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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Simulating the biogeochemical and biogeophysical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

To assess the climate impacts of historical and projected land cover change and land use in the Community Climate System Model (CCSM4) we have developed new time series of transient Community Land Model (CLM4) Plant Functional Type (PFT) parameters and wood harvest parameters. The new parameters capture the dynamics of the Coupled Model Inter-comparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005, and for the four Representative Concentration Pathways (RCP) periods from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 with the parameters found the model produced an historical cumulative land use flux of 148.4 PgC from 1850 to 2005, which was in good agreement with other global estimates of around 156 PgC for the same period. The biogeophysical impacts of only applying the transient land cover change parameters in CCSM4 were cooling of the near surface atmospheric over land by -0.1OC, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was overwhelmed at global scales by decreases in snow albedo from black carbon deposition and from high latitude warming. At regional scales however the land cover change forcing persisted resulting in reduced warming, with the biggest impacts in eastern North America. The future CCSM4 RCP simulations showed that the CLM4 transient PFT and wood harvest parameters could be used to represent a wide range of human land cover change and land use scenarios. Furthermore, these simulations ranged from the RCP 4.5 reforestation scenario that was able to draw down 82.6 PgC from the atmosphere, to the RCP 8.5 wide scale deforestation scenario that released 171.6 PgC to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Structure of the glass-forming metallic liquids by ab-initio and classical molecular dynamics, a case study: Quenching the Cu{sub 60}Ti{sub 20}Zr{sub 20} alloy

We consider the question of the amorphization of metallic alloys by melt quenching, as predicted by molecular dynamics simulations with semi-empirical potentials. The parametrization of the potentials is discussed on the example of the ternary Cu-Ti-Zr transition metals alloy, using the ab-initio simulation as a reference. The pair structure in the amorphous state is computed from a potential of the Stillinger-Weber form. The transferability of the parameters during the quench is investigated using two parametrizations: from solid state data, as usual and from a new parametrization on the liquid structure. When the adjustment is made on the pair structure of the liquid, a satisfactory transferability is found between the pure components and their alloys. The liquid structure predicted in this way agrees well with experiment, in contrast with the one obtained using the adjustment on the solid. The final structure, after quenches down to the amorphous state, determined with the new set of parameters is shown to be very close to the ab-initio one, the latter being in excellent agreement with recent X-rays diffraction experiments. The corresponding critical temperature of the glass transition is estimated from the behavior of the heat capacity. Discussion on the consistency between the structures predicted using semi-empirical potentials and ab-initio simulation, and comparison of different experimental data underlines the question of the dependence of the final structure on the thermodynamic path followed to reach the amorphous state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Efficient and Collision-Free Anticipative Cruise Control in Randomly Mixed Strings

Connected intelligent vehicle following can improve safety and efficiency compared to today's road transport, but real traffic in the near future will not provide an ideal setting for its deployment. Unconnected human-driven vehicles will follow variable behavior patterns that combine with differences in dynamic capability to create heterogeneous scenarios. In this paper, connected automated vehicles employ model predictive control for following in traffic that may include both heavy and passenger vehicles at quasi-random positions. Adding further realism, some quasi-randomly mixed vehicles are completely unconnected and equipped with the reactive intelligent driver model using pseudorandom parameters. A mixed-integer quadratic programming formulation adapts the predictive algorithm to diverse powertrain operating point constraints. The preceding vehicle's control input is estimated from velocity and brake light observations and used to probabilistically generate a preview for the ego vehicle. Here, a terminal constraint designed using particle kinematics prevents collisions due to shortsightedness. Results are simulated at various heavy and predictive vehicle concentrations in the presence of packet loss. Linear fuel economy improvements between 1.4% and 1.9% per 10% increase in predictive vehicle penetration rate are shown.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Alfalfa discovery of the nearby gas-rich dwarf galaxy LEO P. V. Neutral gas dynamics and kinematics

