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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A New Framework for Interstellar Medium Emission Line Models: Connecting Multiscale Simulations across Cosmological Volumes

The James Webb Space Telescope (JWST) and Atacama Large Millimeter/submillimeter Array have detected emission lines from the ionized interstellar medium (ISM) in some of the first galaxies at z ≳ 6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context. In order to meet this challenge, we introduce a novel subgrid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from H II regions within each simulated FIRE galaxy are modeled using the semianalytic HIIL INES code. A machine learning approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the H II regions around each simulated stellar particle. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower-resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the IllustrisTNG simulations at z = 6. The resulting predictions for the [O II ], [O III ], and Balmer line luminosities as a function of star formation rate agree well with current observations. Our predictions differ, however, from related works in the literature, which lack detailed subgrid ISM models. This highlights the importance of our multiscale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys.

(ISM:) H II regions↗
DOE OSTI2014

LyMAS: Predicting large-scale Lyα forest statistics from the dark matter density field

We describe Lyα Mass Association Scheme (LyMAS), a method of predicting clustering statistics in the Lyα forest on large scales from moderate-resolution simulations of the dark matter (DM) distribution, with calibration from high-resolution hydrodynamic simulations of smaller volumes. We use the 'Horizon-MareNostrum' simulation, a 50 h {sup –1} Mpc comoving volume evolved with the adaptive mesh hydrodynamic code RAMSES, to compute the conditional probability distribution P(F{sub s} |δ {sub s}) of the transmitted flux F{sub s} , smoothed (one-dimensionally, 1D) over the spectral resolution scale, on the DM density contrast δ {sub s}, smoothed (three-dimensionally, 3D) over a similar scale. In this study we adopt the spectral resolution of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) at z = 2.5, and we find optimal results for a DM smoothing length σ = 0.3 h {sup –1} Mpc (comoving). In its simplest form, LyMAS draws randomly from the hydro-calibrated P(F{sub s} |δ {sub s}) to convert DM skewers into Lyα forest pseudo-spectra, which are then used to compute cross-sightline flux statistics. In extended form, LyMAS exactly reproduces both the 1D power spectrum and one-point flux distribution of the hydro simulation spectra. Applied to the MareNostrum DM field, LyMAS accurately predicts the two-point conditional flux distribution and flux correlation function of the full hydro simulation for transverse sightline separations as small as 1 h {sup –1} Mpc, including redshift-space distortion effects. It is substantially more accurate than a deterministic density-flux mapping ({sup F}luctuating Gunn-Peterson Approximation{sup )}, often used for large-volume simulations of the forest. With the MareNostrum calibration, we apply LyMAS to 1024{sup 3} N-body simulations of a 300 h {sup –1} Mpc and 1.0 h {sup –1} Gpc cube to produce large, publicly available catalogs of mock BOSS spectra that probe a large comoving volume. LyMAS will be a powerful tool for interpreting 3D Lyα forest data, thereby transforming measurements from BOSS and other massive quasar absorption surveys into constraints on dark energy, DM, space geometry, and intergalactic medium physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Pore size distribution and methane equilibrium conditions at Walker Ridge Block 313, northern Gulf of Mexico

