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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Automation for Distributed Energy Resources Risk Manager Using OSCAL

The risk management framework (RMF) provides a well-organized and thorough approach to diagnose information technology (IT) system threats, to gather required materials to comply with industry standards, and to document a plan for achieving authority to operate (ATO). ATO is given by the operating authority with the awareness of vulnerabilities that arise when operating the IT system. The primary goal of the National Renewable Energy Laboratory’s (NREL’s) distributed energy resource (DER) RM application is to provide a user-friendly interface and in-depth guidance for generating the authorization package for the authorizing official to review. In other words, the application satisfies steps 1 through 7 of the RMF process with a focus on DERs.

cybersecurity↗
DOE OSTI2023

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Operator strategies under varying conditions of workload

An attempt was made to operationally define and measure strategic behavior in a complex multiple task environment. The Multi-Attribute Task battery was developed to simulate various aspects of flight and consisted of an auditory communication task, monitoring tasks, a tracking tasks, a resource management task which allowed a wide range of responding patterns, and a scheduling window which allowed operators to predict changes in workload. This battery was validated for its sensitivity to strategic behavior, and baseline measures for each individual task were collected. Twenty-four undergraduate and graduate students then performed the battery for four 64 minute sessions which took place over a period of 2 days. Each subject performed the task battery under four levels of workload, which were presented for equal lengths of time during all four sessions. Results indicated that in general, performance improves as a function of experience with the battery, but that performance decreased as workload level increased. The data also showed that subjects developed strategies for responding to the resource management task which allowed them to manage the high workload levels more efficiently. This particular strategy developed over time but was also associated with errors of complacency. These results are presented along with implications for the aviation field and areas of future research.

Arnegard, Ruth J.↗
NASA NTRS2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Ghada Y.H. El Serafy↗
DOE OSTI2026

Near-Real-Time Statistical Analysis and Visualization of Streamflow from a Deep-Learning Rainfall-Runoff Model

Near-real-time (NRT) streamflow data are critical importance for timely water resources management. Here, we developed an open-source tool, FlowStats, for NRT streamflow analysis and visualization in Germany, based on NRT meteorological data from the German Weather Service and simulated streamflow from a long short-term memory neural network (LSTM). The LSTM model achieved very good overall performance, median NSE of 0.80 for the test period across 1,479 catchments. FlowStats provides options for deriving various streamflow statistics, from normal and abnormal streamflow detection to drought and flood analyses. An example analysis from FlowStats revealed widespread below-normal to extreme low-flow conditions across Germany from March to May 2025, which weakened from June to September 2025. Drought analysis for September 2025 highlighted severe to extreme drought conditions in northwestern Germany, while flood classifications indicated that high-flow events occurred in southwestern Germany. FlowStats can be used for various hydrological assessments to support water resources management.

Hydrological modeling↗
DOE OSTI2021

Initialized Earth system prediction from subseasonal to decadal timescales

Initialized Earth system predictions are made by starting a numerical prediction model in a state as consistent as possible to observations, and running it forward in time for up to ten years. Skillful predictions at time slices from subseasonal to seasonal (S2S), seasonal to interannual (S2I) and seasonal to decadal (S2D) offer information useful for various stakeholders, from agriculture to water resource management, and human and infrastructure safety. In this Review, we examine the processes influencing predictability, and discuss estimates of skill across S2S, S2I and S2D timescales. There are encouraging signs that skillful predictions can be made: at S2S timescales, there has been some skill in predicting the Madden-Julian Oscillation and North Atlantic Oscillation; at S2I in predicting the El Niño-Southern Oscillation; and at S2D, in predicting variability in North Atlantic sea surface temperatures. However, challenges remain, and future work must prioritise reducing model error, more effectively communicating forecasts to users, and increasing process and mechanistic understanding that could increase predictive skill and, in turn, confidence. As numerical models progress towards Earth system models, initialized predictions are expanding to include prediction of sea-ice, air pollution, terrestrial and ocean biochemistry which can bring clear benefit to society and various stakeholders.