We present new H I spectral line imaging of the extremely metal-poor, star-forming dwarf irregular galaxy Leo P. Our H I images probe the global neutral gas properties and the local conditions of the interstellar medium (ISM). The H I morphology is slightly elongated along the optical major axis. We do not find obvious signatures of interaction or infalling gas at large spatial scales. The neutral gas disk shows obvious rotation, although the velocity dispersion is comparable to the rotation velocity. The rotation amplitude is estimated to be V {sub c} =15 ± 5 km s{sup –1}. Within the H I radius probed by these observations, the mass ratio of gas to stars is roughly 2:1, while the ratio of the total mass to the baryonic mass is ≳15:1. We use this information to place Leo P on the baryonic Tully-Fisher relation, testing the baryonic content of cosmic structures in a sparsely populated portion of parameter space that has hitherto been occupied primarily by dwarf spheroidal galaxies. We detect the signature of two temperature components in the neutral ISM of Leo P; the cold and warm components have characteristic velocity widths of 4.2 ± 0.9 km s{sup –1} and 10.1 ± 1.2 km s{sup –1}, corresponding to kinetic temperature upper limits of ∼1100 K and ∼6200 K, respectively. The cold H I component is unresolved at a physical resolution of 200 pc. The highest H I surface densities are observed in close physical proximity to the single H II region. A comparison of the neutral gas properties of Leo P with other extremely metal-deficient (XMD) galaxies reveals that Leo P has the lowest neutral gas mass of any known XMD, and that the dynamical mass of Leo P is more than two orders of magnitude smaller than any known XMD with comparable metallicity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Bottomonium suppression and elliptic flow using Heavy Quarkonium Quantum Dynamics

We introduce a framework called Heavy Quarkonium Quantum Dynamics (HQQD) which can be used to compute the dynamical suppression of heavy quarkonia propagating in the quark-gluon plasma using real-time in-medium quantum evolution. Using HQQD we compute large sets of real-time solutions to the Schrödinger equation using a realistic in-medium complex-valued potential. We sample 2 million quarkonia wave packet trajectories and evolve them through the QGP using HQQD to obtain their survival probabilities. The computation is performed using three different HQQD model parameter sets in order to estimate our systematic uncertainty. After taking into account final state feed down we compare our results to existing experimental data for the suppression and elliptic flow of bottomonium states and find that HQQD predictions are good agreement with available data for R AA as a function of N part and p T collected at \( \sqrt{s_{\mathrm{NN}}} \) = 5 . 02 TeV. In the case of v 2 for the various states, we find that the path-length dependence of ϒ(1 s ) suppression results in quite small v 2 for ϒ(1 s ). Our prediction for the integrated elliptic flow for ϒ(1 s ) in the 10 – 90% centrality class, which now includes an estimate of the systematic error, is v 2 [ϒ(1 s )] = 0 . 003 ± 0 . 0007 ± \( {}_{0.0013}^{0.0006} \) . We also find that, due to their increased suppression, excited bottomonium states have a larger elliptic flow. Based on this observation we make predictions for v 2 [ϒ(2 s )] and v 2 [ϒ(3 s )] as a function of centrality and transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Fluctuation-driven excess noise near superconducting phase transition

We discuss intrinsic mechanisms of nonequilibrium excess noise in superconducting devices and transition edge sensors. In particular, we present an overview of fluctuation-driven contributions to the current noise in the vicinity of the superconducting transition. We argue that sufficiently close to the critical temperature fluctuations of conductivity may become correlated provided that the rate of quasiparticle relaxation is slow as compared to dynamics of superconducting fluctuations. In this regime, fluctuations of conductivity adiabatically follow the fluctuations of the electron distribution. This leads to a substantial enhancement of current noise. Here, the corresponding spectral power density of noise has a Lorentzian shape in the frequency domain while its magnitude scales proportionally to the inelastic relaxation time. It also sensitively depends on the dephasing and Ginzburg–Landau timescales. Further estimates suggest that this mechanism dominates over the conventional temperature fluctuations in the same range of parameters. To describe these effects microscopically, we use the nonequilibrium Keldysh technique in the semiclassical approximation of superconductivity with Boltzmann–Langevin random forces to account for correlations of fluctuations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Morphotype-resolved characterization of microalgal communities in a nutrient recovery process with ARTiMiS flow imaging microscopy

Microalgae-driven nutrient recovery represents a promising technology for phosphorus removal from wastewater while simultaneously generating biomass that can be valorized to offset treatment costs. As full-scale processes come online, system parameters including biomass composition must be carefully monitored to optimize performance and prevent culture crashes. In this study, flow imaging microscopy (FIM) was leveraged to characterize microalgal community composition in near real-time at a full-scale municipal wastewater treatment plant (WWTP) in Wisconsin, USA, and population and morphotype dynamics were examined to identify relationships between water chemistry, biomass composition, and system performance. Two FIM technologies, FlowCam and ARTiMiS, were evaluated as monitoring tools. ARTiMiS provided a more accurate estimate of total system biomass, and estimates derived from particle area as a proxy for biovolume yielded better approximations than particle counts. Deep learning classification models trained on annotated image libraries demonstrated equivalent performance between FlowCam and ARTiMiS, and convolutional neural network (CNN) classifiers proved significantly more accurate when compared to feature table-based dense neural network (DNN) models. Across a two-year study period, Scenedesmus spp. appeared most important for phosphorus removal, and were negatively impacted by elevated temperatures and increase in nitrite/nitrate concentrations. Chlorella and Monoraphidium also played an important role in phosphorus removal. For both Scenedesmus and Chlorella, smaller morphological types were more often associated with better system performance, whereas larger morphotypes likely associated with stress response(s) correlated with poor phosphorus recovery rates. Furthermore, these results demonstrate the potential of FIM as a critical technology for high-resolution characterization of industrial microalgal processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Analytical model of wall forces produced by kink perturbations in tokamaks