Coexistence of three methane phases (liquid (L), gas (G), hydrate (H)) in marine gas hydrate systems may occur according to in-situ pressure, temperature, salinity and pore size. In sediments with salinity close to seawater, a discrete zone of three-phase (3P) equilibrium may occur near the base of the regional hydrate stability zone (RHSZ) due to capillary effects. The existence of a 3P zone influences the location of the bottom-simulating reflection (BSR) and has implications for methane fluxes at the base of the RHSZ. We studied hydrate stability conditions in two wells, WR313-G and WR313-H, at Walker Ridge Block 313 in the northern Gulf of Mexico. We determined pore size distributions (PSD) by constructing a synthetic nuclear magnetic resonance (NMR) relaxation time distribution. Correlations were obtained by non-linear regression on NMR, gamma ray, and bulk density logs from well KC-151 at Keathley Canyon. The correlations enabled construction of relaxation time distributions for WR313-G and WR313-H, which were used to predict PSD through comparison with mercury injection capillary pressure measurements. With the computed PSD, L+H and L+G methane solubility was determined from in-situ pressure and temperature. The intersection of the L+G and L+H curves for various pore sizes allowed calculation of the depth range of the 3P equilibrium zone. As in previous studies at Blake Ridge and Hydrate Ridge, the top of the 3P zone moves upwards with increasing water depth and overlies the bulk 3P equilibrium depth. In clays at Walker Ridge, the predicted thickness of the 3P zone is approximately 35 m, but in coarse sands it is only a few meters due to the difference in absolute pore sizes and the width of the PSD. The thick 3P zone in the clays may explain in part why the BSR is only observed in the sand layers at Walker Ridge, although other factors may influence the presence or absence of a BSR.

Bihani, Abhishek↗
DOE OSTI2020

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

Abstract The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long‐term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature ( Tmax ) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high‐emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH given Tmax with quantile regression models, using functions of temperature for each city in July for three time periods (1990–2005, 2026–2035, and 2071–2080). Quality‐of‐fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile of Tmax increases from 1990–2005 to 2071–2080, while mean RH decreases modestly. Conditional upon a fixed quantile of Tmax , the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixed Tmax , the high quantiles of RH (and thus of HI and dew point) increase from 1990–2005 to 2071–2080 in all four cities. This result suggests that the heat stress of a day at a given Tmax will increase in a warming climate due to the increase of RH.

Yuan, Jiacan↗
DOE OSTI2019

Distribution of solutions of the fastest apparent convergence condition in optimized perturbation theory and its relation to anti-Stokes lines

We discuss fundamental properties of the fastest apparent convergence (FAC) condition which is used as a variational criterion in optimized perturbation theory (OPT). We examine an integral representation of the FAC condition and a distribution of the zeros of the integral in a complex artificial parameter space on the basis of theory of Lefschetz thimbles. We find that the zeros accumulate on a certain line segment known as an anti-Stokes line in the limit K→∞, where K is a truncation order of a perturbation series. This phenomenon gives an underlying mechanism that physical quantities calculated by OPT can be insensitive to the choice of the artificial parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Simplified Space Conditioning in Low-Load Homes: Results from the Fresno, California, Retrofit Unoccupied Test House

In this study, the Building America team, IBACOS, sought to determine cost-effective, energy-efficient solutions for heating and cooling houses. To this end, the team performed field testing in a retrofit unoccupied test house in Fresno, California, to evaluate three air-based heating, ventilation, and air conditioning (HVAC) distribution systems during heating, cooling, and midseason conditions. These included a typical airflow ducted system to the bedrooms, a low airflow ducted system to the bedrooms, and a system with no ductwork to the bedrooms. The relative ability of each of the three systems was assessed with respect to relevant Air Conditioning Contractors of America (ACCA) and ASHRAE standards for house temperature uniformity and stability, respectively. Computational fluid dynamics modeling also was performed and refined based on comparison to field test results to determine the air flow rate into the bedrooms of over-door and bottom-of-door air transfer grilles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

New Whole-House Solutions Case Study: Evaluating Through-Wall Air Transfer Fans, Pittsburgh, Pennsylvania

In this project, Building America team IBACOS performed field testing in a new construction unoccupied test house in Pittsburgh, Pennsylvania, to evaluate heating, ventilating, and air conditioning (HVAC) distribution systems during heating, cooling, and midseason conditions. The team evaluated a market-available through-wall air transfer fan system that provides air to the bedrooms.The relative ability of this system was considered with respect to relevant Air Conditioning Contractors of America and ASHRAE standards for house temperature uniformity and stability.

