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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Overcoming persistent challenges in putting environmental flow policy into practice: a systematic review and bibliometric analysis

The implementation of environmental flows (e-flows) aims to reduce the negative impacts of hydrological alteration on freshwater ecosystems. Despite the growing attention to the importance of e-flows since the 1970s, actual implementation has lagged. Therefore, we explore the limitations in e-flows implementation, their systemic reasons, and solutions. We conducted a systematic review and a bibliometric analysis to identify peer-reviewed articles published on the topic of e-flows implementation research in the last two decades, resulting in 68 research and review papers. Co-occurrence of terms, and geographic and temporal trends were analyzed to identify the gaps in environmental water management and propose recommendations to address limitations on e-flows implementation. We identify the underlying causes and potential solutions to such challenges in environmental water management. The limitations to e-flow implementation identified were categorized into 21 classes. The most recognized limitation was the competing priorities of human uses of water (n = 29). Many secondary limitations, generally co-occurring in co-causation, were identified as limiting factors, especially for implementing more nuanced and sophisticated e-flows. The lack of adequate hydrological data (n = 24) and ecological data (n = 28) were among the most mentioned, and ultimately lead to difficulties in starting or continuing monitoring/adaptive management (n = 28) efforts. The lack of resource/capacity (n = 21), experimentation (n = 19), regulatory enforcement (n = 17), and differing authorities involved (n = 18) were also recurrent problems, driven by the deficiencies in the relative importance given to e-flows when facing other human priorities. In order to provide a clearer path for successful e-flow implementation, system mapping can be used as a starting point and general-purpose resource for understanding the sociohydrological problems, interactions, and inherited complexity of river systems. Secondly, we recommend a system analysis approach to address competing demands, especially with the use of coupled water-energy modeling tools to support decision-making when hydropower generation is involved. Such approaches can better assess the complex interactions among the hydrologic, ecological, socioeconomic, and engineering dimensions of water resource systems and their effective management. Lastly, given the complexities in environmental water allocation, implementation requires both scientific rigor and proven utility. Consequently, and where possible, we recommend a move from simplistic flow allocations to a more holistic approach informed by hydroecological principles. To ease conflicts between competing water demands, water managers can realize more 'pop per drop' by supporting key components of a flow regime that include functional attributes and processes that enhance biogeochemical cycling, structural habitat formation, and ecosystem maintenance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Global teleconnections influencing large-scale drought in the United States using SVDI

Understanding recent large-scale drought patterns and the mechanisms producing extreme drought events is vital for future drought forecasts and understanding future drought risks. Increasingly, vapor pressure deficit (VPD) has been used as an important measure of evaporative demand and proxy for drought detection. In this study, VPD is used to calculate the new Standardized VPD Drought Index (SVDI) with NASA North American Land Data Assimilation System (NLDAS) data. Previous studies have shown that SVDI accurately identifies the timing and magnitude short-term droughts in the United States (U.S). In the present study, SVDI is now used to identify large-scale drought patterns between 1980 and 2021 and drought variability driven by selected global teleconnections originating in the Pacific and Atlantic Oceans. Spatial drought characteristics were extracted from SVDI using empirical orthogonal function (EOF) analysis. Then a k-means clustering algorithm was applied to both EOF principal components and primary teleconnections, including the El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) to identify drought events driven by the Pacific Ocean. Results show that the SVDI is useful in evaluating large-scale drought variability in the U.S. related to global teleconnections, and that mechanisms influencing summer drought patterns in the Western and Southwestern U.S. are driven by a tropical-extratropical interactions originating in the equatorial Pacific Ocean related to ENSO dynamics with interdecadal variability modulated by PDO. The large-scale droughts in the Central and Southern U.S., like those in 2011 and 2012, on the other hand, are driven by the North Pacific Ocean warm pool during a strong negative PDO, which subsequently influenced variability in the Bermuda-Azores High in the Atlantic Ocean. In summer 2011, the Bermuda-Azores High weakened, reducing the onshore winds and moisture transport along the eastern Gulf of Mexico and contributing to ongoing drought in the region. The Northern Pacific and Atlantic Ocean sea surface temperatures (SSTs) have increased between 1980 and 2021. In conclusion, as SSTs continue to rise in the Northern Pacific Ocean, one consequence of the coupled North Pacific warm pool and atmospheric dynamics, is to increase summer drought variability over a large region in the southern and midwestern U.S. under global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Revealing the Structure and Dynamics of Self-Generated Electric and Magnetic Fields Near Plasma Stagnation in Laser-Driven Hohlraums