Analytical model of the electromagnetic forces produced by kink modes on the tokamak wall [H. R. Strauss et al., Phys. Plasmas 17, 082505 (2010)] is revisited. One of the main conclusions of the mentioned paper is that the largest force occurs at γτ{sub w}≈1, where γ is the kink growth rate and τ{sub w} is the wall penetration time. In the present study, a similar approach is developed under less restrictive assumptions on the plasma and dynamics of perturbation, and a different result is obtained: the force increases with γ and must be maximal at γτ{sub w}→∞. Additionally, the dependence of its amplitude on the plasma parameters is clarified. All distinctions and their reasons are explained in detail. The analysis is performed in the cylindrical model incorporating a resistive wall treated without traditional thin-wall constraints and covering therefore a full range in γτ{sub w}. It is applicable to either locked or rotating modes. Estimates of the sideways force are presented and compared with earlier forecasts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Investigation of partitionless growth of ε -Al 60 Sm 11 phase in Al-10 at% Sm liquid

Recent experiments on devitrification of Al 90 Sm 10 amorphous alloys revealed an unusual polymorphic transformation to a complex cubic crystal structure called the ε-Al 60 Sm 11 phase. Molecular dynamics simulations of the growth of the stoichiometric ε-phase seed in contact with an undercooled Al-10 at% Sm liquid are performed to elucidate the microscopic process of transformation. The as-grown crystal and undercooled liquid possess similar local order around Al atoms whereas a rigid network defined by the Sm sub-lattice develops during the growth. Using a template-cluster alignment method, we define an order parameter to characterize the structural evolution in the system. Estimates of the attachment rate is ${R}_{{\rm{a}}}=8.70\times {10}^{-4}$ Å-2 ns-1 and detachment rate is ${R}_{{\rm{d}}}=3.83\times {10}^{-4}$ Å-2 ns-1 at the interface between ε-Al 60 Sm 11 and Al-10 at% Sm liquid at 800 K.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Gravitational waves from the electroweak phase transition

We study the generation of gravitational waves in the electroweak phase transition. We consider a few extensions of the Standard Model, namely, the addition of scalar singlets, the minimal supersymmetric extension, and the addition of TeV fermions. For each model we consider the complete dynamics of the phase transition. In particular, we estimate the friction force acting on bubble walls, and we take into account the fact that they can propagate either as detonations or as deflagrations preceded by shock fronts, or they can run away. We compute the peak frequency and peak intensity of the gravitational radiation generated by bubble collisions and turbulence. We discuss the detectability by proposed spaceborne detectors. For the models we considered, runaway walls require significant fine tuning of the parameters, and the gravitational wave signal from bubble collisions is generally much weaker than that from turbulence. Although the predicted signal is in most cases rather low for the sensitivity of LISA, models with strongly coupled extra scalars reach this sensitivity for frequencies f ∼ 10{sup −4} Hz, and give intensities as high as h{sup 2}Ω{sub GW} ∼ 10{sup −8}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Quantifying the Diversification of Hepatitis C Virus (HCV) during Primary Infection: Estimates of the In Vivo Mutation Rate

Hepatitis C virus (HCV) is present in the host with multiple variants generated by its error prone RNA-dependent RNA polymerase. Little is known about the initial viral diversification and the viral life cycle processes that influence diversity. We studied the diversification of HCV during acute infection in 17 plasma donors, with frequent sampling early in infection. To analyze these data, we developed a new stochastic model of the HCV life cycle. We found that the accumulation of mutations is surprisingly slow: at 30 days, the viral population on average is still 46% identical to its transmitted viral genome. Fitting the model to the sequence data, we estimate the median in vivo viral mutation rate is 2.561025 mutations per nucleotide per genome replication (range 1.6–6.261025 ), about 5-fold lower than previous estimates. To confirm these results we analyzed the frequency of stop codons (N = 10) among all possible non-sense mutation targets (M = 898,335), and found a mutation rate of 2.8–3.261025 , consistent with the estimate from the dynamical model. The slow accumulation of mutations is consistent with slow turnover of infected cells and replication complexes within infected cells. This slow turnover is also inferred from the viral load kinetics. Our estimated mutation rate, which is similar to that of other RNA viruses (e.g., HIV and influenza), is also compatible with the accumulation of substitutions seen in HCV at the population level. Our model identifies the relevant processes (long-lived cells and slow turnover of replication complexes) and parameters involved in determining the rate of HCV diversification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China

Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as high as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.

