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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

CHANDRA DEEP OBSERVATION OF XDCP J0044.0-2033, A MASSIVE GALAXY CLUSTER AT z > 1.5

We report the analysis of the Chandra observation of XDCP J0044.0-2033, a massive, distant (z = 1.579) galaxy cluster discovered in the XDCP survey. The total exposure time of 380 ks with Chandra ACIS-S provides the deepest X-ray observation currently achieved on a massive, high-redshift cluster. Extended emission from the intra cluster medium (ICM) is detected at a very high significance level (S/N ∼ 20) on a circular region with a 44'' radius, corresponding to R {sub ext} = 375 kpc at the cluster redshift. We perform an X-ray spectral fit of the ICM emission modeling the spectrum with a single-temperature thermal mekal model. Our analysis provides a global temperature kT=6.7{sub −0.9}{sup +1.3} keV, and a iron abundance Z{sub Fe}=0.41{sub −0.26}{sup +0.29}Z{sub Fe{sub ⊙}} (error bars correspond to 1σ). We fit the background-subtracted surface brightness profile with a single β-model out to 44'', finding a rather flat profile with no hints of a cool core. We derive the deprojected electron density profile and compute the ICM mass within the extraction radius R {sub ext} = 375 kpc to be M {sub ICM}(r < R {sub ext}) = (1.48 ± 0.20) × 10{sup 13} M {sub ☉}. Under the assumption of hydrostatic equilibrium and assuming isothermality within R {sub ext}, the total mass is M{sub 2500}=1.23{sub −0.27}{sup +0.46}×10{sup 14} M{sub ⊙} for R{sub 2500}=240{sub −20}{sup +30} kpc. Extrapolating the profile at radii larger than the extraction radius R {sub ext} we find M{sub 500}=3.2{sub −0.6}{sup +0.9}×10{sup 14} M{sub ⊙} for R{sub 500}=562{sub −37}{sup +50} kpc. This analysis establishes the existence of virialized, massive galaxy clusters at redshift z ∼ 1.6, paving the way to the investigation of the progenitors of the most massive clusters today. Given its mass and the XDCP survey volume, XDCP J0044.0-2033 does not create significant tension with the WMAP-7 ΛCDM cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2021

Analytical models of the strength and ductility of CNT reinforced metal matrix nano composites under elevated temperatures

Carbon nanotubes (CNTs) can greatly enhance the strength of metal matrix composites while resulting in ductility loss. This strength-ductility tradeoff dilemma always confines the development of material design and real-life applications. Here in this work, a temperature dependent strengthening analytical model is proposed for CNT reinforced metal matrix composites which considers three common strengthening mechanisms: Orowan looping effect, thermal expansion mismatch effect, and load bearing effect. The proposed model can predict composite material strength with different volume fractions of CNTs and under different temperatures. Combining the strengthening model with the stress based modified Mohr-Coulomb (sMMC) ductile fracture model, a ductility analytical model is then derived. This ductility analytical model includes the influences of temperature, multi-axial stress loading conditions, as well as the aforementioned three strengthening mechanisms. A good agreement has been achieved between literature published experimental data and analytical predictions for both composite material strength and ductility loss. The proposed two analytical models can provide a straightforward way to study the strength-ductility relationship for CNT reinforced metal matrix composites over a wide range of temperatures and different stress states, and then provide guidance on new material design and processing.

36 MATERIALS SCIENCE↗
NASA NTRS2022

Observation Impact and Information Retention in the Lower Troposphere of the GMAO GEOS Data Assimilation System

In this study, we have assessed the effectiveness of the use of existing observing systems in the lower troposphere in the GEOS hybrid–4DEnVar data assimilation system through a set of observing system experiments. The results show that microwave radiances have a large impact in the Southern Hemisphere and Tropical ocean, but the large influence is mostly observed above 925 hPa and dissipates relatively quickly with longer forecast lead times. Conventional data information holds better in the forecast ranging from the surface to 100 hPa, depending on the field evaluated, in the Northern Hemisphere and lowest model levels in the Tropics. Infrared radiances collectively have much less impact in the lower troposphere. Removing surface observations has small but persistent impact on specific humidity in the upper atmosphere, but small or negligible impact on planetary boundary layer (PBL) height and temperature. The model responses to the incremental analysis update (IAU) forcing are also analyzed. In the IAU assimilation window, the physics responds strongly to the IAU forcing in the lower troposphere, and the changes of physics tendency in the lower troposphere and hydrodynamics tendency in the mid- and upper troposphere are viewed as beneficial to the reduction of state error covariance. In the subsequent forecast, the model tendencies continue to deviate further from the original free forecast with forecast lead times around 300–400 hPa, but physics tendency has showed signs of returning to its original free forecast mechanisms at 1-day forecast in the lower troposphere.