climate prediction↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2021

Quantifying Dam-Induced Fluctuations in Streamflow Frequencies Across the Colorado River Basin

Periodic fluctuations in natural streamflow are a major driver of river ecosystem dynamics and water resource management. However, most U.S. rivers are impacted both by long-term hydroclimatic trends and dams that alter flow variability. Despite these impacts, it remains largely unexplored how dams affect the dominant frequencies of natural streamflow over a highly regulated river network. We investigated the entire Colorado River Basin (CRB) to understand how the annual (10–14 months) and multi-annual (24–60 months) frequencies in natural flow regimes have been progressively altered by dams. Given the significant alteration over the CRB, we captured changes in streamflow frequencies between naturalized and observed monthly flows via wavelet analysis. Based on the similarity of changes in streamflow frequencies (annual and multi-annual) over the last 30 years, sections of the riverine network were classified into four groups. The annual frequency was relatively well preserved downstream of Hoover Dam, while showing a systematic trend of alteration downstream of Glen Canyon Dam until Hoover Dam. Meanwhile, the multi-annual frequency component was highly altered for the entire Lower Colorado main stem (i.e., downstream of Glen Canyon). We also identified dams with significant impacts on streamflow frequency by comparing wavelet coherence estimates. This study advances the notion that dams fundamentally alter river flow regimes across multiple frequencies and with varying amplitudes over time and space, with alteration propagating – or being dampened – by both hydroclimatic fluctuations and water resource management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.

Bailey, Nathan R.↗
NASA NTRS1996

Cross-Cultural Barriers to Effective Communication in Aviation

Communication is essential to safe flight, as evidenced by several accidents in which crew communicates was found to have contributed to the accidents. This chapter documents the essential role of explicit efficient communication to flight safety with a global context. It addresses communication between flight crews and air traffic controllers in regions a the world where pilots and controllers speak different native languages, as well as cases in which crew members within the flight deck represent different native languages and cultures. It also addresses problems associated with "exporting" crew resource management training programs to parts of the world which values and norms differ from those of the United States, where these programs were initially developed. This chapter is organized around several central questions: (1) What are various kinds of communication failures and what are their consequences; (2) What are the causes of communication failure; (3) What are features of effective crew communication; (4) What can be done to enhance communication success? To explore a wider range of communication failures than available from accident reports, we examined a set of incident reports from the Aviation Safety Reporting System. These could be classified into three major categories: those in which language actually interfered with transmission of a message; those in which transmission was adequate but the context was not expressed unambiguously and thus the message received was not the same as the message intended; and those in which the message was received as intended, but was not adequately understood or acted upon, mainly because of cultural factors. The consequences of failed communication can be flight errors (such as when a clearance is not received correctly), loss of situation awareness, or failure of crew members (or ATC and pilots) to build a shared understanding of a situation. Causes of misunderstanding can be traced to a number of sources, often grounded in faulty assumptions held by one or both parties to a conversation. Speakers and listeners often experience "illusionary understanding" in which they think they understand each other, but in fact do not. While this problem can exist within a single culture, it is much more serious across cultures. Training in effective explicit communication is a component of Crew Resource Management training programs developed in the U.S. These programs are being adopted by airlines around the world, with varying degrees of success. The level of success in part depends on how similar the conversational and social styles of those cultures are to those of the U.S. A factor that influences conversational style is a culture's relative positioned on two major dimensions that distinguish national cultural groups: individualism vs. collectivism and degree of power distance. The chapter concludes with a discussion of techniques for overcoming the various classes of communication failures and for effectively adapting training programs to fit the values and norms of cultures around the globe.

Fischer, U.↗
DOE OSTI2025

Advancing ocean monitoring and knowledge for societal benefit: the urgency to expand Argo to OneArgo by 2030

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come.