By coupling newly developed triparticle charged particle radiography with radiography reconstruction algorithms and novel reconstruction postprocessing techniques, the spatial structure and time evolution of self-generated electric and magnetic fields in laser-driven vacuum hohlraums have been quantitatively revealed. Through high-fidelity data from a series of experiments, it is shown that late in the hohlraum evolution (after the end of laser drive) these fields are strongly correlated in both space and time, providing evidence that their evolution is primarily dominated by advection with the plasma flow. At these late times, plasma flow velocities inferred from both gross radiography analysis and field reconstructions (and corroborated with Thomson scattering measurements) indicate that the plasma is approaching stagnation near the hohlraum axis. Finally, these experiments provide not only new physical insight into spontaneously generated hohlraum fields, but also provide important spatially and temporally resolved information for future benchmarking of numerical codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Unlocking the distinctive enzymatic functions of the early plant biomass deconstructive genes in a brown rot fungus by cell-free protein expression

ABSTRACT Saprotrophic fungi that cause brown rot of woody biomass evolved a distinctive mechanism that relies on reactive oxygen species (ROS) to kick-start lignocellulosic polymers’ deconstruction. These ROS agents are generated at incipient decay stages through a series of redox relays that shuttle electrons from fungus’s central metabolism to extracellular Fenton chemistry. A list of genes has been suggested encoding the enzyme catalysts of the redox processes involved in ROS’s function. However, navigating the functions of the encoded enzymes has been challenging due to the lack of a rapid method for protein synthesis. Here, we employed cell-free expression system to synthesize four redox or degradative enzymes, which were identified, by transcriptomic data, as conserved players of the ROS oxidation phase across brown rot fungal species. All four enzymes were successfully expressed and showed activities that enable confident assignment of function, namely, benzoquinone reductase (BQR), ferric reductase, α-L-arabinofuranosidase (ABF), and heme-thiolate peroxidase (HTP). Detailed analysis of their catalytic features within the context of brown rot environments allowed us to interpret their roles during ROS-driven wood decomposition. Specifically, we validated the functions of BQR as the driver redox enzyme of Fenton cycles and reconstructed its interactions with the co-occurring HTP or laccase and ABF. Taken together, this research demonstrated that the cell-free expression platform is adequate for synthesizing functional fungal enzymes and provided an alternative route for the rapid characterization of fungal proteins, escalating our understanding of the distinctive biocatalyst system for plant biomass conversion. IMPORTANCE Brown rot fungi are efficient wood decomposers in nature, and their unique degradative systems harbor untapped catalysts pursued by the biorefinery and bioremediation industries. While the use of “omics” platforms has recently uncovered the key “oxidative-hydrolytic” mechanisms that allow these fungi to attack lignocellulose, individual protein characterization is lagging behind due to the lack of a robust method for rapid synthesis of crucial fungal enzymes. This work delves into the studies of biochemical functions of brown rot enzymes using a rapid, cell-free expression platform, which allowed the successful depictions of enzymes’ catalytic features, their interactions with Fenton chemistry, and their roles played during the incipient stage of brown rot when fungus sets off the reactive oxygen species for oxidative degradation. We expect this research could illuminate cell-free protein expression system’s use to fulfill the increasing need for functional studies of fungal enzymes, advancing the discoveries of novel biomass-converting catalysts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts an existing, rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The resulting hourly price data from PLEXOS is provided to technology developers under the ARPA-E FLECCS program to enable technology-specific economic analysis. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming and the FLECCS teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options, new operational parameterizations, and detailed data defining CO2 capture, transportation, and storage systems are being integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities will take advantage of high-performance computing resources to permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative CO2 prices, fossil fuel prices, electricity demand growth, and other electric sector characteristics. Final outcomes will include publicly available hourly grid operation and price data for any U.S. region of interest along with open-access capacity expansion tools for evaluating CCS/NET systems. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

air capture↗
NASA NTRS1989

Frequency domain model for analysis of paralleled, series-output-connected Mapham inverters

The Mapham resonant inverter is characterized as a two-port network driven by a selected periodic voltage. The two-port model is then used to model a pair of Mapham inverters connected in series and employing phasor voltage regulation. It is shown that the model is useful for predicting power output in paralleled inverter units, and for predicting harmonic current output of inverter pairs, using standard power flow techniques. Some examples are compared to data obtained from testing hardware inverters.

