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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Nonparametric Method for the Inference of Halo Occupation Distributions

The galaxy–halo connection traces processes by which galaxies form and evolve. The halo occupation distribution (HOD) describes the relationship between galaxies and their host dark matter haloes. Measurements of the galaxy two-point correlation function (2PCF) allow us to extract information about the HODs of observed galaxy samples. Several parametric HOD models have been proposed in the literature, but the choice of parameterization restricts the space of possible HODs. To resolve this issue, we introduce a nonparametric HOD fitting method in which we train an emulator to learn the mappings among the galaxy 2PCF, physical properties used to select galaxy samples, and the HOD, all obtained from simulated past light cones constructed with the Santa Cruz semianalytic model. Implementing this emulator within a likelihood analysis framework, we derive constraints on the HOD of a galaxy sample when provided with a measurement of its 2PCF. Using the emulator to accelerate likelihood evaluations, we test the nonparametric HOD approach on a set of 2PCFs for mock galaxy samples drawn from the TNG100-1 simulation and selected above threshold values of stellar mass and star formation rate. Our framework is able to recover TNG100-1 HODs within 0.2 dex. We use the TNG100-1 mocks to tune the reported uncertainties to estimate those expected in the analysis of observations. Comparing to parametric HOD modelling routines applied to the same mock galaxy samples, our approach consistently infers the HOD with comparable or greater precision and accuracy.

Kennedy, Jacob [Rutgers Univ., Piscataway, NJ (Uni↗
DOE OSTI2016

Some functional limit theorems for compound Cox processes

An improved version of the functional limit theorem is proved establishing weak convergence of random walks generated by compound doubly stochastic Poisson processes (compound Cox processes) to Lévy processes in the Skorokhod space under more realistic moment conditions. As corollaries, theorems are proved on convergence of random walks with jumps having finite variances to Lévy processes with variance-mean mixed normal distributions, in particular, to stable Lévy processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Anaerobic CO2 fixation by the acetogenic bacterium Moorella thermoacetica

Anaerobic bacteria such as Moorella thermoacetica have the capacity of fixing carbon dioxide with carbon monoxide and hydrogen for the production of ethanol, acetic acid, and other useful chemicals. In this study, we evaluated the fixation of CO2 for the production of acetic acid, as a product in its own right but also as precursor for lipid synthesis by oleaginous organisms. We achieved maximum cell optical density of 11.3, acetic acid titer of 31 g/L, and productivity of 0.55 g/L-h at CO mass-transfer rate of 83 mM/h. We also showed electron availability by CO mass transfer limited the process at CO mass transfer rates lower than 30 mM/h. Further enhancement of mass-transfer rate removed such limitations in favor of biological kinetics as main limitation. This work underlines the potential of microbial processes for converting syngas to fuel and chemical products in processes suitable for distributed feedstock utilization. (c) 2013 American Institute of Chemical Engineers AIChE J, 59: 3176-3183, 2013

Hu, P↗
DOE OSTI2021

Gauge-invariant TMD factorization for Drell-Yan hadronic tensor at small $\mathcal{x}$

The Drell-Yan hadronic tensor for electromagnetic (EM) current is calculated in the Sudakov region $s\gg Q^2 \gg q^2_⊥$ with $\frac{1}{Q^2}$ accuracy, first at the tree level and then with the double-log accuracy. It is demonstrated that in the leading order in $N_c$ the higher-twist quark-quark-gluon TMDs reduce to leading-twist TMDs due to QCD equation of motion. The resulting tensor for unpolarized hadrons is EM gauge-invariant and depends on two leading-twist TMDs: $f_1$ responsible for total DY cross section, and Boer-Mulders function $h\frac{⊥}{1}$. The order-of-magnitude estimates of angular distributions for DY process seem to agree with LHC results at corresponding kinematics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Gluon TMD in particle production from low to moderate x

We study the rapidity evolution of gluon transverse momentum dependent distributions appearing in processes of particle production and show how this evolution changes from small to moderate Bjorken x.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Synthesis of boron-carbide aerogels

We present the synthesis of boron carbide aerogels utilizing nano-boron powder and resorcinol–formaldehyde (RF) organic aerogels as precursors. Monolithic aerogels were fabricated from suspensions of boron nanoparticles and RF via an organic sol-gel process, enabling effective distribution of boron in the gel network. The resulting gels underwent supercritical drying, thermal reduction, and subsequent heat treatment to yield boron carbide aerogels with densities ranging from 37 to 55 mg/cm³. By tuning the boron-to-carbon ratio, heat treatment temperature, and dwell time, surface areas up to 53 m²/g were obtained. X-ray diffraction analysis confirmed the formation of the boron carbide phase and detected the presence of residual carbon within the structure.