ARGO↗
DOE OSTI2022

Environmental Share: Damage to a Cultural Site from Off-Road Driving [Slides]

Cultural resources, including archaeological sites and historic buildings, at Los Alamos National Laboratory are protected under the National Historic Preservation Act. Disclosure of archaeological site locations is prohibited by law, which can make it difficult to communicate issues or identify where these sites occur. The Laboratory Cultural Resources Management Plan describes how we work to manage and protect these resources: https://permalink.lanl.gov/object/tr?what=info:lanlrepo/lareport/LA-UR-19-21590. Recently, our cultural resources staff identified vehicle damage to a site . There were no active projects occurring in this area, but evidence that vehicles had been driving over the site was visible. It is not possible to mark the locations of all cultural resources as there are about 2000 on Laboratory property.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ambassador Project (Final Report)

SEL, in collaboration with its partners, performed research, development and demonstration of a trust, data, and resource management software layer enabling multiple software applications from different suppliers to operate in a Software Defined Infrastructure. The Energy sector has successfully deployed Software Defined Networking (SDN) technology and is rapidly scaling deployments. One major benefit of SDN is the abstracted centralized nature of the orchestration and management of the network. This architecture enables end users to deploy new technology and capabilities as quickly as they perform firmware upgrades to field devices. When an end user needs to roll trucks to install new equipment, they simply deploy new software to run on top of this SD-Infrastructure. This has attracted many software companies to develop value added features and introduce new capabilities, which is all good for the industry but has also introduced new challenges, including how to manage trust between these software applications, how to manage the data integrity and access, and how to manage access to the network resources each of these software applications are demanding. Completion of this project developed and demonstrated a safe and reliable resource scheduler and cybersecurity trust management communication platform allowing multiple software applications to operate in a SD-Infrastructure resulting in the commercialization of a software eco-system and architecture that maintains interoperability, cybersecurity, and reliability where the end user can safely scale out their software to leverage the powerful benefits of SDN.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

In an effort to bridge the gap between the research community and the user agencies, this investigation was designed to take the remote sensing technology and products of that technology to the user agencies and to assist them in the use of this technology. The first semi-annual report summarizes the progress which has been made in the following specific projects: (1) pilot study for land use inventory of the Great Lakes Watershed; (2) resource inventory of Marion County (Indianapolis), Indiana; (3) resource inventory of 8 central Indiana counties for the Indiana Heartland Coordinating Commission; (4) applications within the Indiana Department of Natural Resources; (5) applications within the Indiana Department of Commerce; and (6) applications within the USDA Soil Conservation Service.

Landgrebe, D. A.↗
NASA NTRS1977

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

The author has identified the following significant results. The Lydich quadrangle area was successfully classified into seven cover types: (1) trees, (2) poorly drained soil and water, (3) pasture land, (4) well drained brown soil, (5) moderately well drained dark brown soil, (6) moderately drained soil, and (7) medium to poorly drained soil. Measurements of the percent of mapping unit represented by a named soil series range from 44 to 55 percent. If the class identified as vegetation is combined with the named unit, the range increases from 54 to 64 percent. The Xenia mapping unit was the only unit represented by less than 50 percent of the named unit. Results from the intensive tent moth study in Owensburg and Williams were interpreted from 70 mm color infrared and visually transferred to maps. A correction factor was necessary, because the date the sample photography was taken was a month later than the intensive site data (CF x acres defoliated in each level = expanded defoliated acres).

Weismiller, R. A.↗
NASA NTRS1977

Application of remote sensing technology to the solution of problems in the management of resources in Indiana

The author has identified the following significant results. The Lydick, South Bend West, South Bend East, and Osceola quadrangles were successfully classified into twenty-six cover types with a high degree of accuracy. The ability of this computer-assisted classification system to delineate various stages of urban development, from heavy industry to new suburban development, was of particular interest to the planning commission. The classification is clearly more beneficial than the existing agricultural soils and topographic maps, because it shows the current ground cover conditions all on one map. It shows how an area is developing along with the specific type and location of new development. The classification also shows at a glance whether development is taking place in an area suitable for development or if growth is taking place in prime agricultural land, areas of poor foundation material, or other places where development is not desirable.

Weismiller, R. A.↗