Brush, Andrew S.↗
DOE OSTI2024

Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts

Recent years have seen a growing concern about climate change and its impacts. While Earth System Models (ESMs) can be invaluable tools for studying the impacts of climate change, the complex coupling processes encoded in ESMs and the large amounts of data produced by these models, together with the high internal variability of the Earth system, can obscure important source-to-impact relationships. Here, this paper presents a novel and efficient unsupervised data-driven approach for detecting statistically-significant impacts and tracing spatio-temporal source-impact pathways in the climate through a unique combination of ideas from anomaly detection, clustering and Natural Language Processing (NLP). Using as an exemplar the 1991 eruption of Mount Pinatubo in the Philippines, we demonstrate that the proposed approach is capable of detecting known post-eruption impacts/events. We additionally describe a methodology for extracting meaningful sequences of post-eruption impacts/events by using NLP to efficiently mine frequent multivariate cluster evolutions, which can be used to confirm or discover the chain of physical processes between a climate source and its impact(s).

Anomaly detection↗
DOE OSTI2026

Phase change material-to-refrigerant heat exchangers: Experimental validation and uneven melting analysis

Thermal energy storage (TES) using phase change materials (PCMs) enables load shifting and reduces mismatches between the building's thermal demand and the heat pump (HP) system's thermal capacity. While most TES studies have focused on single-phase heat transfer fluids, PCM-to-refrigerant heat exchangers (PRHX), in which the refrigerant undergoes liquid-vapor phase change, remain largely underexplored. Here, to address this gap, this study systematically investigates a shell-and-tube PRHX operating as the condenser in an HP through experiments and simulations. A two-dimensional enthalpy-based finite-volume PRHX model was developed and validated against experimental data, including refrigerant and PCM temperature profiles, PRHX capacity, and system-level performance. Results show three characteristic stages: Stage I, the condenser temperature rapidly increases with PCM in the solid state absorbing sensible heat; Stage II, stable operation during PCM phase change; and Stage III, performance decline once part of the PCM becomes fully melted. Heat transfer analysis revealed that uneven PCM melting along the condenser length was driven primarily by variations in the refrigerant-side heat transfer coefficient, rather than local approach temperature differences. Further study demonstrated that minimizing refrigerant outlet subcooling led to more uniform PCM melting and extended Stages I and II by up to 89%. This paper provides a validated PRHX model, clarifies the mechanisms of uneven PCM melting, and highlights subcooling control as an effective strategy to improve TES performance in HP systems without requiring secondary loops.

Graphite matrix↗
DOE OSTI2020

Reshock analysis for PMMA driven above the threshold for chemical decomposition

Polymethyl methacrylate (PMMA) is a transparent thermoplastic often used in shock compression science. Previous proceedings (AIP Conf. Proc. 845, 131 (2006)) described plate impact experiments in which PMMA was reshocked to pressures of up to ~130 GPa, well above that at which it decomposes on its principal Hugoniot. Because some of the conclusions of the original analysis were surprising, the results were reanalyzed in a later proceeding (ibid. 1426, 771 (2012)). In addition to our own reanalysis of the data, we performed hydrodynamic simulations of the experiments based on a new equation of state for PMMA shocked above its threshold for decomposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗
DOE OSTI2020

Atomic kinetics of laboratory photoionized plasmas relevant to astrophysics. Final report

The major goal of this project was to study the atomic and radiation physics of photoionized plasmas driven by a broadband x-ray flux and its impact on plasma x-ray heating and ionization, emissivity and opacity, and radiation-hydrodynamics. This problem is relevant to the physics of accretion disks surrounding black holes, x-ray binaries, and active galactic nuclei in astrophysics. In addition, it is also important for understanding non-equilibrium laboratory plasmas driven by a distribution of photons. To this end, and motivated by previous and ongoing gas-cell experiments performed by the PI at the Z facility of Sandia National Laboratories, we developed a new experimental platform at the 1MA Zebra pulsed power accelerator of the University of Nevada, Reno based on using a gas jet produced by a supersonic nozzle. The gas jet is turned into a photoionized plasma driven by the x- ray flux from a wire-array z-pinch. Establishing this new experimental platform at Zebra was a major goal of this project. In addition, we have also dedicated effort to continue complementary experiments at the Z facility using the gas-cell photoionized plasma set up with support from the Fundamental Science Program at Z as well as to perform data processing and analysis, and theory and modeling simulations, including electron kinetics and radiation-hydrodynamics. Since we seek to test and establish what physics models are needed to describe photoionized plasma guided by experimental observation, these complementary experimental efforts were central to achieving the goals of this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quantifying the impacts of atmospheric rivers on the surface energy budget of the Arctic based on reanalysis

