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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Improving initialization and evolution accuracy of cosmological neutrino simulations

Neutrino mass constraints are a primary focus of current and future large-scale structure (LSS) surveys. Non-linear LSS models rely heavily on cosmological simulations — the impact of massive neutrinos should therefore be included in these simulations in a realistic, computationally tractable, and controlled manner. Here, a recent proposal to reduce the related computational cost employs a symmetric neutrino momentum sampling strategy in the initial conditions. We implement a modified version of this strategy into the Hardware/Hybrid Accelerated Cosmology Code (HACC) and perform convergence tests on its internal parameters. We illustrate that this method can impart Script $\mathcal{O}$(1%) numerical artifacts on the total matter field on small scales, similar to previous findings, and present a method to remove these artifacts using Fourier-space filtering of the neutrino density field. Moreover, we show that the converged neutrino power spectrum does not follow linear theory predictions on relatively large scales at early times at the 15% level, prompting a more careful study of systematics in particle-based neutrino simulations. We also present an improved method for backscaling linear transfer functions for initial conditions in massive neutrino cosmologies that is based on achieving the same relative neutrino growth as computed with Boltzmann solvers. Our self-consistent backscaling method yields sub-percent accuracy in the total matter growth function. Comparisons for the non-linear power spectrum with the Mira-Titan emulator at a neutrino mass of m ν = 0.15 eV are in very good agreement with the expected level of errors in the emulator and in the direct N-body simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Microstructural basis for improved corrosion resistance of laser surface processed AZ31 Mg alloy

Despite their excellent strength to weight ratio, wider use of Mg alloys for light weighting applications is limited by their poor corrosion resistance, especially in chloride ion-containing environments. The present study shows improved corrosion resistance imparted by laser surface processing (LSP) of a commercial AZ31 (Mg-3Al-1Zn) alloy. Nanosecond laser processing at three different power settings was carried out on the surface of a 1 mm thick rolled AZ31 sheet. Corrosion testing based on ASTM B117 method and several other electrochemical tests indicates substantial enhancement of corrosion resistance in LSP-treated AZ31. The underlying reason behind improved corrosion resistance of LSP-AZ31 surface has been identified using a variety of characterization tools (SEM, TEM, XPS). Formation of a ~0.5 µm thick mixed metal (Mg, Al) oxide surface film together with refinement in the size and number density of Al-Mn intermetallic particles appear to be playing a major role towards improved corrosion resistance after LSP treatment of AZ31 alloy.

Jana, Saumyadeep↗
NASA NTRS1994

Planetary Rings

Just over two decades ago, Jim Pollack made a critical contribution to our understanding of planetary ring particle properties, and resolved a major apparent paradox between radar reflection and radio emission observations. At the time, particle properties were about all there were to study about planetary rings, and the fundamental questions were, why is Saturn the only planet with rings, how big are the particles, and what are they made of? Since then, we have received an avalanche of observations of planetary ring systems, both from spacecraft and from Earth. Meanwhile, we have seen steady progress in our understanding of the myriad ways in which gravity, fluid and statistical mechanics, and electromagnetism can combine to shape the distribution of the submicron-to-several-meter size particles which comprise ring systems into the complex webs of structure that we now know them to display. Insights gained from studies of these giant dynamical analogs have carried over into improved understanding of the formation of the planets themselves from particle disks, a subject very close to Jim's heart. The now-complete reconnaissance of the gas giant planets by spacecraft has revealed that ring systems are invariably found in association with families of regular satellites, and there is ark emerging perspective that they are not only physically but causally linked. There is also mounting evidence that many features or aspects of all planetary ring systems, if not the ring systems themselves, are considerably younger than the solar system

Cuzzi, Jeffrey N.↗
NASA NTRSDate not supplied

Development of Flexible Energy Storage Device for Wearable Electronics using All-organic Composites