GEOS↗
NASA NTRSDate not supplied

Improved Treatment of Snow Over Ice Sheets in the NASA GISS Climate Model: Towards Ice Sheet–Climate Coupling

Representing the interactions between ice sheets and climate is essential for more accurate prediction of climate change and sea level rise. Ice sheets interact with the overlying atmosphere via the accumulation of snow and its compaction into firn, then ice, as well as the melting of surface snow and ice and the creation of runoff water. Getting an adequate representation of heat transfer, compaction, and melting processes is essential for an accurate representation of snow on land ice in global climate models. We are implementing an improved snow model on top of land ice as part of an effort to couple the NASA GISS climate model with the PISM ice sheet model. The new snow model includes additional layers and processes that are not currently incorporated (e.g., liquid water retention, percolation and refreezing, and snow densification), and mass and energy transfer methods that are consistent with both static ice sheets (with implicit iceberg fluxes) and interactive ice sheets (with explicit dynamics). We are tuning the densification scheme of this snow model with temperature and density data from common FirnCover and SumUp observations at locations in the accumulation zone of Greenland, and we compare the resulting density profiles to other SumUp density profiles in Greenland and Antarctica. We will assess the impact of this new snow model in climate model simulations with a static ice sheet compared with the previous (simpler) 2-layer snow model. Finally, we aim to use the non-coupled simulations as a baseline to assess the impact of dynamic coupling with an interactive ice sheet model.

snow↗
DOE OSTI2018

Impact of Heat Dissipation Profiles on Power Electronics Packaging Design

This work focuses on understanding the thermal impacts of using discrete power devices and limitations of applying conventional thermal design methods. Empirically, a thermal system is designed based on selecting a heat sink with the required thermal resistance from the manufacturer datasheet. This method, as an approximate estimation, has been proven effective as a rough design of Si-based power module. However, wide bandgap (WBG) bare dies bring additional thermal design concerns that have been overlooked. The benefits of WBG devices, such as smaller chip sizes and higher power ratings, on the other hand, lead to thermal concentration issues. Detailed analyses and impacts of the thermal concentration are presented in this paper. Finally, a more accurate model involving Finite Element Analysis (FEA) and Genetic Algorithm optimization is also proposed for a more accurate thermal design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model

We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Effects of subsurface volume scattering on the lunar microwave brightness temperature spectrum

The effects of volumetric scattering on the lunar microwave brightness temperature are examined for a broad range of feasible lunar rock population distributions. Mie-scattering phase functions and the radiative transfer method are utilized. Surveyor and Apollo data relevant to lunar rock size distributions are discussed, and parameters are chosen for nine scattering models which liberally cover the range of studied rock population distributions. Scattering model brightness temperature predictions are analyzed in terms of the lunar disk center emission averaged over a lunation for wavelengths of 3-30 cm. The effects of scattering on the amplitude of disk center brightness temperature variations and resultant deductions of regolith electrical loss are examined. Constraints on the global scale variability of subsurface scatterers imposed by microwave brightness temperature maps are considered.

Keihm, S. J.↗
DOE OSTI2018

A strategy based on thermal flexibility to design triosephosphate isomerase proteins with increased or decreased kinetic stability

Kinetic stability of proteins determines their susceptibility to irreversibly unfold in a time-dependent process, and therefore its half-life. A residue displacement analysis of temperature-induced unfolding molecular dynamics simulations was recently employed to define the thermal flexibility of proteins. This property was found to be correlated with the activation energy barrier (E{sub act}) separating the native from the transition state in the denaturation process. The E{sub act} was determined from the application of a two-state irreversible model to temperature unfolding experiments using differential scanning calorimetry (DSC). The contribution of each residue to the thermal flexibility of proteins is used here to propose multiple mutations in triosephosphate isomerase (TIM) from Trypanosoma brucei (TbTIM) and Trypanosoma cruzi (TcTIM), two parasites closely related by evolution. These two enzymes, taken as model systems, have practically identical structure but large differences in their kinetic stability. We constructed two functional TIM variants with more than twice and less than half the activation energy of their respective wild-type reference structures. The results show that the proposed strategy is able to identify the crucial residues for the kinetic stability in these enzymes. As it occurs with other protein properties reflecting their complex behavior, kinetic stability appears to be the consequence of an extensive network of inter-residue interactions, acting in a concerted manner. The proposed strategy to design variants can be used with other proteins, to increase or decrease their functional half-life.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Predicting the influence of particle size on the glass transition temperature and viscosity of secondary organic material