We present a comprehensive analysis of Arctic surface energy budget (SEB) components during atmospheric river (AR) events identified by integrated water vapor transport exceeding the monthly 85th-percentile climatological threshold in 3-hourly ERA5 reanalysis data from January 1980 to December 2019. Analysis of average anomalies in SEB components, net SEB, and the overall AR contribution to both the seasonal SEB components and net SEB climatology reveals clear seasonality and distinct land–sea–sea ice contrast patterns. Over the sea-ice-covered central Arctic Ocean, ARs significantly impact net SEB, inducing substantial surface warming in fall, winter, and spring. This warming is primarily driven by large anomalies in surface downward longwave radiation (LWD), which average 29–45 W m −2 during the cold seasons. In contrast, AR-related LWD anomalies are smaller in summer, averaging around 15 W m −2 , indicating a reduced impact during this season. Over sub-polar oceans, ARs have the most substantial positive impact on net SEB in cold seasons, mainly attributed to significant positive turbulent heat flux anomalies. AR-related turbulent heat anomalies reduce the upward turbulent flux, contributing up to −11 % relative to its seasonal climatology. In summer, ARs induce negative impacts on net SEB, primarily due to reduced shortwave radiation from increased cloud cover during AR events. Over continents, ARs generate smaller absolute impacts on net SEB because the large LWD anomalies are largely offset by corresponding increases in upward longwave radiation, particularly during cold seasons. Additionally, the seemingly large relative contributions of ARs to the net SEB over land primarily reflects the small magnitude of the climatological net SEB over continents. Greenland, especially western Greenland, exhibits significant downward longwave radiation anomalies associated with ARs, which drive large net SEB anomalies and contribute >54 % to mean SEB and induce amplified surface warming year-round. This holds significance for melt events, particularly during summer. Additionally, results of AR-related SEB impacts strongly depend on detection methods, as restrictive AR detection algorithms that emphasize extreme AR events, with large AR-related anomalies, do not necessarily indicate a large overall contribution to the SEB climatology due to the low occurrence frequency of these events. This study quantifies the role of ARs in the surface energy budget, contributing to our understanding of the Arctic warming and sea ice decline in ongoing Arctic amplification.

Arctic Sea ice change↗
NASA NTRS1989

Frequency domain model for analysis of paralleled, series-output-connected Mapham inverters

The Mapham resonant inverter is characterized as a two-port network driven by a selected periodic voltage. The two-port model is then used to model a pair of Mapham inverters connected in series and employing phasor voltage regulation. It is shown that the model is useful for predicting power output in paralleled inverter units, and for predicting harmonic current output of inverter pairs, using standard power flow techniques. Some sample results are compared to data obtained from testing hardware inverters.

Brush, Andrew S.↗
NASA NTRS2000

Control of Cavity Resonance Using Oscillatory Blowing

The near-zero net mass oscillatory blowing control of a subsonic cavity flow has been experimentally investigated. An actuator was designed and fabricated to provide both steady and oscillatory blowing over a range of blowing amplitudes and forcing frequencies. The blowing was applied just upstream of the cavity front Wall through interchangeable plate configurations These configurations enabled the effects of hole size, hole shape, and blowing angle to be examined. A significant finding is that in terms of the blowing amplitude, the near zero net mass oscillatory blowing is much more effective than steady blowing; momentum coefficients Lip two orders of magnitude smaller than those required for steady blowing are sufficient to accomplish the same control of cavity resonance. The detailed measurements obtained in the experiment include fluctuating pressure data within the cavity wall, and hot-wire measurements of the cavity shear layer. Spectral and wavelet analysis techniques are applied to understand the dynamics and mechanisms of the cavity flow with control. The oscillatory blowing, is effective in enhancing the mixing in the cavity shear layer and thus modifying the feedback loop associated with the cavity resonance. The nonlinear interactions in the cavity flow are no longer driven by the resonant cavity modes but by the forcing associated with the oscillatory blowing. The oscillatory blowing does not suppress the mode switching behavior of the cavity flow, but the amplitude modulation is reduced.

Scarfe, Alison Lamp↗
NASA NTRS2002

Remote Sensing Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properties such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization and band-to-band registration drive sensor platform and spacecraft system architecture and cost, analysis of these criteria is important to optimize system design objectively. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy and geopositional accuracy affect the complexity and cost of calibration methods. However, few studies have quantified the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at the John C. Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated datasets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood.

Zanoni, Vicki↗
NASA NTRS2002

Remote Sensing System Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properites such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization, and band-to-band registration drive sensor platform and spaceraft system architecture and cost, analysis of these criteria is important to objectively optimize system design. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy, and geopositional accuracy affect the complexity and cost of calibration methods. However, there are few studies that quantify the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated data sets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution, and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood. This paper describes the ART and its applicability for rigorously deriving remote sensing data requirements.

Zanoni, Vicki↗