50% Building America Benchmark↗
DOE OSTI2021

A Bayesian interpretation of inconsistency measures in cosmology

Abstract Measures of inconsistency and tension between datasets have become an essential part of cosmological analyses. It is important to accurately evaluate the significance of such tensions when present. We propose here a Bayesian interpretation of inconsistency measures that can extract information about physical inconsistencies in the presence of data scatter. This new framework is based on the conditional probability distribution of the level of physical inconsistency given the obtained value of the measure. We use the index of inconsistency as a case study to illustrate the new interpretation framework, but this can be generalized to other metrics. Importantly, there are two aspects in the quantification of inconsistency that behave differently as the number of model parameters increases. The first is the probability for the level of physical inconsistency to reach a threshold which drops with the increase of the number of parameters under consideration. The second is the actual level of physical inconsistency which remains rather insensitive to such an increase in parameters. The difference between these two aspects is often overlooked, which leads to a long-standing ambiguity: when a given inconsistency is found between two constraints, its “significance” seems to be lower when considered in a higher-dimensional parameter space. This ambiguity is resolved by the Bayesian interpretation we introduce in this work because the conditional probability distribution includes all the statistical information of the level of physical inconsistency. Finally, we apply the Bayesian interpretation to examine the (in)consistency between Planck versus the Cepheid-based local measurement, the Dark Energy Survey (DES), the Atacama Cosmology Telescope (ACT) and WMAP. We confirm and revisit the degrees of previous physical inconsistencies and show the stability of the new interpretation with respect to the number of cosmological parameters compared to the commonly used n-σ interpretation when applied to cosmological tensions in multi-parameter spaces.

Astronomy & Astrophysics↗
DOE OSTI2025

Plutonium Oxidation State Distribution under WIPP Relevant Conditions (Rev. 2)

The oxidation state of plutonium in the Waste Isolation Pilot Plant (WIPP) environment has been a topic of interest since the initial compliance certification application. Plutonium (Pu) was initially expected to be present primarily as Pu(IV), but since the presence of Pu(III) could not be ruled out, it was also included in performance assessment (PA) calculations. The redox of the other variant actinides, uranium (U) and neptunium (Np), are also coupled to the plutonium redox. This led to a position in performance assessment calculations that is commonly referred to as “50/50”. In which half of the PA realizations assume solubility is dominated by the low oxidation state [U(IV), Np(IV), Pu(III)] and the other half assume solubility is dominated by the higher oxidation state [U(VI), Np(V), Pu(IV)]. Recently, a joint group of WIPP project participants from Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), and the Department of Energy’s Carlsbad Field Office (DOE-CBFO) agreed on a new path forward for the oxidation state model in PA which will decouple the redox active actinides and will instead consider their redox as a function of E h . This will take the current binary approach and turn it into a system with four possible redox states.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Analyzing at-scale distribution grid response to extreme temperatures

Threats against power grids continue to increase, as extreme weather conditions and natural disasters (extreme events) become more frequent. Hence, there is a need for the simulation and modeling of power grids to reflect realistic conditions during extreme events conditions, especially distribution systems. Herein, this paper presents a modeling and simulation platform for electric distribution grids which can estimate overall power demand during extreme weather conditions. The presented platform's efficacy is shown by demonstrating estimation of electrical demand for 1) Electricity Reliability Council of Texas (ERCOT) during winter storm Uri in 2021, and 2) alternative hypothetical scenarios of integrating Distributed Energy Resources (DERs), weatherization, and load electrification. In comparing to the actual demand served by ERCOT during the winter storm Uri of 2021, the proposed platform estimates approximately 34 GW of peak capacity deficit. These numbers are consistent with state-of-the-art prediction results published in the literature. For the case of the future electrification of heating loads, peak capacity of 78 GW (124% increase) is estimated, which would be reduced to 47 GW (38% increase) with the adoption of efficient heating appliances and improved thermal insulation. Integrating distributed solar PV and storage into the grid causes improvement in the local energy utilization and hence reduces the potential unmet energy by 31% and 40%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Cold Plasmaspheric Electrons Affected by ULF Waves in the Inner Magnetosphere: A Van Allen Probes Statistical Study