Situ, S.↗
DOE OSTI2012

Torsion cosmology of Poincaré gauge theory and the constraints of its parameters via SNeIa data

Poincarè gauge theory (PGT) is an alternative gravity theory, which brings the gravity into the gauge-theoretic framework, where the Lagrangian includes both quadratic torsion and curvature terms. Recently, the cosmological models with torsion based on this theory, which explained the cosmic acceleration in a new way, have received much attention. Among these PGT cosmological models, the one with only even parity dynamical modes-SNY model, for its realistic meaning, is very attractive. In this paper, we first analyze the past-time cosmic evolution of SNY model analytically. And based on these results we fit this model to the most comprehensive SNeIa data (Union 2) and thus find the best-fit values of model parameters and initial conditions, whose related χ{sup 2} value is consistent with the one from ΛCMD at the 1σ level. Also by the χ{sup 2} estimate, we provide certain constraints on these parameters. Using these best-fit values for the Union 2 SNeIa dataset, we are able to predict the evolution of our real universe in late time. From this prediction, we know that the fate of our universe is that it would expand forever, slowly asymptotically to a halt, which is in accordance with the earlier works.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

ON THE FORMATION OF HOT JUPITERS IN STELLAR BINARIES

We study the production of hot Jupiters (HJs) in stellar binaries. We show that the 'eccentric Kozai-Lidov' (EKL) mechanism can play a key role in the dynamical evolution of a star-planet-star triple system. We run a large set of Monte Carlo simulations including the secular evolution of the orbits, general relativistic precession, and tides, and we determine the semimajor axis, eccentricity, inclination, and spin-orbit angle distributions of the HJs that are produced. We explore the effect of different tidal friction parameters on the results. We find that the efficiency of forming HJs when taking the EKL mechanism into account is higher then previously estimated. Accounting for the frequency of stellar binaries, we find that this production mechanism can account for about 30% of the observed HJ population. Current observations of spin-orbit angles are consistent with this mechanism producing {approx}30% of all HJs, and up to 100% of the misaligned systems. Based on the properties of binaries without an HJ in our simulations, we predict the existence of many Jupiter-like planets with moderately eccentric and inclined orbits and semimajor axes of several AU.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Causal network inference using biochemical kinetics

Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. Results: We present a general framework for network inference and dynamical prediction using time course data that is rooted in nonlinear biochemical kinetics. This is achieved by considering a dynamical system based on a chemical reaction graph with associated kinetic parameters. Both the graph and kinetic parameters are treated as unknown; inference is carried out within a Bayesian framework. This allows prediction of dynamical behavior even when the underlying reaction graph itself is unknown or uncertain. Results, based on (i) data simulated from a mechanistic model of mitogen-activated protein kinase signaling and (ii) phosphoproteomic data from cancer cell lines, demonstrate that non-linear formulations can yield gains in causal network inference and permit dynamical prediction and uncertainty quantification in the challenging setting where the reaction graph is unknown. Availability and implementation: MATLAB R2014a software is available to download from warwick.ac.uk/chrisoates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Intra-beam scattering and its application to ERL

Treatment of Coulomb collisions within the beam requires consideration of both large and small angle scattering. Such collisions lead to the Touschek effect and Intrabeam Scattering (IBS). The Touschek effect refers to particle loss as a result of a single collision, where only transfer from the transverse direction into longitudinal plays a role. It is important to consider this effect for ERL design to have an appropriate choice of collimation system. The IBS is a diffusion process which leads to changes of beam distribution but does not necessarily result in a beam loss. Evaluation of IBS in ERLs, where beam distribution is non-Gaussian, requires special treatment. Here we describe the IBS and Touschek effects with application to ERLs. In circular accelerators both the Touschek effect and IBS were found important. The generalized formulas for Touschek calculations are available and are already being used in advanced tracking simulations of several ERL-based projects. The IBS (which is diffusion due to multiple Coulomb scattering) is not expected to cause any significant effect on beam distribution in ERLs, unless one considers very long transport of high-brightness beams at low energies. Both large and small-angle Coulomb scattering can contribute to halo formation in future ERLs with high-brightness beams, as follows from simple order-of-magnitude estimates. In this report, a test comparison between 'local' and 'sliced' IBS models within the BET ACOOL code was presented for an illustrative ERL distribution. We also presented accumulated current loss distribution due to Touschek scattering for design parameters of ERL proposed for the eRHIC project, as well as scaling for multi-pass ERLs.

43 PARTICLE ACCELERATORS↗