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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Monsoon Depression Amplification by Horizontal Shear and Humidity Gradients: A Shallow Water Perspective

Transient, synoptic-scale vortices produce a large fraction of total rainfall in most monsoon regions and are often associated with extreme precipitation. However, the mechanism of their amplification remains a topic of active research. For monsoon depressions, which are the most prominent synoptic-scale vortex in the Asian–Australian monsoon, recent work has suggested that meridional gradients in zonal wind in the vortex environment may produce growth through barotropic instability, while meridional gradients in environmental humidity have also been proposed to cause amplification through coupling with precipitating convection. Here, a two-dimensional shallow water model on a sphere with parameterized precipitation is used to examine the relative role played by these two environmental gradients. By systematically varying the meridional moisture gradient and meridional wind shear for both weak, quasi-linear waves and finite-amplitude isolated vortices, we show that rotational winds in the initial vortex are amplified most strongly by meridional shear of the environmental zonal wind, while vortex precipitation rates are most sensitive to environmental moisture gradients. The growth rate in the presence of both gradients is less than the sum of growth rates in the presence of isolated gradients, as the phase relation between moisture and vorticity anomalies becomes distorted with increasing shear. In conclusion, these results suggest that background meridional gradients in both zonal wind and environmental humidity can contribute to the amplification of vortices to monsoon depression strength, but with some degree of decoupling of the dry rotational flow and the moist convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chemical templates of the Central Molecular Zone

Context . The Central Molecular Zone (CMZ) of the Milky Way exhibits extreme conditions, including high gas densities, elevated temperatures, enhanced cosmic-ray ionization rates, and large-scale dynamics. This makes it a perfect laboratory for astrochemical studies. With large-scale molecular surveys revealing increasing chemical and physical complexity in the CMZ, it is essential to develop robust methods to decode the chemical information embedded in this extreme region. Aims . A key step to interpreting the molecular richness found in the CMZ is building chemical templates tailored to its diverse conditions. In particular, understanding how CMZ environments affect shock and protostellar chemistry is crucial. The combined impact of high ionization, elevated temperatures, and dense gas remains insufficiently explored for observable tracers. Methods . For this study, we utilized UCLCHEM , a gas-grain time-dependent chemical model, to link physical conditions with their corresponding molecular signatures and identify key tracers of temperature, density, ionization, and shock activity. To achieve this, we ran a grid of models of shocks and protostellar objects representative of typical CMZ conditions, focusing on 24 species, including complex organic molecules. Results . Shocked and protostellar environments show distinct evolutionary timescales (≲10 4 vs. ≳10 4 years); 300 K emerges as a key temperature threshold for chemical differentiation. We find that cosmic-ray ionization and temperature are the main drivers of chemical trends. HCO + , H 2 CO, and CH 3 SH trace ionization, while HCO, HCO + , CH 3 SH, CH 3 NCO, and HCOOCH 3 show consistent abundance contrasts between shocks and protostellar regions over similar temperature ranges. Conclusions . We characterized the behavior of 24 species in protostellar and shock-related environments. While our models underpredict some complex organics in shocks, they reproduce observed trends for most species, supporting scenarios involving a need for recurring shocks in Galactic Center clouds and enhanced ionization toward Sgr B2(N2). Future work should assess the role of shock recurrence and metallicity in shaping chemistry.

Galaxy: center↗
DOE OSTI2023

Challenges resulting from urban density and climate change for the EU energy transition

Dense urban morphologies further amplify extreme climate events due to the urban heat island phenomenon, rendering cities more vulnerable to extreme climate events. Here we develop a modelling framework using multi-scale climate and energy system models to assess the compound impact of future climate variations and urban densification on renewable energy integration for 18 European cities. We observe a marked change in wind speed and temperature due to the aforementioned compound impact, resulting in a notable increase in both peak and annual energy demand. Therefore, an additional cost of 20–60% will be needed during the energy transition (without technology innovation in building) to guarantee climate resilience. Failure to consider extreme climate events will lower power supply reliability by up to 30%. Here, energy infrastructure in dense urban areas of southern Europe is more vulnerable to the compound impact, necessitating flexibility improvements at the design phase when improving renewable penetration levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Simulating and Evaluating Atmospheric River-Induced Precipitation Extremes Along the U.S. Pacific Coast: Case Studies From 1980–2017

