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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Cryopump for large pulses of hydrogen

A test involving a flow of hot hydrazine decomposition products at a rate of 13.6 g/s (0.03 lb/s) established the requirement to maintain pressure in an 11.9-m-(39 ft) diameter space chamber below 200 microns. The flow, 2/3 hydrogen and 1/3 nitrogen by volume, continued for several periods ranging from 3 to 15 min. The pressure requirement was necessary to minimize thermal effects of the gas on the test vehicle but was well beyond the capability of the existing facility pumps. Various methods of obtaining additional temporary jump capacity were considered. From these, the slugged-charcoal approach was selected as the quickest and least expensive method to implement.

Moore, B. C.↗
DOE OSTI2017

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An artificial neural network framework for reduced order modeling of transient flows

Here, this paper proposes a supervised machine learning framework for the non-intrusive model order reduction of unsteady fluid flows to provide accurate predictions of non-stationary state variables when the control parameter values vary. Our approach utilizes a training process from full-order scale direct numerical simulation data projected on proper orthogonal decomposition (POD) modes to achieve an artificial neural network (ANN) model with reduced memory requirements. This data-driven ANN framework allows for a nonlinear time evolution of the modal coefficients without performing a Galerkin projection. Our POD-ANN framework can thus be considered an equation-free approach for latent space dynamics evolution of nonlinear transient systems and can be applied to a wide range of physical and engineering applications. Within this framework we introduce two architectures, namely sequential network (SN) and residual network (RN), to train the trajectory of modal coefficients. We perform a systematic analysis of the performance of the proposed reduced order modeling approaches on prediction of a nonlinear wave-propagation problem governed by the viscous Burgers equation, a simplified prototype setting for transient flows. We find that the POD-ANN-RN yields stable and accurate results for test problems assessed both within inside and outside of the database range and performs significantly better than the standard intrusive Galerkin projection model. Finally, our results show that the proposed framework provides a non-intrusive alternative to the evolution of transient physics in a POD basis spanned space, and can be used as a robust predictive model order reduction tool for nonlinear dynamical systems.

42 ENGINEERING↗
DOE OSTI2018

AFe{sub 2}O{sub 4}/(Pb{sub 0.80}Sr{sub 0.20})TiO{sub 3} (A = Mn, Ni and Co): a New Room-Temperature Magnetoelectric Multiferroic Bi-layered Composite Films

The room temperature and magnetic field-dependent dielectric, impedance and magnetoelectric (ME) coupling effect of polycrystalline AFe{sub 2}O{sub 4}/(Pb{sub 0.80}Sr{sub 0.20})TiO{sub 3} (A = Mn, Ni and Co) bi-layered composite films have been investigated. The structural and microstructural analyses using the X-ray diffraction (XRD), atomic force microscopy (AFM) and scanning electron microscopy (SEM) reveal the presence of homogenous growth of both tetragonal and spinel phases without any extra phase and diffusion in the AFO/PST20 bi-layered composite films. Our results show that all composite films exhibit ferroelectric as well as considerable magnetic, indicating magnetoelectric coupling effect. Our results show that the dielectric and impedance properties of AFO/PST20 bi-layered composite films can be manipulated by the magnetic field at room temperature, also indicating the existence of magnetoelectric coupling. The impedance (Z{sup ′} and Z{sup ″}) Nyquist plots show distinct electrical responses with the magnetic field. The maximum magnetoelectric coefficient (α) is found to be α{sub ME}∼ 239 and ∼ 195 mV/cm/Oe for the MFO/PST20 and CFO/PST20 bi-layered composite films, respectively. The above results show that the AFO/PST20 bi-layered composite films are room-temperature multiferroic material that can be potentially used in magnetoelectric devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Tailoring of crystal phase and Néel temperature of cobalt monoxides nanocrystals with synthetic approach conditions

Cobalt monoxide (CoO) nanocrystals were synthesized by thermal decomposition of cobalt oleate precursor in a high boiling point organic solvent 1-octadecene. The X-ray diffraction pattern and transmission electron microscopy studies suggest that pure face-centered-cubic (fcc) phase of CoO can be synthesized in the temperature range of 569–575 K. Thermolysis product at higher synthesis temperature 585 K is a mixture of fcc and hexagonal-closed-packed (hcp) phases. These nanocrystals are single crystals of CoO and exhibit mixture of two types of morphologies; one is nearly spherical with 5–25 nm diameter, and other one is 5–10 nm thick flake. The pure fcc-CoO nanocrystals show enhanced, and mixture of fcc- and hcp-CoO nanocrystals show reduced antiferromagnetic ordering temperature. Such results provide new opportunities for optimizing and enhancing the properties and performance of cobalt oxide nanomaterials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Carbon Sink Strength of Subsurface Horizons in Brazilian Oxisols