As the demands and applications of wearable electronics increase, the need of power supply for wearable electronics becomes the critical issue. Both batteries and capacitors can be used as power supplier. In terms of energy storage device, capacitors have many advantages over the batteries, but have a lower energy storage density. To improve the energy density, composites, in which inorganic particles are embedded in a polymer matrix, have been identified as a promising approach to create the dielectrics with a higher energy storage density. The physics behind the composite approach is that the inorganics have a higher dielectric constant and polymers can stand with a higher electric field so that the composites can exhibit a relative dielectric constant and stand with a relative electric field. Therefore, the composites can exhibit a higher energy storage density. However, the embedment of inorganic particles into polymer severely reduces the flexibility of the polymer. To develop flexible energy storage ultracapacitors as an energy storage device for wearable electronics, an all-organic composite approach, in which a dielectric polymer is mixed with polar organic molecules, is introduced. It is experimentally found that by adding a small amount of polar organic molecules into dielectric polymers, the polymers exhibits a high dielectric constant and can stand with a higher electric field. More importantly, the flexibility of the all-organic composites is better than the polymer matrix. Therefore, the all-organic composites can be a strong and promising candidate for the development of flexible energy storage devices for the wearable electronics. In this study, three different dielectric polymers and three different polar molecules were studied. All the all-organic composite systems exhibit a significant improvement on the energy storage density. These new flexible energy storage devices are being developed to be fabricated with on-demandadditive electronics manufacturing processes, so that they can be fabricated when needed in space on the International Space Station and planned lunar habitat and other future missions. These flexible energy storage devices will provide the storage in concert with other printed power generation devices to allow crew health and structural health monitoring sensor devices and systems to be self-powered, not requiring any external power or batteries.

energy storage↗
NASA NTRS2016

Low Temperature Regolith Bricks for In-Situ Structural Material

Current technology for producing in-situ structural materials on future missions to Mars or the moon relies heavily on energy-intensive sintering processes to produce solid bricks from regolith. This process requires heating the material up to temperatures in excess of 1000 C and results in solid regolith pieces with compressive strengths in the range of 14000 to 28000 psi, but are heavily dependent on the porosity of the final material and are brittle. This method is currently preferred over a low temperature cementation process to prevent consumption of precious water and other non-renewable materials. A high strength structural material with low energy requirements is still needed for future colonization of other planets. To fulfill these requirements, a nano-functionalization process has been developed to produce structural bricks from regolith simulant and shows promising mechanical strength results. Functionalization of granular silicate particles into alkoxides using a simple low temperature chemical process produces a high surface area zeolite particles that are held together via inter-particle oxygen bonding. Addition of water in the resulting zeolite particles produces a sol-gel reaction called "inorganic polymerization" which gives a strong solid material after a curing process at 60 C. The aqueous solution by-product of the reaction is currently being investigated for its reusability; an essential component of any ISRU technology. For this study, two batches of regolith bricks are synthesized from JSC-1A; the first batch from fresh solvents and chemicals, the second batch made from the water solution by-product of the first batch. This is done to determine the feasibility of recycling necessary components of the synthesis process, mainly water. Characterization including BET surface area, SEM, and EDS has been done on the regolith bricks as well as the constituent particles,. The specific surface area of 17.53 sq m/g (average) of the granular regolith material was obtained from nitrogen adsorption isotherm measurement. The size, shape and textures of regolith from SEM shows that the particles are 25-50 micrometers in size and mostly irregular in shape (Figure 1a). The elemental composition of regolith was identified from EDS analysis showed the presence of Si, Al, Fe, Na, Mg, Ca, Ti, O and C (see figure 1b). Each set of cylindrical brick samples were prepared by low energy process, and cured for 21 and 28 days, respectively to compare their compressive strength. Figure 1c, and d shows the JSC-1A brick and the compressive strength measurements. The results from the 21 day cured bricks (2 bricks) have been done and yielded an aver-age strength of 3050 psi, considerably higher than Portland cement mortars (Type IV and V). This promising technology provides the benefits of construction material similar to concrete, with a low complexity, low energy synthesis process and the likelihood of complete reusability of precious resources. Compressive strength using this method can be improved by increasing the surface area of the particles, using bi-modal particle size distribution, and adding certain additives to increase inter-particle forces.