Six years of Van Allen Probes data are used to investigate cold plasmaspheric electrons affected by ultralow-frequency (ULF) waves in the inner magnetosphere (L<7) including spatial distributions, occurrence conditions, and resonant energy range. Events exhibit a global distribution within L= 4–7 but preferentially occur at L~5.5–7 in the dayside, while there is higher occurrence rate in the duskside than dawnside. They can occur under different geomagnetic activities and solar wind velocities (V S ), but the occurrence rates are increasing with larger AE, |SYMH|, and V S . These features are closely associated with the generation and propagation of ULF waves in Pc4 (45–150 s) and Pc5 (150–600 s) bands. Combined with electron observations from HOPE instrument, the resonant energies inferred from wave power indicate that cold electrons at ones to hundreds of electron volts can be affected by ULF waves. Finally, this study may shed new light on further investigations on the acceleration and transportation of cold plasmaspheric particles that would affect plasmaspheric material release to the Earth's magnetosphere and instabilities for exciting various waves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Strategy for distributed controller defence: Leveraging controller roles and control support groups to maintain or regain control in cyber-adversarial power systems

Distributed controllers play a prominent role in electric power grid operation. The coordinated failure or malfunction of these controllers is a serious threat, where the resulting mechanisms and consequences are not yet well-known and planned against. If certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the system to an unsafe state. The authors present a strategy for distributed controller defence (SDCD) for improved grid tolerance under conditions of distributed controller compromise. The work of the authors’ first formalises the roles that distributed controllers play and their control support groups using controllability analysis techniques. With these formally defined roles and groups, the authors then present defence strategies for maintaining or regaining system control during such an attack. A general control response framework is presented here for the compromise or failure of distributed controllers using the remaining, operational set. The SDCD approach is successfully demonstrated with a 7-bus system and the IEEE 118-bus system for single and coordinated distributed controller compromise; the results indicate that SDCD is able to significantly reduce system stress and mitigate compromise consequences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Distributed Small-Signal Stability Conditions for Inverter-Based Unbalanced Microgrids

The proliferation of inverter-based generation and advanced sensing, controls, and communication infrastructure have facilitated accelerated deployment of microgrids. A coordinated network of microgrids can maintain reliable power delivery to critical facilities during extreme events. Low-inertia offered by the power-electronics–interfaced energy resources, however, can present significant challenges to ensuring stable operation of the microgrids. In this work, distributed small-signal stability conditions for inverter-based microgrids are developed that involve the droop-controller parameters and the network parameters (e.g. line impedances, loads). The distributed closed-form parametric stability conditions derived in this paper can be verified in a computationally efficient manner, facilitating reliable design and operations of networks of microgrids. Dynamic phasor models have been used to capture the effects of electromagnetic transients. Furthermore, numerical results are presented, along with PSCAD simulations, to validate the analytical stability conditions. Effects of design choices, such as the conductor types, and inverter sizes, on the small-signal stability of inverter-based microgrids are investigated to derive useful engineering insights.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Method of adiabatic modes in research of smoothly irregular integrated optical waveguides: zero approximation

We consider the application of the method of adiabatic waveguide modes for calculating the propagation of electromagnetic radiation in three-dimensional (3D) irregular integrated optical waveguides. The method of adiabatic modes takes into account a three-dimensional distribution of quasi-waveguide modes and explicit ('inclined') tangential boundary conditions. The possibilities of the method are demonstrated on the example of numerical research of two major elements of integrated optics: a waveguide of 'horn' type and a thin-film generalised waveguide Luneburg lens by the methods of adiabatic modes and comparative waveguides. (integral optical waveguides)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

60 APPLIED LIFE SCIENCES↗