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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Accelerator Vacuum Windows: A Review of Past Research and a Strategy for the Development of a New Design for Improved Safety and Longevity for Particle Accelerators

Vacuum window research continues at Fermilab and this paper will examine cost effective, consistent designs which can have a huge impact on accelerator laboratories in terms of safety and cost. Issues such as the design, materials, analysis, testing and fabrication are addressed, including beam scattering plots and materials cost-benefit analysis and examining different materials which can potentially be substitutes for beryllium. A previous research paper has examined current fabrication and design techniques and also failure modes at Fermi, and this paper examines previous research in addition to emerging technologies. Many different paths have been taken by HEP Laboratories throughout the world with varying success. The history of vacuum window development is extensive and not well defined, and a matrix of what research has already been done on materials and joint design for vacuum windows will be shown. This report finally includes a treatise for vacuum window technology and a view towards emerging designs and materials and discusses future advances of research such as fabrication techniques including additive manufacturing and ultrasonic welding. Further exploration into these would prove beneficial to developing vacuum windows that are safer and stronger while being more transparent to the beam.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Analysis of Monte Carlo accelerated iterative methods for sparse linear systems: Analysis of Monte Carlo accelerated iterative methods for sparse linear systems

Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Accelerating ab initio path integral molecular dynamics with multilevel sampling of potential surface

A multilevel approach to sample the potential energy surface in a path integral formalism is proposed. The purpose is to reduce the required number of ab initio evaluations of energy and forces in ab initio path integral molecular dynamics (AI-PIMD) simulation, without compromising the overall accuracy. To validate the method, the internal energy and free energy of an Einstein crystal are calculated and compared with the analytical solutions. As a preliminary application, we assess the performance of the method in a realistic model—the FCC phase of dense atomic hydrogen, in which the calculated result shows that the acceleration rate is about 3 to 4-fold for a two-level implementation, and can be increased up to 10 times if extrapolation is used. With only 16 beads used for the ab initio potential sampling, this method gives a well converged internal energy. The residual error in pressure is just about 3 GPa, whereas it is about 20 GPa for a plain AI-PIMD calculation with the same number of beads. The vibrational free energy of the FCC phase of dense hydrogen at 300 K is also calculated with an AI-PIMD thermodynamic integration method, which gives a result of about 0.51 eV/proton at a density of r{sub s}=0.912.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A coupled ordinates method for solution acceleration of rarefied gas dynamics simulations

Non-equilibrium rarefied flows are frequently encountered in a wide range of applications, including atmospheric re-entry vehicles, vacuum technology, and microscale devices. Rarefied flows at the microscale can be effectively modeled using the ellipsoidal statistical Bhatnagar–Gross–Krook (ESBGK) form of the Boltzmann kinetic equation. Numerical solutions of these equations are often based on the finite volume method (FVM) in physical space and the discrete ordinates method in velocity space. However, existing solvers use a sequential solution procedure wherein the velocity distribution functions are implicitly coupled in physical space, but are solved sequentially in velocity space. This leads to explicit coupling of the distribution function values in velocity space and slows down convergence in systems with low Knudsen numbers. Furthermore, this also makes it difficult to solve multiscale problems or problems in which there is a large range of Knudsen numbers. In this paper, we extend the coupled ordinates method (COMET), previously developed to study participating radiative heat transfer, to solve the ESBGK equations. In this method, at each cell in the physical domain, distribution function values for all velocity ordinates are solved simultaneously. This coupled solution is used as a relaxation sweep in a geometric multigrid method in the spatial domain. Enhancements to COMET to account for the non-linearity of the ESBGK equations, as well as the coupled implementation of boundary conditions, are presented. The methodology works well with arbitrary convex polyhedral meshes, and is shown to give significantly faster solutions than the conventional sequential solution procedure. Acceleration factors of 5–9 are obtained for low to moderate Knudsen numbers on single processor platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

The complex reaction network of catalytic biomass conversions often involves hundreds of surface intermediates and thousands of reaction steps, greatly hindering the rational design of metal catalysts for these conversions. Here, we present a framework of machine learning (ML)-accelerated first-principles studies for the hydrodeoxygenation (HDO) of propanoic acid over transition metal surfaces. The microkinetic model (MKM) is initially parametrized by ML-predicted energies and iteratively improved by identifying the rate-determining species and steps (RDS), computing their energies by density functional theory (DFT), and reparameterizing the MKM until all the RDS are computed by DFT. The Gaussian process (GP) model performs significantly better than the linear ridge regression model for predicting both the adsorption free energies and transition state free energies. Parameterized with energies from the GP model, only 5–20% of the full reaction network has to be computed by DFT for the MKM to possess DFT-level accuracy for the TOF and dominant reaction pathway. While the linear ridge regression model performs worse than the GP model, its performance is greatly improved when only transition states are predicted by the regression model and adsorption energies are computed by DFT. Overall, we find that a high accuracy in adsorption free energies is more important for a reliable MKM than a high accuracy in TS free energies. Lastly, based on the GP model with GOH and GCHCHCO as catalyst descriptors, we build two-dimensional volcano plots in activity and selectivity that can help design promising alloy catalysts for HDO reactions of organic acids.