ISRU↗
DOE OSTI2021

A Triple-Moment Representation of Ice in the Predicted Particle Properties (P3) Microphysics Scheme

In the original Predicted Particle Properties (P3) bulk microphysics scheme, all ice-phase hydrometeors are represented by one or more “free” ice categories, where the physical properties evolve smoothly through changes to the four prognostic variables (per category), and with a two-moment representation of the particle size distribution. As such, the spectral dispersion cannot evolve independently, which thus results in limitations in representation of ice—in particular, hail—due to necessary constraints in the scheme to prevent excessive gravitational size sorting. To overcome this, P3 has been modified to include a three-moment representation of the size distribution of each ice category through the addition of a fifth prognostic variable, the sixth moment of the size distribution. The details of the three-moment ice parameterization in P3 are provided. The behavior of the modified scheme, with the single-ice-category configuration, is illustrated through simulations in a simple 1D kinematic model framework as well as with near large-eddy-resolving (250-m grid spacing) 3D simulations of a hail-producing supercell. It is shown that the three-moment ice configuration controls size sorting in a physically based way and leads to an improved capacity to simulate large, heavily rimed ice (hail), including mean and maximum sizes and reflectivity, and thus an overall improvement in the representation of ice-phase particles in the P3 scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Optical Imaging of Flow Pattern and Phantom

Time-resolved optical imaging technique has been used to image the spatial distribution of small droplets and jet sprays in a highly scattering environment. The snake and ballistic components of the transmitted pulse are less scattered, and contain direct information about the sample to facilitate image formation as opposed to the diffusive components which are due to multiple collisions as a light pulse propagates through a scattering medium. In a time-gated imaging scheme, these early-arriving, image-bearing components of the incident pulse are selected by opening a gate for an ultrashort period of time and a shadowgram image is detected. Using a single shot cooled CCD camera system, the formation of water droplets is monitored as a function of time. Picosecond time-gated image of drop in scattering cells, spray droplets as a function of let speed and gas pressure, and model calcification samples consisted of calcium carbonate particles of irregular shapes ranging in size from 0. 1 to 1.5 mm affixed to a microscope slide have been measured. Formation produced by an impinging jet will be further monitored using a CCD with 1 kHz framing illuminated with pulsed light. The desired image resolution of the fuel droplets is on the 20 pm scale using early light through a highly scattering medium. A 10(exp -6)m displacement from a jet spray with a flow speed of 100 m/sec introduced by the ns grating pulse used in the imaging is negligible. Early ballistic/snake light imaging offers nondestructive and noninvasive method to observe the spatial distribution of hidden objects inside a highly scattering environment for space, biomedical, and materials applications. In this paper, the techniques we will present are time-resolved K-F transillumination imaging and time-gated scattered light imaging. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

Galland, Pierre A.↗
DOE OSTI2020

Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions

Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
NASA NTRS2002

Parameterization of Shortwave Cloud Optical Properties for a Mixture of Ice Particle Habits for use in Atmospheric Models

Based on the single-scattering optical properties pre-computed with an improved geometric optics method, the bulk absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the effective particle size of a mixture of ice habits, the ice water amount, and spectral band. The parameterization has been applied to computing fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. It is found that flux calculations are not overly sensitive to the assumed particle habits if the definition of the effective particle size is consistent with the particle habits that the parameterization is based. Otherwise, the error in the flux calculations could reach a magnitude unacceptable for climate studies. Different from many previous studies, the parameterization requires only an effective particle size representing all ice habits in a cloud layer, but not the effective size of individual ice habits.

Chou, Ming-Dah↗
DOE OSTI2022

LArQL: A phenomenological model for treating light and charge generation in liquid argon

Experimental data shows that both ionization charge and scintillation light in LAr depend on the deposited energy density ($dE/dx$) and electric field ($\mathcal{E}$). Moreover, free ionization charge and scintillation light are anticorrelated, complementary at a given ($dE/dx$, $\mathcal{E}$) pair. We present LArQL, a phenomenological model that provides the anticorrelation between light and charge and its dependence on the deposited energy as well as on the electric field applied. It modifies the Birks' charge model considering the contribution from the escape electrons at null and low electric fields, and reconciles with Birks' model prediction at higher fields. Deviations from current Birks' model are observed for LArTPCs operating at low $\mathcal{E}$ and for heavily ionizing particles. The LArQL model presents a satisfactory description at $dE/dx$ and field ranges for interacting particles in LArTPCs and fits well the available data. Improvements via data sets compilation and global fits are also interesting features of the model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Improvement of Raman lidar algorithm for quantifying aerosol extinction