Abstract Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs–Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter $$\xi $$ ξ describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of $$\alpha $$ α -pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Self-organized Segregation on the Grid

We consider an agent-based model with exponentially distributed waiting times in which two types of agents interact locally over a graph, and based on this interaction and on the value of a common intolerance threshold τ, decide whether to change their types. This is equivalent to a zero-temperature ising model with Glauber dynamics, an asynchronous cellular automaton with extended Moore neighborhoods, or a Schelling model of self-organized segregation in an open system, and has applications in the analysis of social and biological networks, and spin glasses systems. Some rigorous results were recently obtained in the theoretical computer science literature, and this work provides several extensions. We enlarge the intolerance interval leading to the expected formation of large segregated regions of agents of a single type from the known size ϵ>0 to size ≈0.134. Namely, we show that for 0.433<τ<1/2 (and by symmetry 1/2<τ<0.567), the expected size of the largest segregated region containing an arbitrary agent is exponential in the size of the neighborhood. We further extend the interval leading to expected large segregated regions to size ≈0.312 considering “almost segregated” regions, namely regions where the ratio of the number of agents of one type and the number of agents of the other type vanishes quickly as the size of the neighborhood grows. In this case, we show that for 0.344<τ≤0.433 (and by symmetry for 0.567≤τ<0.656) the expected size of the largest almost segregated region containing an arbitrary agent is exponential in the size of the neighborhood. This behavior is reminiscent of supercritical percolation, where small clusters of empty sites can be observed within any sufficiently large region of the occupied percolation cluster. The exponential bounds that we provide also imply that complete segregation, where agents of a single type cover the whole grid, does not occur with high probability for p=1/2 and the range of intolerance considered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗
DOE OSTI2012

Growth of high Bi concentration GaAs{sub 1-x}Bi{sub x} by molecular beam epitaxy

The incorporation of Bi is investigated in the molecular beam epitaxy growth of GaAs{sub 1-x}Bi{sub x}. Bi content increases rapidly as the As{sub 2}:Ga flux ratio is lowered to 0.5 and then saturates for lower flux ratios. Growth under Ga and Bi rich conditions shows that Bi content increases strongly with decreasing temperature. A model is proposed where Bi from a wetting layer incorporates through attachment to Ga-terminated surface sites. The weak Ga-Bi bond can be broken thermally, ejecting Bi back into the wetting layer. Highly crystalline films with up to 22% Bi were grown at temperatures as low as 200 Degree-Sign C.

36 MATERIALS SCIENCE↗
NASA NTRS1989

The US National Transonic Facility, NTF

The construction of the National Transonic Facility was completed in September 1982 and the start-up and checkout of tunnel systems were performed over the next two years. In August 1984, the Operational Readiness Review (ORR) was conducted and the facility was declared operational for final checkout of cryogenic instrumentation and control systems, and for the aerodynamic calibration and testing to commence. Also, the model access system for the cryogenic mode of operation would be placed into operation along with tunnel testing. Since the ORR, a host of operating problems resulting from the cryogenic environment were identified and solved. These range from making mechanical and electrical systems functional to eliminating temperature induced model vibration to coping with the outgassing of moisture from the thermal insulation. Additionally, a series of aerodynamic tests have demonstrated data quality and provided research data on several configurations. Some of the more significant efforts are reviewed since the ORR and the NTF status concerning hardware, instrumentation and process controls systems, operating constraints imposed by the cryogenic environment, and data quality are summarized.