Atmospheric rivers (ARs) are responsible for a majority of extreme precipitation and floodevents along the U.S. West Coast. To better understand the present-day characteristics of AR-relatedprecipitation extremes, a selection of nine most intense historical AR events during 1980–2017 is simulatedusing a dynamical downscaling modeling framework based on the Weather Research and ForecastingModel. We find that the chosen framework and Weather Research and Forecasting Model configurationreproduces both large-scale atmospheric features—including parent synoptic-scale cyclones—as well asthe filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracyof simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations,improves notably with increasing model resolution, with improvements as large as 40–60% for fine scale(3 km) relative to coarse-scale (27 km) simulations. A separate set of simulations using smoothedtopography suggests that much of these gains stem from the improved representation of complex terrain.Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstratethat only the highest-resolution simulations resolve important fine-scale features—such as localizedorographically forced vertical motion and powerful near hurricane-force boundary layer winds. Given thedemonstrated ability of a targeted dynamical downscaling framework to capture both local extremeprecipitation and key fine-scale characteristics of the most intense ARs in the historical record, we arguethat such a configuration may be highly conducive to understanding AR-related extremes and associatedchanges in a warming climate

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modular hybrid modeling to increase efficiency, explore structural uncertainty, and allow multidimensional complexity scaling in land surface models

Land surface models (LSMs) are indispensable tools for predicting hydrologic extremes, as well as a particularly uncertain component of Earth system models that has stubbornly resisted the convergence in projections over several successive generations of model intercomparisons. This uncertainty in LSMs is poorly quantified and poorly attributed to specific processes, which has hampered efforts to focus research in reducing uncertainty. This has resulted from sparse sampling of the possible uncertainty space—which is high-dimensional and has contributions from parametric, structural, initial, and boundary condition uncertainties—as an artifact of CMIP-type ensembles of opportunity and limitations inherent in observational benchmarks. A new approach is needed to understand and reduce this uncertainty, based around individual LSMs that can represent the breadth of assumptions represented in current CMIP-type efforts, while at the same time exploring that uncertainty in a systematic way, confronting multiple types of observations, and where justified, replacing process representations with ML-driven emulators. We propose an approach of modular hybrid modeling to address these challenges.

58 GEOSCIENCES↗
DOE OSTI2026

Record-Breaking Atmospheric River Drives April 2024 Extreme Precipitation in the United Arab Emirates and the Surrounding Gulf Region

In mid-April 2024, the United Arab Emirates (UAE) and the surrounding Gulf region experienced unprecedented rainfall and catastrophic flooding, causing widespread damage, loss of life, and significant economic costs. During the 3-day period from 15 to 17 April, rainfall in the UAE exceeded 100 mm in the hardest-hit areas, with more than 170% of the typical annual precipitation recorded in just 72 h. The event was associated with exceptionally strong integrated water vapor transport (IVT), driven by a persistent low pressure system and a focused corridor of moisture transport. This environment, combined with favorable dynamical and convective conditions, triggered intense thunderstorms and widespread flooding. This article examines the role of an atmospheric river (AR) in the April 2024 extreme precipitation event, emphasizing the contribution of extreme IVT to preconditioning and amplifying the heavy rainfall. While this event has previously been described primarily in terms of a mesoscale convective system (MCS) and potential vorticity (PV) streamers, here we document and illustrate its close relationship to a record-breaking moisture transport corridor. This AR-based perspective highlights how large-scale moisture-transport frameworks can complement synoptic and mesoscale analyses in understanding extreme rainfall in arid and semiarid regions such as the UAE and the Gulf. The event serves as a stark example of the vulnerabilities faced by arid regions, where atmospheric conditions conducive to extreme flooding may become more frequent in the future.

Massoud, Elias [ORNL] (ORCID:0000000217725361)↗
DOE OSTI2021

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design, optimization, and validation of a triply periodic minimal surface based heat exchanger for extreme temperature applications

Heat exchanger (HX) innovation offers potential for significant improvements in energy efficiency for a host of applications including but not limited to aviation and power generation cycles. Triply Periodic Minimal Surfaces (TPMS) have received significant attention in recent years due to their incredibly high surface area density, which makes them very attractive from a heat transfer point of view. Recent efforts have largely focused on thermal-hydraulic characterization of the many available TPMS and the testing of small-scale HX prototypes. However, practical implementation remains largely unexplored, partially due to the extreme computational cost associated with accurately simulating these complex structures. In this work, we present the design, simulation, and optimization of a TPMS-HX for high temperature (900 °C) and pressure (25 MPa) applications. Detailed analysis of HX sub-sections is conducted to define the smallest repeatable section which may be used to characterize the thermal-hydraulic performance of the entire HX, enabling rapid design and iteration with significantly reduced computational cost. Compared to preliminary results for a water-to-water experiment, calibrated heat transfer and pressure drop predictions were within ±5 % and ±10 %, respectively. Optimization results show a 10x increase in volumetric power density over the initial design, which is verified against a parametric exhaustive search of the HX design space. Furthermore, it was found that reducing the unit cell hydraulic diameter cell plays the largest role in increasing heat transfer, increasing the surface area density and enabling a more compact and efficient HX.

