↗
NASA NTRS1985

Space station human productivity study. Volume 5: Management plans

The 67 Management Plans represent recommended study approaches for resolving 108 of the 305 Issues which were identified. Each study Management Plan is prepared in three formats: Management Plan Overview (lists the subsumed Issues, study background, and related overview information); Study Plan (details the study approach by tasks, lists special needs, and describes expected study products); Schedule-Task Flow (provides a time-lined schedule for the study tasks and resource requirements). The Management Relationships Matrix, included in this volume, shows the data input-output relationships among all recommended studies. A listing is also included which cross-references the unresolved requirements to Issues to management plans. A glossary of all abbreviations utilized is provided.

Source record↗
NASA NTRS1990

Background, current status, and prognosis of the ongoing slush hydrogen technology development program for the NASP

Among the Hydrogen Projects at the NASA Lewis Research Center (NASA LeRC), is the task of implementing and managing the Slush Hydrogen (SLH2) Technology Program for the United States' National AeroSpace Plane Joint Program Office (NASP JPO). The objectives of this NASA LeRC program are to provide verified numerical models of fluid production, storage, transfer, and feed systems and to provide verified design criteria for other engineered aspects of SLH2 systems germane to a NASP. The pursuit of these objectives is multidimensional, covers a range of problem areas, works these to different levels of depth, and takes advantage of the resources available in private industry, academia, and the U.S. Government. A summary of the NASA LeRC overall SLH2 program plan, is presented along with its implementation, the present level of effort in each of the program areas, some of the results already in hand, and the prognosis for the effort in the immediate future.

Dewitt, R. L.↗
NASA NTRS1991

Quo vadimus: Coming to grips with the information world

The new information-oriented culture in which we find ourselves has created new relationships, new stimulating and expanding opportunities, new methods of doing our work, and new environments in which we carry out our work. An integral part of the NASA aerospace research and development (R and D) process is the scientific and technical information (STI) associated with it; it is both a raw material (input) and a product (output) of this process. Within this process, the NASA STI Program is tasked to provide information management and services, to ensure that accurate and timely STI is generated and entered into an appropriate information service and made available in a usable form to those who have a need for it; in essence, a means to exploit both internal (NASA corporate) and pertinent external (other governmental/industrial/foreign) information to meet the requirements of the R and D community. To understand the STI Program management issues, it is critical to understand the role of the STI Program in the context of the R and D process. STI management must become part of the accepted culture of the R and D community, but it cannot become so unless adopted and accepted by it. A start should be made now to integrate the NASA STI Program into the R and D infrastructure, including funding and operational control. Within this infrastructure, we must obtain management commitment, review and produce policy reflecting the organizational status, allocate responsibilities, and set to work on implementing the true requirements of the R and D community.

Blados, Walter R.↗
NASA NTRS1990

IDEF5 Ontology Description Capture Method: Concept Paper

The results of research towards an ontology capture method referred to as IDEF5 are presented. Viewed simply as the study of what exists in a domain, ontology is an activity that can be understood to be at work across the full range of human inquiry prompted by the persistent effort to understand the world in which it has found itself - and which it has helped to shape. In the contest of information management, ontology is the task of extracting the structure of a given engineering, manufacturing, business, or logistical domain and storing it in an usable representational medium. A key to effective integration is a system ontology that can be accessed and modified across domains and which captures common features of the overall system relevant to the goals of the disparate domains. If the focus is on information integration, then the strongest motivation for ontology comes from the need to support data sharing and function interoperability. In the correct architecture, an enterprise ontology base would allow th e construction of an integrated environment in which legacy systems appear to be open architecture integrated resources. If the focus is on system/software development, then support for the rapid acquisition of reliable systems is perhaps the strongest motivation for ontology. Finally, ontological analysis was demonstrated to be an effective first step in the construction of robust knowledge based systems.

Menzel, Christopher P.↗
NASA NTRS1990

Crew factors in the aerospace workplace

The effects of technological change in the aerospace workplace on pilot performance are discussed. Attention is given to individual and physiological problems, crew and interpersonal problems, environmental and task problems, organization and management problems, training and intervention problems. A philosophy and conceptual framework for conducting research on these problems are presented and two aerospace studies are examined which investigated: (1) the effect of leader personality on crew effectiveness and (2) the working undersea habitat known as Aquarius.

Kanki, Barbara G.↗
NASA NTRS1995

The coupling of fluids, dynamics, and controls on advanced architecture computers

This grant provided for the demonstration of coupled controls, body dynamics, and fluids computations in a workstation cluster environment; and an investigation of the impact of peer-peer communication on flow solver performance and robustness. The findings of these investigations were documented in the conference articles.The attached publication, 'Towards Distributed Fluids/Controls Simulations', documents the solution and scaling of the coupled Navier-Stokes, Euler rigid-body dynamics, and state feedback control equations for a two-dimensional canard-wing. The poor scaling shown was due to serialized grid connectivity computation and Ethernet bandwidth limits. The scaling of a peer-to-peer communication flow code on an IBM SP-2 was also shown. The scaling of the code on the switched fabric-linked nodes was good, with a 2.4 percent loss due to communication of intergrid boundary point information. The code performance on 30 worker nodes was 1.7 (mu)s/point/iteration, or a factor of three over a Cray C-90 head. The attached paper, 'Nonlinear Fluid Computations in a Distributed Environment', documents the effect of several computational rate enhancing methods on convergence. For the cases shown, the highest throughput was achieved using boundary updates at each step, with the manager process performing communication tasks only. Constrained domain decomposition of the implicit fluid equations did not degrade the convergence rate or final solution. The scaling of a coupled body/fluid dynamics problem on an Ethernet-linked cluster was also shown.