Aerosols are particles of different composition and origin and influence the formation of clouds which are important in atmospheric radiative balance. At the present there is high uncertainty on the effect of aerosols on climate and this is mainly due to the fact that aerosol presence in the atmosphere can be highly variable in space and time. Monitoring of the aerosols in the atmosphere is necessary to better understanding many of these uncertainties. A lidar (an instrument that uses light to detect the extent of atmospheric aerosol loading) can be particularly useful to monitor aerosols in the atmosphere since it is capable to record the scattered intensity as a function of altitude from molecules and aerosols. One lidar method (the Raman lidar) makes use of the different wavelength changes that occur when light interacts with the varying chemistry and structure of atmospheric aerosols. One quantity that is indicative of aerosol presence is the aerosol extinction which quantifies the amount of attenuation (removal of photons), due to scattering, that light undergoes when propagating in the atmosphere. It can be directly measured with a Raman lidar using the wavelength dependence of the received signal. In order to calculate aerosol extinction from Raman scattering data it is necessary to evaluate the rate of change (derivative) of a Raman signal with respect to altitude. Since derivatives are defined for continuous functions, they cannot be performed directly on the experimental data which are not continuous. The most popular technique to find the functional behavior of experimental data is the least-square fit. This procedure allows finding a polynomial function which better approximate the experimental data. The typical approach in the lidar community is to make an a priori assumption about the functional behavior of the data in order to calculate the derivative. It has been shown in previous work that the use of the chi-square technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. We note that the a priori choice of a model itself can lead to larger uncertainties as compared to the method that is validated here. In this manuscript, the chi-square technique that determines the most likely functional behavior is validated through numerical simulation and by application to a large body of Raman lidar measurements. In general, we show that the chi-square approach to evaluate aerosol extinction yields lower extinction uncertainty than the traditional technique. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the use of the chi-square technique.

Russo, Felicita↗
DOE OSTI2020

Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks

The emergence of a pandemic affecting the respiratory system can result in a significant demand for face masks. This includes the use of cloth masks by large sections of the public, as can be seen during the current global spread of COVID-19. However, there is limited knowledge available on the performance of various commonly available fabrics used in cloth masks. Importantly, there is a need to evaluate filtration efficiencies as a function of aerosol particulate sizes in the 10 nm – 10 µm range, which is particularly relevant for respiratory virus transmission. We have carried out these studies for several common fabrics including cotton, silk, chiffon, flannel, various synthetics, and their combinations. While the filtration efficiencies for various fabrics when a single layer was used ranged from 5-80% and 15-95% for particle sizes <300 nm and >300 nm respectively, the efficiencies improved when multiple layers were used, and when using a specific combination of different fabrics. Filtration efficiencies of the hybrids (such as cotton-silk, cotton-chiffon, cotton-flannel) was >80 % (for particles <300 nm) and >90 % (for particles >300 nm). We speculate that the enhanced performance of the hybrids is likely due to the combined effect of mechanical and electrostatic-based filtration. Cotton, the most widely used material for cloth masks performs better at higher weave densities (i.e., threads per inch) and can make a significant difference in filtration efficiencies. Our studies also imply that gaps (as caused by an improper fit of the mask) can result in over a 60% decrease in the filtration efficiency, implying the need for future cloth mask design studies to take into account issues of “fit” and leakage, while allowing the exhaled air to vent efficiently. Overall, we find that combinations of various commonly available fabrics used in cloth masks can potentially provide significant protection against the transmission of aerosol particles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rapid assessment of SARS-CoV-2–evolved variants using virus-like particles

Efforts to determine why new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants demonstrate improved fitness have been limited to analyzing mutations in the spike (S) protein with the use of S-pseudotyped particles. In this study, we show that SARS-CoV-2 virus-like particles (SC2-VLPs) can package and deliver exogenous transcripts, enabling analysis of mutations within all structural proteins and at multiple steps in the viral life cycle. In SC2-VLPs, four nucleocapsid (N) mutations found universally in more-transmissible variants independently increased messenger RNA delivery and expression ~10-fold, and in a reverse genetics model, the serine-202→arginine (S202R) and arginine-203→methionine (R203M) mutations each produced >50 times as much virus. SC2-VLPs provide a platform for rapid testing of viral variants outside of a biosafety level 3 setting and demonstrate N mutations and particle assembly to be mechanisms that could explain the increased spread of variants, including B.1.617.2 (Delta, which contains the R203M mutation).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Multi-hadron systems via Lattice QCD