Interactions with pedogenic oxides are a known mechanism of soil organic matter (SOM) protection, but little is known about how the protective power of pedogenic oxides varies with soil depth in highly weathered tropical soils. To address this issue, we followed the decomposition of a double-labeled plant litter ( 13 C/ 15 N) in microcosm experiments using samples collected at four depths (0–10, 10–20, 20–40, and 60–100 cm) from six Brazilian Oxisols. These soils were selected to include a range of taxonomic subtypes, spanning wide variations in mineralogy and texture. After a 12-mo incubation, we quantified the proportion of isotopically-labeled SOM ( 13 C/ 15 N) within the mineral fraction <53 µm (i.e., clay+silt). We found that litter-C retention increased with depth, while the opposite occurred for litter-N. Correlations between isotopically-labeled SOM and short-range order (SRO) Al-/Fe-(hydr)oxides were insignificant in topsoil (0–10 cm), but increased with depth, reaching peak significance in the 20- to 40-cm interval (r = 0.64 and 0.58, for litter-C and -N, respectively). A similar trend was observed for crystalline Al-/Fe-(hydr)oxides, which were more strongly correlated with the retention of 13 C than 15 N. We posit that in subsoil, both SRO and crystalline Al-/Fe-(hydr)oxides are more readily involved in the neoformation of mineral-organic associations. Overall, litter-C is less efficiently transferred into the clay+silt fraction of C-rich topsoil relative to C-depleted subsoil horizons, which may represent a significant C sink for Oxisols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Final Report - PyVERAIn: An Open Source, Python-based CASL Preprocessing Platform for Reactor Geometry, Code Discretizations, and Parallel Domain Decompositions

The introduction of advanced modeling and simulation practices over the last several decades has proven to produce better products, more quickly, and at the reduced cost. This computational experimentation has enabled the design and development of a variety of innovative products by reducing the need to build expensive prototypes, and by allowing rapid, comprehensive design studies across a wide range of products. Despite these successes, there are significant barriers to widespread adoption of these tools. This project aims to address several of these barriers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Kinematically identified recoiling supermassive black hole candidates in SDSS QSOs with z < 0.25

We have performed a spectral decomposition to search for recoiling supermassive black holes (rSMBHs) in Sloan Digital Sky Survey (SDSS) quasi-stellar objects (QSOs) with z < 0.25. Out of 1271 QSOs, we have identified 26 rSMBH candidates that are recoiling toward us. The projected recoil velocities range from −76 to −307 km s{sup −1} with a mean of −149 ± 58 km s{sup −1}. Most of the rSMBH candidates are hosted by gas-rich luminous infrared galaxies (LIRGs)/ultra-luminous infrared galaxies (ULIRGs), but only 23% of them show signs of tidal features, which suggests that a majority of them are advanced mergers. We find that the black hole masses M {sub BH} of the rSMBH candidates are on average ∼5 times smaller than those of their stationary counterparts and cause a scatter in the M{sub BH}−σ{sub ∗} relation. The Eddington ratios of all of the rSMBH candidates are larger than 0.1, with a mean of 0.52 ± 0.27, suggesting that they are actively accreting mass. Velocity shifts in high-excitation coronal lines suggest that the rSMBH candidates are recoiling with an average velocity of about −265 km s{sup −1}. The electron density in the narrow line region of the H ii rSMBH candidates is about 1/10 of that in active galactic nucleus (AGN) rSMBH candidates, probably because the AGN in the former was more spatially offset than that in the latter. The estimated spatial offsets between the rSMBH candidate and the center of the host galaxy range from 0.″21 to 1.″97 and need to be confirmed spatially with high-resolution adaptive optics imaging observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Decomposition of NO studied by infrared emission and CO laser absorption

A diagnostic technique for monitoring the concentration of NO using absorption of CO laser radiation was developed and applied in a study of the decomposition kinetics of NO. Simultaneous measurements of infrared emission by NO at 5.3 microns were also made to validate the laser absorption technique. The data were obtained behind incident shocks in NO-N2O-Ar (or Kr) mixtures, with temperatures in the range 2400-4100 K. Rate constants for dominant reactions were inferred from comparisons with computer simulations of the reactive flow.