42 ENGINEERING↗
DOE OSTI2023

High-density integrated delay line using extreme skin-depth subwavelength grating waveguides

Optical delay lines control the flow of light in time, introducing phase and group delays for engineering interferences and ultrashort pulses. Photonic integration of such optical delay lines is essential for chip-scale lightwave signal processing and pulse control. However, typical photonic delay lines based on long spiral waveguides require extensively large chip footprints, ranging from mm 2 to cm 2 scales. Here we present a scalable, high-density integrated delay line using a skin-depth engineered subwavelength grating waveguide, i.e., an extreme skin-depth (eskid) waveguide. The eskid waveguide suppresses the crosstalk between closely spaced waveguides, significantly saving the chip footprint area. Our eskid-based photonic delay line is easily scalable by increasing the number of turns and should improve the photonic chip integration density.

Ahmed, Ishtiaque↗
DOE OSTI2024

Streamflow in the United States: Characteristics, trends, regime shifts, and extremes

Long-term streamflow observations contain essential information for understanding hydrological changes and managing water resources. A continental-scale dataset or analysis of temporal streamflow change is still lacking across hydrologic gauges in the Conterminous United States (CONUS). Here, we compiled 70 years of streamflow records from 1951 to 2021 at ~ 8000 hydrologic stations across the CONUS and characterized temporal trends, regime shifts, and extreme events using a Bayesian time series analysis algorithm. We found that the occurrences of sudden streamflow changes (e.g., regime shifts and extreme events) have been increasing with time across the CONUS. In addition, we derived 181 streamflow indicators that are valuable for hydrological and biological applications, such as the duration and frequency of high or low streamflow events. The Mississippi River Basin, especially the middle and lower parts, was a hot spot of high-frequency high-flow events. Overall, we anticipate the dataset generated here offers valuable information for understanding and quantifying changes in water resources across the CONUS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bridging nuclear physics across energy scales: from neutrinoless double-beta decay to high-energy heavy-ion collisions

This paper exemplifies how connecting methods at disparate energy scales can illuminate fundamental questions. By demonstrating that nuclear wave function properties governing rare decay processes also influence collective behavior at extreme temperatures and densities, the authors have opened a new pathway for constraining physics beyond the Standard Model. With multiple ton-scale 0νββ experiments under construction, any method reducing NME uncertainties will directly impact our ability to interpret discoveries or constrain neutrino properties. The general principle—that collective phenomena in high-energy collisions can illuminate subtle features of many-body correlations in the colliding nuclei—may find applications across nuclear and particle physics. Furthermore, this intersection of nuclear structure theory, heavy-ion physics, and fundamental symmetry tests represents fertile ground for future discoveries in modern physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Novel Signatures Beyond the Standard Model: From Extreme Environments to Precision Measurements

Most of our universe is dark. It is dark literally—visible matter makes up only 5% of the energy density—and conceptually, as many outstanding questions remain unsolved. The discovery of particle dark matter would shed light on our dark universe and throw open a window on the highest energy scales. This research made progress toward dark matter and new particle searches in three ways. Extreme compact objects, such as black holes, neutron stars, and stellar cores, can parametrically increase the production rates of feebly interacting particles and yield observable signatures. Specifically, a process known as superradiance leads to exponential growth of the number of ultralight particles gravitationally bound to rotating black holes, and turns astrophysical black holes into particle detectors. This research broadened the scope of applicability of superradiance studies to particles with a wide range of interactions and masses, predicting multi messenger signals. When ultralight particles are produced as dark matter in the early universe, they can be detected directly in laboratory experiments. However, these feebly interacting particles lead to small signals that are inevitably difficult to tease out from backgrounds; their detection requires the theoretical development of unique signatures that can be searched for in low-noise experiments. Some dark matter particles could be detectable with thin film metamaterials combined with low noise single-photon detectors. This research develop the theoretical framework and supported experimental efforts for ambitious searches for a wider class of ultralight particles. Overall, the outcome of this theoretical particle physics program developed novel signatures of new dark matter particles, and thereby expanded the particle parameter space which can be explored with astrophysical observations and precision experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed

Integrated forecasting systems for precipitation, streamflow, and floodplain inundation are of critical importance in mitigating the impacts of destructive floods caused by extreme weather events. However, the skills of streamflow and floodplain inundation forecasts derived from various Quantitative Precipitation Forecasts (QPF) require a greater level of understanding. In this paper, a set of QPF developed by the National Weather Service (NWS) were used to drive a flood modeling system obtained utilizing offline coupling of a physics-based distributed hydrological model, the Distributed Hydrology Soil and Vegetation Model (DHSVM), and a hydrodynamic model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). This flood modeling system was used to produce forecasts of streamflow and floodplain inundation maps during three major flood events in the Brays Bayou Watershed (Houston, Texas, USA) for a range of QPF durations (6–72 h). Then, to investigate the effects of increasing QPF durations on the forecasts, the forecasting skills of precipitation, streamflow, and floodplain inundation were quantified. The results show that: 1) QPF skills for more intense and sustained events such as hurricanes and tropical storms are higher than for shorter, less intense events; 2) while QPF and streamflow forecasting skills decrease as QPF durations increase, inundation forecasts under longer QPF durations (24 or 72 h) show higher skills; 3) extending the maximum QPF duration in operational hydrologic modeling from 24 h (under normal circumstances) to 72 h (for extreme events) may increase the skills of long lead time forecasts for large-scale events like Hurricane Harvey.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mesoscale Convective Systems Modulated by Convectively Coupled Equatorial Waves

Mesoscale convective systems (MCSs) produce over 50% of tropical precipitation and account for the majority of extreme rainfall and flooding events. MCSs are considered the building blocks of larger-scale convectively coupled equatorial waves (CCEWs). While CCEWs can provide favorable environments for convection, how CCEWs can systematically impact organized convection and thereby MCS characteristics is less clear. We examine this question by analyzing a global MCS tracking data set. During the active phase of CCEWs, MCS frequency increases and MCSs rain harder, produce more lifetime total rain, and grow larger in size. The probability of extreme MCSs also elevates. These changes are most pronounced when MCSs are associated with Kelvin waves and tropical depression-type waves while less so with the Madden-Julian Oscillation. Furthermore, these results can be benchmarks to improve model representation of MCS interactions with large-scale circulations and can be leveraged for operational forecasts of high-impact MCSs at extended lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Living on the edge: A continental-scale assessment of forest vulnerability to drought

Globally, forests are facing an increasing risk of mass tree mortality events associated with extreme droughts and higher temperatures. Hydraulic dysfunction is considered a key mechanism of drought-triggered dieback. By leveraging the climate breadth of the Australian landscape and a national network of research sites (Terrestrial Ecosystem Research Network), we conducted a continental-scale study of physiological and hydraulic traits of 33 native tree species from contrasting environments to disentangle the complexities of plant response to drought across communities. Here, we found strong relationships between key plant hydraulic traits and site aridity. Leaf turgor loss point and xylem embolism resistance were correlated with minimum water potential experienced by each species. Across the data set, there was a strong coordination between hydraulic traits, including those linked to hydraulic safety, stomatal regulation and the cost of carbon investment into woody tissue. These results illustrate that aridity has acted as a strong selective pressure, shaping hydraulic traits of tree species across the Australian landscape. Hydraulic safety margins were constrained across sites, with species from wetter sites tending to have smaller safety margin compared with species at drier sites, suggesting trees are operating close to their hydraulic thresholds and forest biomes across the spectrum may be susceptible to shifts in climate that result in the intensification of drought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Interfacial Void Formation and Self-Healing in Oxide Scales on Al-containing High-Entropy Alloy

The exceptional high-temperature oxidation resistance of Al-containing high-entropy alloys (HEAs) is often attributed to the formation of a protective α-Al 2 O 3 scale. However, the dynamic, atomic-scale mechanisms governing the stability of this scale—including interfacial void formation and the often-postulated but rarely visualized “self-healing” capacity—remain poorly understood. Herein, we reveal the complex evolution of the triple-layer oxide scale on an Al 10 CoCrFeNi HEA through combined electron microscopy and diffraction study. We show that interfacial voids are an inherent consequence of the scaling process, originating from two distinct mechanisms: the Kirkendall effect at the interface between the γ-Al 2 O 3 /α-Al 2 O 3 and alloy driven by cationic diffusion imbalance and volumetric contraction due to phase transformations at the spinel/Cr 2 O 3 interface. Crucially, we provide microstructural evidence consistent with an intrinsic self-healing response. This process is driven by coupled inward diffusion of oxygen and outward diffusion of metal cations, leading to the in-situ formation of transient θ-Al 2 O 3 and spinel phases that partially fill and seal the voids. Here, these results provide atomic-scale insights into the phase evolution, defect formation, and self-repair of oxide scales in HEAs—highlighting pathways to enhance their oxidation resistance in extreme environments.

High-entropy alloy↗
DOE OSTI2022

Thermal fluctuations in the dissipation range of homogeneous isotropic turbulence

In this work, using fluctuating hydrodynamics we investigate the effect of thermal fluctuations in the dissipation range of homogeneous isotropic turbulence. Simulations confirm theoretical predictions that the energy spectrum is dominated by these fluctuations at length scales comparable to the Kolmogorov length. We also find that the extreme intermittency in the far-dissipation range predicted by Kraichnan is replaced by Gaussian thermal equipartition.

42 ENGINEERING↗