Bruce, Walter E., Jr.↗
NASA NTRS1997

Kinetics and Thermochemistry of the Cl((sup 2)P(sub J)) + C2Cl4 Association Reaction

A laser flash photolysis-resonance fluorescence technique has been employed to study the kinetics of the Cl(sup 2)P(sub j) + C2Cl4 association reaction as a function of temperature (231-390 K) and pressure (3-700 Torr) in nitrogen buffer gas. The reaction is found to be in the falloff regime between third and second order over the range of conditions investigated, although the second-order limit is approached at the highest pressures and lowest temperatures. At temperatures below 300 K, the association reaction is found to be irreversible on the experimental time scale of approximately 20 m-s. The kinetic data at T is less than 300 K have been employed to obtain falloff parameters in a convenient format for atmospheric modeling. At temperatures above 330 K, reversible addition is observed, thus allowing equilibrium constants for C2Cl5 formation and dissociation to be determined. Second- and third-law analyses of the equilibrium data lead to the following thermochemical parameters for the association reaction: Delta-H(298) = -18.1 +/- 1.3 kcal/mol, Delta-H(0) = -17.6 +/- 1.3 kcal/mol, and Delta-S(298) = -27.7 +/- 3.0 cal/mol.K. In conjunction with the well-known heats of formation of Cl((sup 2)P(sub j)) and C2Cl4 the above Delta-H values lead to the following heats of formation for C2Cl5, at 298 and 0 K: Delta-H(f,298) = 8.0 +/- 1.3 kcal/mol and Delta-H(f,0) = 8.1 +/- 1.5 kcal/mol. The kinetic and thermochemical parameters reported above are compared with other reported values, and the significance of reported association rate coefficients for understanding tropospheric chlorine chemistry is discussed.

Nicovich, J. M.↗
NASA NTRS1982

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reacting flows

The use of probability theory to determine the effects of turbulent fluctuations on reaction rates in turbulent combustion systems is briefly reviewed. Results are presented for the effect of species fluctuations in particular. It is found that turbulent fluctuations of species act to reduce the reaction rates, in contrast with the temperature fluctuations previously determined to increase Arrhenius reaction rate constants. For the temperature fluctuations, a criterion is set forth for determining if, in a given region of a turbulent flow field, the temperature can be expected to exhibit ramp like fluctuations. Using the above results, along with results previously obtained, a model is described for testing the effects of turbulent fluctuations of temperature and species on reaction rates in computer programs dealing with turbulent reacting flows. An alternative model which employs three variable probability density functions (temperature and two species) and is currently being formulated is discussed as well.

Chinitz, W.↗
DOE OSTI2016

A variational master equation approach to quantum dynamics with off-diagonal coupling in a sub-Ohmic environment

A master equation approach based on an optimized polaron transformation is adopted for dynamics simulation with simultaneous diagonal and off-diagonal spin-boson coupling. Two types of bath spectral density functions are considered, the Ohmic and the sub-Ohmic. The off-diagonal coupling leads asymptotically to a thermal equilibrium with a nonzero population difference P{sub z}(t → ∞) ≠ 0, which implies localization of the system, and it also plays a role in restraining coherent dynamics for the sub-Ohmic case. Since the new method can extend to the stronger coupling regime, we can investigate the coherent-incoherent transition in the sub-Ohmic environment. Relevant phase diagrams are obtained for different temperatures. It is found that the sub-Ohmic environment allows coherent dynamics at a higher temperature than the Ohmic environment.

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

The Temperature Dependence of the Langmuir Adsorption Model for a Single-Site Metal–Organic Framework

The single-site Langmuir adsorption model, also known as the Langmuir isotherm equation, is one of the simplest possible descriptions of adsorption phenomena, and yet finds widespread applicability across a range of disciplines. In its simplest form, it is deployed to treat adsorption equilibria at constant temperature (i.e., along isotherms); however, at the heart of its derivation is a more general class of models that each incorporate an explicit temperature dependence, subject to assumptions about the spatial/translational degrees of freedom of the adsorbed species. In this work, measurements of the temperature dependence of supercritical adsorption of H 2 on a single-site metal-organic framework (MOF) are presented, and fitted using a range of Langmuir models with distinct treatments of degrees of freedom in the adsorbed phase. Surprisingly, all of the models can be used to adequately represent the measured data, despite yielding significantly different values for binding energy and the temperature dependence of the isosteric enthalpy of adsorption (i.e., the isosteric heat, qst). Furthermore, a critical finding is that the mean-temperature isosteric enthalpy of adsorption remains consistent across all models within experimental error, highlighting its reliability for evaluating adsorption thermodynamics.

08 HYDROGEN↗