Hanson, R. K.↗
NASA NTRS1975

Decomposition of NO studied by infrared emission and CO laser absorption

A diagnostic technique for monitoring the concentration of NO using absorption of CO laser radiation has been developed and applied in a study of the decomposition kinetics of NO. Simultaneous measurements of infrared emission by NO at 5.3 microns were also made to validate the laser absorption technique. The data were obtained behind incident shocks in NO-N2O-Ar (or Kr) mixtures, with temperatures in the range 2400-4100 K. The rate constant for the dominant reaction of O and NO to yield N and O2 was inferred from comparisons with computer simulations of the reactive flow.

Hanson, R. K.↗
DOE OSTI2020

Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations

Here we propose a generalized space-time domain decomposition approach for the physics-informed neural networks (PINNs) to solve nonlinear partial differential equations (PDEs) on arbitrary complex-geometry domains. The proposed framework, named eXtended PINNs ( X P I N N s ), further pushes the boundaries of both PINNs as well as conservative PINNs (cPINNs), which is a recently proposed domain decomposition approach in the PINN framework tailored to conservation laws. Compared to PINN, the XPINN method has large representation and parallelization capacity due to the inherent property of deployment of multiple neural networks in the smaller subdomains. Unlike cPINN, XPINN can be extended to any type of PDEs. Moreover, the domain can be decomposed in any arbitrary way (in space and time), which is not possible in cPINN. Thus, XPINN offers both space and time parallelization, thereby reducing the training cost more effectively. In each subdomain, a separate neural network is employed with optimally selected hyperparameters, e.g., depth/width of the network, number and location of residual points, activation function, optimization method, etc. A deep network can be employed in a subdomain with complex solution, whereas a shallow neural network can be used in a subdomain with relatively simple and smooth solutions. We demonstrate the versatility of XPINN by solving both forward and inverse PDE problems, ranging from one-dimensional to three-dimensional problems, from time-dependent to time-independent problems, and from continuous to discontinuous problems, which clearly shows that the XPINN method is promising in many practical problems. The proposed XPINN method is the generalization of PINN and cPINN methods, both in terms of applicability as well as domain decomposition approach, which efficiently lends itself to parallelized computation. The XPINN code is available on h t t p s : / / g i t h u b . c o m / A m e y a J a g t a p / X P I N N s .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Compact video content representation for video coding using low multi-linear tensor rank approximation with dynamic core tensor order

Tensor is a multi-way representation of an entity that is widely used in many applications of mathematics and physics. The wide range of tensor algebra operations attract the researchers of graphical and vision field to identify unique methods for various applications such as segmentation, compression, indexing and so on. In this paper, low multi-linear rank approximation of a tensor is used for decomposition so as to perform compression on a video that is represented as a 4D tensor. Thus, the encoder has blocks for (1) multilinear rank approximation method so as to aid decomposition, (2) sparsity removal of residual data to reduce the required memory storage to a small level, (3) quantization on the sparse less residual data and (4) LZ77 dictionary coding for the video. The decoder uses a tensor reconstruction block along with residual error correction block that reduces loss/error in the reconstructed video. The size of core tensor is an important factor in rank approximation. It is identified at run time depending on the video contents. This size is determined adaptively using Tikhonov’s regularization method. The best value of core tensor size is identified with the corner of L-curve which preserves the video contents from heavy loss/error. Experimental results of the proposed work on comparison with H.264/AVC compression method indicate that the proposed method achieves up to 10% improvement in compression ratio with the least amount of loss and a maximum signal to noise ratio of 0.14. The proposed system gives better compression ratio than H.265 for videos with more number of frames without compromising quality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The metallization and superconductivity of dense hydrogen sulfide

Hydrogen sulfide (H{sub 2}S) is a prototype molecular system and a sister molecule of water (H{sub 2}O). The phase diagram of solid H{sub 2}S at high pressures remains largely unexplored arising from the challenges in dealing with the pressure-induced weakening of S–H bond and larger atomic core difference between H and S. Metallization is yet achieved for H{sub 2}O, but it was observed for H{sub 2}S above 96 GPa. However, the metallic structure of H{sub 2}S remains elusive, greatly impeding the understanding of its metallicity and the potential superconductivity. We have performed an extensive structural study on solid H{sub 2}S at pressure ranges of 10–200 GPa through an unbiased structure prediction method based on particle swarm optimization algorithm. Besides the findings of candidate structures for nonmetallic phases IV and V, we are able to establish stable metallic structures violating an earlier proposal of elemental decomposition into sulfur and hydrogen [R. Rousseau, M. Boero, M. Bernasconi, M. Parrinello, and K. Terakura, Phys. Rev. Lett. 85, 1254 (2000)]. Our study unravels a superconductive potential of metallic H{sub 2}S with an estimated maximal transition temperature of ∼80 K at 160 GPa, higher than those predicted for most archetypal hydrogen-containing compounds (e.g., SiH{sub 4}, GeH{sub 4}, etc.)