Materials science↗
DOE OSTI2019

Nitrogen balances and impacts on the algae cultivation-extraction-digestion-cultivation process

Anaerobic digestion of lipid extracted algae is a method for recycling nutrients to a cultivation system. Growth of algae on recycled nitrogen from these systems has been demonstrated. This study focuses on how the initial nitrogen concentration impacts each stage of an integrated cultivation-extraction-digestion-cultivation process; and how the nitrogen is distributed in each step. The entire process was performed at five different initial nitrogen concentrations, ranging from nutrient deplete to excess. Algae production and lipid content were measured to evaluate the impact of initial nitrogen concentration. A thorough nitrogen mass balance for every step of the process was completed. The results show that initial nitrogen concentration had significant impacts on the whole process. The nitrogen recoveries through the nutrient recycle process were all approximately 65% regardless of initial nitrogen concentration. All nitrogen balances closed within experimental error. As a result, the largest losses of nitrogen occurred in the extraction and cultivation steps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Analyzing source apportioned methane in northern California during Discover-AQ-CA using airborne measurements and model simulations

This study analyzes source apportioned methane (CH 4 ) emissions and atmospheric mixing ratios in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH 4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH 4 emissions were ~5.30 Gg day –1 (Gg = 1.0 × 10 9 g) (equating to ~1.90 × 10 3 Gg yr –1 ) for all of California. According to EDGAR, the SFBA and northern SJV region contributes ~30% of total CH 4 emissions from California. Source apportionment analysis during this study shows that CH 4 mixing ratios over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH 4 mixing ratios in northern California (average normalized mean bias (NMB) = –5.2% and linear regression slope = 0.20). The largest negative biases in the model were calculated on days when large amounts of CH 4 were measured over local emission sources and atmospheric CH 4 mixing ratios reached values >2.5 parts per million. Sensitivity emission studies conducted during this research suggest that local emissions of CH 4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH 4 emissions in California.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Metal accumulation in dragonfly nymphs and crayfish as indicators of constructed wetland effectiveness

Constructed wetland effectiveness is often assessed by measuring reductions of contaminant concentrations in influent versus departing effluent, but this can be complicated by fluctuations in contaminant content/chemistry and hydrology. We assessed effectiveness of a constructed wetland at protecting downstream biota from accumulating elevated metal concentrations—particularly copper and zinc in effluents from a nuclear materials processing facility. Contaminants distributed throughout a constructed wetland system and two reference wetlands were assessed using six dragonfly nymph genera (Anax, Erythemis, Libellula, Pachydiplax, Tramea, and Plathemis) as biomonitors. Additionally, the crayfish, Cambarus latimanus, were analyzed from the receiving and two reference streams. Concentrations of Cu, Zn, Pb, Mn, Cr, Cd, and Al were evaluated in 597 dragonfly nymph and 149 crayfish whole-body composite samples. Dragonfly genera varied substantially in metal accumulation and the ability to identify elevated metal levels throughout components of the constructed wetland. Genera more closely associated with bottom sediments tended to accumulate higher levels of metals with Libellula, Pachydiplax, and Erythemis often accumulating highest concentrations and differing most among sites. This, combined with their abundance and broad distributions make the latter two species suitable candidates as biomonitors for constructed wetlands. As expected, dragonfly nymphs accumulated higher metal concentrations in the constructed wetland than reference sites. However, dragonfly nymphs often accumulated as high of metal concentrations downstream as upstream of the water treatment cells. Moreover, crayfish from the receiving stream near the constructed wetland accumulated substantially higher Cu concentrations than from downstream locations or reference streams. Despite reducing metal concentrations at base flow and maintaining regulatory compliance, metal fluxes from the wetland were sufficient to increase accumulation in downstream biota. Future work should evaluate the causes of downstream accumulation as the next step necessary to develop plans to improve the metal sequestering efficiency of the wetland under variable flow regimes.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Titanium and chromium isotopic compositions of calcium-aluminum-rich inclusions: Implications for the sources of isotopic anomalies and the formation of distinct isotopic reservoirs in the early Solar System