adsorption↗
DOE OSTI2018

Tracking Tumor Colonization in Xenograft Mouse Models Using Accelerator Mass Spectrometry [Tracking Tumor Colonization in vivo Using Accelerator Mass Spectrometry]

Here we propose an Accelerator Mass Spectrometry (AMS)-based high precision method for quantifying the number of cancer cells that initiate metastatic tumors, in xenograft mice. Quantification of 14 C per cell prior to injection into animals, and quantification of 14 C in whole organs allows us to extrapolate the number of cancer cells available to initiate metastatic tumors. The 14 C labeling was optimized such that 1 cancer cell was detected among 1 million normal cells. We show that ~1–5% of human cancer cells injected into immunodeficient mice form subcutaneous tumors, and even fewer cells initiate metastatic tumors. Comparisons of metastatic site colonization between a highly metastatic (PC3) and a non-metastatic (LnCap) cell line showed that PC3 cells colonize target tissues in greater quantities at 2 weeks post-delivery, and by 12 weeks post-delivery no 14 C was detected in LnCap xenografts, suggesting that all metastatic cells were cleared. The 14 C-signal correlated with the presence and the severity of metastatic tumors. AMS measurements of 14 C-labeled cells provides a highly-sensitive, quantitative assay to experimentally evaluate metastasis and colonization of target tissues in xenograft mouse models. This method can potentially be used to evaluate tumor aggressiveness and assist in making informed decisions regarding treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Order-parameter-aided temperature-accelerated sampling for the exploration of crystal polymorphism and solid-liquid phase transitions

The problem of predicting polymorphism in atomic and molecular crystals constitutes a significant challenge both experimentally and theoretically. From the theoretical viewpoint, polymorphism prediction falls into the general class of problems characterized by an underlying rough energy landscape, and consequently, free energy based enhanced sampling approaches can be brought to bear on the problem. In this paper, we build on a scheme previously introduced by two of the authors in which the lengths and angles of the supercell are targeted for enhanced sampling via temperature accelerated adiabatic free energy dynamics [T. Q. Yu and M. E. Tuckerman, Phys. Rev. Lett. 107, 015701 (2011)]. Here, that framework is expanded to include general order parameters that distinguish different crystalline arrangements as target collective variables for enhanced sampling. The resulting free energy surface, being of quite high dimension, is nontrivial to reconstruct, and we discuss one particular strategy for performing the free energy analysis. The method is applied to the study of polymorphism in xenon crystals at high pressure and temperature using the Steinhardt order parameters without and with the supercell included in the set of collective variables. The expected fcc and bcc structures are obtained, and when the supercell parameters are included as collective variables, we also find several new structures, including fcc states with hcp stacking faults. We also apply the new method to the solid-liquid phase transition in copper at 1300 K using the same Steinhardt order parameters. Our method is able to melt and refreeze the system repeatedly, and the free energy profile can be obtained with high efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Investigation of radiative bow-shocks in magnetically accelerated plasma flows

We present a study of the formation of bow shocks in radiatively cooled plasma flows. This work uses an inverse wire array to provide a quasi-uniform, large scale hydrodynamic flow accelerated by Lorentz forces to supersonic velocities. This flow impacts a stationary object placed in its path, forming a well-defined Mach cone. Interferogram data are used to determine a Mach number of ∼6, which may increase with radial position suggesting a strongly cooling flow. Self-emission imaging shows the formation of a thin (<60 μm) strongly emitting shock region, where T{sub e} ∼ 40–50 eV, and rapid cooling behind the shock. Emission is observed upstream of the shock position which appears consistent with a radiation driven phenomenon. Data are compared to 2-dimensional simulations using the Gorgon MHD code, which show good agreement with the experiments. The simulations are also used to investigate the effect of magnetic field in the target, demonstrating that the bow-shocks have a high plasma β, and the influence of B-field at the shock is small. This consistent with experimental measurement with micro bdot probes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