Atwood, Christopher↗
NASA NTRS1995

Training for Aviation Decision Making: The Naturalistic Decision Making Perspective

This paper describes the implications of a naturalistic decision making (NDM) perspective for training air crews to make flight-related decisions. The implications are based on two types of analyses: (a) identification of distinctive features that serve as a basis for classifying a diverse set of decision events actually encountered by flight crews, and (b) performance strategies that distinguished more from less effective crews flying full-mission simulators, as well as performance analyses from NTSB accident investigations. Six training recommendations are offered: (1) Because of the diversity of decision situations, crews need to be aware that different strategies may be appropriate for different problems; (2) Given that situation assessment is essential to making a good decision, it is important to train specific content knowledge needed to recognize critical conditions, to assess risks and available time, and to develop strategies to verify or diagnose the problem; (3) Tendencies to oversimplify problems may be overcome by training to evaluate options in terms of goals, constraints, consequences, and prevailing conditions; (4) In order to provide the time to gather information and consider options, it is essential to manage the situation, which includes managing crew workload, prioritizing tasks, contingency planning, buying time (e.g., requesting holding or vectors), and using low workload periods to prepare for high workload; (5) Evaluating resource requirements ("What do I need?") and capabilities ("'What do I have?" ) are essential to making good decisions. Using resources to meet requirements may involve the cabin crew, ATC, dispatchers, and maintenance personnel; (6) Given that decisions must often be made under high risk, time pressure, and workload, train under realistic flight conditions to promote the development of robust decision skills.

Orasanu, Judith↗
NASA NTRS2007

Physiological Self-Regulation and Adaptive Automation

Adaptive automation has been proposed as a solution to current problems of human-automation interaction. Past research has shown the potential of this advanced form of automation to enhance pilot engagement and lower cognitive workload. However, there have been concerns voiced regarding issues, such as automation surprises, associated with the use of adaptive automation. This study examined the use of psychophysiological self-regulation training with adaptive automation that may help pilots deal with these problems through the enhancement of cognitive resource management skills. Eighteen participants were assigned to 3 groups (self-regulation training, false feedback, and control) and performed resource management, monitoring, and tracking tasks from the Multiple Attribute Task Battery. The tracking task was cycled between 3 levels of task difficulty (automatic, adaptive aiding, manual) on the basis of the electroencephalogram-derived engagement index. The other two tasks remained in automatic mode that had a single automation failure. Those participants who had received self-regulation training performed significantly better and reported lower National Aeronautics and Space Administration Task Load Index scores than participants in the false feedback and control groups. The theoretical and practical implications of these results for adaptive automation are discussed.

Prinzell, Lawrence J.↗
NASA NTRS2011

Analogs and the BHP Risk Reduction Strategy for Future Spaceflight Missions

In preparation for future exploration missions to distant destinations (e.g., Moon, Near Earth Objects (NEO), and Mars), the NASA Human Research Program s (HRP) Behavioral Health and Performance Element (BHP) conducts and supports research to address four human health risks: Risk of Behavioral Conditions; Risk of Psychiatric Conditions; Risk of Performance Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team; and Risk of Performance Errors due to Sleep Loss, Fatigue, Circadian Desynchronization, and Work Overload (HRP Science Management Plan, 2008). BHP Research, in collaboration with internal and external research investigators, as well as subject matter experts within NASA operations including flight surgeons, astronauts, and mission planners and others within the Mission Operations Directorate (MOD), identifies knowledge and technology gaps within each Risk. BHP Research subsequently manages and conducts research tasks to address and close the gaps, either through risk assessment and quantification, or the development of countermeasures and monitoring technologies. The resulting deliverables, in many instances, also support current Medical Operations and/or Mission Operations for the International Space Station (ISS).

Whitmire, Sandra↗
NASA NTRS2012

Enhanced project management tool

A system for managing a project that includes multiple tasks and a plurality of workers. Input information includes characterizations based upon a human model, a team model and a product model. Periodic reports, such as one or more of a monthly report, a task plan report, a schedule report, a budget report and a risk management report, are generated and made available for display or further analysis or collection into a customized report template. An extensible database allows searching for information based upon context and upon content. Seven different types of project risks are addressed, including non-availability of required skill mix of workers. The system can be configured to exchange data and results with corresponding portions of similar project analyses, and to provide user-specific access to specified information.

Maluf, David A.↗
NASA NTRS2013

Multicore Considerations for Legacy Flight Software Migration

In this paper we will discuss potential benefits and pitfalls when considering a migration from an existing single core code base to a multicore processor implementation. The results of this study present options that should be considered before migrating fault managers, device handlers and tasks with time-constrained requirements to a multicore flight software environment. Possible future multicore test bed demonstrations are also discussed.

legacy flight software↗
NASA NTRS2016

Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

software defined radio↗