As the earliest-dated solids in our Solar System, calcium-aluminum-rich inclusions (CAIs) provide a record of their formation environment near the young Sun and hold clues to the formation of planetary-scale isotopic reservoirs in the solar protoplanetary disk. Although CAIs from several CV, CK, CM, CO, and ordinary chondrites have been analyzed previously for their Ti isotopic compositions, CAIs from just three CV chondrites have been analyzed for their Cr isotopic compositions, and only a handful of CAIs have been measured for both their Ti and Cr isotopic compositions. We report mass-independent Ti and Cr isotopic anomalies in several CAIs from CV and CK chondrites; this is the first report of the Cr isotopic composition of a CAI from a CK chondrite. With this data, we aim to better constrain the compositional range of CAIs in ε 50 Ti versus ε 54 Cr space, thereby facilitating the isotopic characterization of the material inherited by the solar protoplanetary disk and the role of CAIs in the formation of distinct planetary-scale isotopic reservoirs in our early Solar System. The narrow range in isotopic anomalies in CAIs when compared to other early-formed refractory inclusions such as platy hibonite crystals (PLACs) and spinel-hibonite inclusions (SHIBs) suggests that CAIs record the mixing of these precursor materials and the averaging of their larger isotopic anomalies. The isotopic composition of CAIs is therefore likely the result of a combination of factors, including mixing of material inherited from their formation region, heterogeneous carrier phase distribution, and thermal processing in the disk. The ε 50 Ti and ε 54 Cr isotopic compositions of CAIs are not correlated, further demonstrating that these isotopic anomalies have different carrier phases. The Ti and Cr isotopic compositions of CAIs additionally show that CAIs alone cannot be responsible for the compositional difference between the non-carbonaceous chondritic (NC) and carbonaceous chondritic (CC) isotopic reservoirs but nevertheless do play a role in the formation of these large-scale isotopic reservoirs in the early Solar System.

58 GEOSCIENCES↗
DOE OSTI2016

Investigation of the dynamic stress–strain response of compressible polymeric foam using a non-parametric analysis

Dynamic stress–strain response of rigid closed-cell polymeric foams is investigated in this work by subjecting high toughness polyurethane foam specimens to direct impact with different projectile velocities and quantifying their deformation response with high speed stereo-photography together with 3D digital image correlation. The measured transient displacement field developed in the specimens during high stain rate loading is used to calculate the transient axial acceleration field throughout the specimen. A simple mathematical formulation based on conservation of mass is also proposed to determine the local change of density in the specimen during deformation. By obtaining the full-field acceleration and density distributions, the inertia stresses at each point in the specimen are determined through a non-parametric analysis and superimposed on the stress magnitudes measured at specimen ends to obtain the full-field stress distribution. Furthermore, the process outlined above overcomes a major challenge in high strain rate experiments with low impedance polymeric foam specimens, i.e. the delayed equilibrium conditions can be quantified.

42 ENGINEERING↗
DOE OSTI2022

Learning functional priors and posteriors from data and physics

In this work, we develop a new Bayesian framework based on deep neural networks to be able to extrapolate in space-time using historical data and to quantify uncertainties arising from both noisy and gappy data in physical problems. Specifically, the proposed approach has two stages: (1) prior learning and (2) posterior estimation. At the first stage, we employ the physics-informed Generative Adversarial Networks (PI-GAN) to learn a functional prior either from a prescribed function distribution, e.g., Gaussian process, or from historical data and physics. At the second stage, we employ the Hamiltonian Monte Carlo (HMC) method to estimate the posterior in the latent space of PI-GANs. In addition, we use two different approaches to encode the physics: (1) automatic differentiation, used in the physicsinformed neural networks (PINNs) for scenarios with explicitly known partial differential equations (PDEs), and (2) operator regression using the deep operator network (DeepONet) for PDE-agnostic scenarios. We then test the proposed method for (1) meta-learning for one-dimensional regression, and forward/inverse PDE problems (combined with PINNs); (2) PDE-agnostic physical problems (combined with DeepONet), e.g., fractional diffusion as well as saturated stochastic (100-dimensional) flows in heterogeneous porous media; and (3) spatial-temporal regression problems, i.e., inference of a marine riser displacement field using experimental data from the Norwegian Deepwater Programme (NDP). The results demonstrate that the proposed approach can provide accurate predictions as well as uncertainty quantification given very limited scattered and noisy data, since historical data could be available to provide informative priors. In summary, the proposed method is capable of learning flexible functional priors, e.g., both Gaussian and non-Gaussian process, and can be readily extended to big data problems by enabling mini-batch training using stochastic HMC or normalizing flows since the latent space is generally characterized as low dimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Performance of asynchronous optimized Schwarz with one-sided communication