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

First Double-Differential Cross Section Measurement of Neutral-Current 𝜋 0 Production in Neutrino-Argon Scattering in the MicroBooNE Detector

We report the first double-differential cross section measurement of neutral-current neutral pion (NC⁢𝜋 0 ) production in neutrino-argon scattering, as well as single-differential measurements of the same channel in terms of final states with and without protons. The kinematic variables of interest for these measurements are the 𝜋 0 momentum and the 𝜋 0 scattering angle with respect to the neutrino beam. A total of 4971 candidate NC⁢𝜋 0 events fully contained within the MicroBooNE detector are selected using data collected at a mean neutrino energy of ∼0.8 GeV from 6.4 ×10 20 protons on target from the Booster Neutrino Beam at the Fermi National Accelerator Laboratory. After extensive data-driven model validation to ensure unbiased unfolding, the Wiener-singular-value-decomposition method is used to extract nominal flux-averaged cross sections. The results are compared to predictions from commonly used neutrino event generators, which tend to overpredict the measured NC⁢𝜋 0 cross section, especially in the 0.2–0.5 GeV/c 𝜋 0 momentum range and at forward scattering angles. Events with at least one proton present in the final state are also underestimated. This data will help improve the modeling of NC⁢𝜋 0 production, which represents a major background in measurements of charge-parity violation in the neutrino sector and in searches for new physics beyond the standard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers

The Gyrokinetic Toroidal Code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5D Vlasov-Poisson equation featuring efficient utilization of modern parallel computer architectures at the petascale and beyond. Motivated by the goal of developing a modern code capable of dealing with the physics challenge of increasing problem size with sufficient resolution, new thread-level optimizations have been introduced as well as a key additional domain decomposition. GTC-P's multiple levels of parallelism, including inter-node 2D domain decomposition and particle decomposition, as well as intra-node shared memory partition and vectorization have enabled pushing the scalability of the PIC method to extreme computational scales. In this paper, we describe the methods developed to build a highly parallelized PIC code across a broad range of supercomputer designs. This particularly includes implementations on heterogeneous systems using NVIDIA GPU accelerators and Intel Xeon Phi (MIC) co-processors and performance comparisons with state-of-the-art homogeneous HPC systems such as Blue Gene/Q. New discovery science capabilities in the magnetic fusion energy application domain are enabled, including investigations of Ion-Temperature-Gradient (ITG) driven turbulence simulations with unprecedented spatial resolution and long temporal duration. Performance studies with realistic fusion experimental parameters are carried out on multiple supercomputing systems spanning a wide range of cache capacities, cache-sharing configurations, memory bandwidth, interconnects and network topologies. Furthermore, these performance comparisons using a realistic discovery-science-capable domain application code provide valuable insights on optimization techniques across one of the broadest sets of current high-end computing platforms worldwide.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2003

Isothermal Microcalorimetric Evaluation of Compatibility of Proposed Injector Materials with High-Test Hydrogen Peroxide Propellant

High-test hydrogen peroxide (HTP) is receiving renewed interest as a monopropellant and as the oxidizer for bipropellant systems. HTP is hydrogen peroxide in concentrations ranging from 70 to 98%. All surfaces wetted by HTP must be evaluated for compatibility with the fluid. In the case of tanks, lines and valves compatibility is required to preserve the HTP oxygen and energy content and to avoid overpressurization due to decomposition. With injectors and regenerative cooling passages shorter exposure time reduces these concerns. However, phase changes from fluid to gas impact heat transfer and become the dominant compatibility concern. Isothermal microcalorimetry (IMC) provides a convenient and reproducible means to observe the decomposition of HTP when exposed to structural materials and therefore the compatibility of those materials'. The instrument provides heat flow values in terms of watts that may be converted to a reaction rate given the heat of reaction for the decomposition of hydrogen peroxide. These values are then converted to percent active oxygen loss per week (%AOL/wk) to preserve an earlier convention for quantifying HTP compatibility. Additionally, qualitative designations of compatibility have been assigned to these values. This scheme consists of four classes with Class 1 being the most compatible. While historical compatibility data is available its current applicability is in question due to subtle changes in the compositions of both HTP and structural materials. Trace levels of molecules can have significant influence on compatibility. Therefore representative samples of materials must be evaluated with current HTP formulations. In this work seven materials were selected for their strength characteristics at high temperature as expected in a HTP injector. The materials were then evaluated by IMC for HTP compatibility.

Gostowski, Rudy↗