This project supported a broad set of research in theoretical nuclear physics which has been designed to support current and future experimental DOE facilities. The broad summary of physical observables of interest in this project were the bread-and-butter observables obtained in experimental nuclear and particle physics experiments, namely scattering amplitude including multi-hadronic states. The primary goal of this project was to design a systematically improvable paradigm for accessing such amplitudes directly from the Standard Model of Particle Physics. The main tools that were used and explored in this project were scattering theory, lattice QCD, and future quantum computers. The physics outputs included various novel formalisms, exploratory lattice QCD calculations, and a new proposal for studying any scattering observable using future quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1990

A turbulent two-phase flow model for nebula flows

A new and very efficient turbulent two-phase flow numericaly model is described to analyze the environment of a protoplanetary nebula at a stage prior to the formation of planets. Focus is on settling processes of dust particles in flattened gaseous nebulae. The model employs a perturbation technique to improve the accuracy of the numerical simulations of such flows where small variations of physical quantities occur over large distance ranges. The particles are allowed to be diffused by gas turbulence in addition to settling under gravity. Their diffusion coefficients is related to the gas turbulent viscosity by the non-dimensional Schmidt number. The gas turbulent viscosity is determined by the means of the eddy viscosity hypothesis that assumes the Reynolds stress tensor proportional to the mean strain rate tensor. Zero- and two-equation turbulence models are employed. Modeling assumptions are detailed and discussed. The numerical model is shown to reproduce an existing analytical solution for the settling process of particles in an inviscid nebula. Results of nebula flows are presented taking into account turbulence effects of nebula flows. Diffusion processes are found to control the settling of particles.

Champney, Joelle M.↗
NASA NTRS2013

Copper-Multiwall Carbon Nanotubes and Copper-Diamond Composites for Advanced Rocket Engines

This paper reports on the research effort to improve the thermal conductivity of the copper-based alloy NARloy-Z (Cu-3 wt.%Ag-0.5 wt.% Zr), the state-of-the-art alloy used to make combustion chamber liners in regeneratively-cooled liquid rocket engines, using nanotechnology. The approach was to embed high thermal conductivity multiwall carbon nanotubes (MWCNTs) and diamond (D) particles in the NARloy-Z matrix using powder metallurgy techniques. The thermal conductivity of MWCNTs and D have been reported to be 5 to 10 times that of NARloy-Z. Hence, 10 to 20 vol. % MWCNT finely dispersed in NARloy-Z matrix could nearly double the thermal conductivity, provided there is a good thermal bond between MWCNTs and copper matrix. Quantum mechanics-based modeling showed that zirconium (Zr) in NARloy-Z should form ZrC at the MWCNT-Cu interface and provide a good thermal bond. In this study, NARloy-Z powder was blended with MWCNTs in a ball mill, and the resulting mixture was consolidated under high pressure and temperature using Field Assisted Sintering Technology (FAST). Microstructural analysis showed that the MWCNTs, which were provided as tangles of MWCNTs by the manufacturer, did not detangle well during blending and formed clumps at the prior particle boundaries. The composites made form these powders showed lower thermal conductivity than the base NARloy-Z. To eliminate the observed physical agglomeration, tangled multiwall MWCNTs were separated by acid treatment and electroless plated with a thin layer of chromium to keep them separated during further processing. Separately, the thermal conductivities of MWCNTs used in this work were measured, and the results showed very low values, a major factor in the low thermal conductivity of the composite. On the other hand, D particles embedded in NARloy-Z matrix showed much improved thermal conductivity. Elemental analysis showed migration of Zr to the NARloy-Z-D interface to form ZrC, which appeared to provide a low contact thermal resistance. These results are consistent with the quantum mechanics-based model predictions. NARloy-Z-D composites have relatively high thermal conductivities and are promising for further development.

Bhat, Biliyar N.↗