In asynchronous iterative methods on distributed-memory computers, processes update their local solutions using data from other processes without an implicit or explicit global synchronization that corresponds to advancing the global iteration counter. Here in this work, we test the asynchronous optimized Schwarz domain-decomposition iterative method using various one-sided (remote direct memory access) communication schemes with passive target completion. The results show that when one-sided communication is well-supported, the asynchronous version of optimized Schwarz can outperform the synchronous version even for perfectly balanced partitionings of the problem on a supercomputer with uniform nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Sensitive Targeted Quantification of ERK Phosphorylation Dynamics and Stoichiometry in Human Cells without Affinity Enrichment

Mass spectrometry-based targeted quantification is a promising technology for site-specific quantification of posttranslational modifications (PTMs). However, a major constraint of most targeted MS approaches is the limited sensitivity for quantifying low-abundance PTMs, requiring the use of affinity reagents to enrich specific PTMs. Herein, we demonstrate the direct site-specific quantification of ERK phosphorylation isoforms (pT, pY, pTpY) and their relative stoichiometries using a highly sensitive targeted MS approach termed high-pressure, high-resolution separations with intelligent selection and multiplexing (PRISM). PRISM provides effective enrichment of target peptides within a given fraction from complex biological matrix with minimal sample losses, followed by selected reaction monitoring (SRM) quantification. The PRISM-SRM approach enabled direct quantification of ERK phosphorylation in human mammary epithelial cells (HMEC) from as little as 25 µg tryptic peptides from whole cell lysates. Compared to immobilized metal-ion affinity chromatography, PRISM provided >10-fold improvement in signal intensities, presumably due to the better peptide recovery of PRISM for handling small size samples. This approach was applied to quantify ERK phosphorylation dynamics in HMEC treated by different doses of EGF at both the peak activation (10 min) and steady state (2 h). At 10 min, the maximal ERK activation was observed with 0.3 ng/mL dose, whereas the maximal steady state level of ERK activation at 2 h was at 3 ng/ml dose, corresponding to 1200 and 9000 occupied receptors, respectively. At 10 min, the maximally activated pTpY isoform represented ~40% of total ERK, falling to less than 10% at 2 h. The time course and dose-response profiles of individual phosphorylated ERK isoforms indicated that singly phosphorylated pT-ERK never increases significantly, while the increase of pY-ERK paralleled that of pTpY-ERK. This data supports for a processive, rather than distributed, model of ERK phosphorylation. The PRISM-SRM quantification of protein phosphorylation illustrates the potential for simultaneous quantification of multiple PTMs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Aqueous Bromide Discharges from U.S. Coal-Fired Power Plants: Points of Origin, Concentration Ranges, and Effluent Treatment Costs

Bromide discharges from coal-fired power plants have received increased attention from regulatory bodies due to their contribution to the formation of disinfection byproducts (DBPs) in downstream drinking water treatment plants. Here, this paper characterizes the relative contributions of bromide from coal feedstocks and bromine-based mercury control processes, estimates the distribution of bromide concentrations at 85 active coal-fired power plants across the United States (U.S.) with wet flue gas desulfurization units, and estimates the cost of bromide removal from wastewater discharge using year 2020 data. Bromide discharges are estimated at the plant level using a combination of the reported coal rank and composition combusted, estimates of bromide addition in mercury control techniques under multiple halogen addition scenarios, and the estimated flue gas desulfurization (FGD) wastewater flow rate. The median, simulated plant-level estimation of total FGD wastewater flow is 18.3 gallons/min at a bromide concentration of 319 mg/L, equivalent to ~11.6 tonnes/year of bromide discharges to the environment. Next, we evaluated the expected cost of employing the best available technology (BAT) to control bromide discharges in FGD wastewater to prevent contributions to DBP formation. Treatment would need to remove more than 99.8% of bromide to reach the 0.2 mg/L voluntary incentive program (VIP) limit. The total cost of treatment depends on whether disposal is on- or off-site; the average costs for all plants combined come to an average of $110 million ($95.2/kgal) in 2021 U.S. dollars for on-site disposal, or $134 million ($115/kgal) for off-site disposal.

01 COAL, LIGNITE, AND PEAT↗