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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cation Radical-Accelerated Nucleophilic Aromatic Substitution for Amination of Alkoxyarenes

Nucleophilic aromatic substitution (S N Ar) is a common method for arene functionalization; however, reactions of this type are typically limited to electron-deficient aromatic halides. Herein, we describe a mild, metal-free, cation-radical accelerated nucleophilic aromatic substitution (CRA-S N Ar) using a potent, highly oxidizing acridinium photoredox catalyst. Selective substitution of arene C–O bonds on a wide array of aryl ether substrates was shown with a variety of primary amine nucleophiles. Mechanistic evidence is also presented that supports the proposed CRA-S N Ar pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Advising Big Data Transfer Over Dedicated Connections Based on Profiling Optimization

Big data transfer in next-generation scientific applications is currently commonly carried out over dedicated channels in high-performance networks (HPNs), where transport protocols play a critical role in maximizing application-level throughput. Optimizing the performance of these protocols is challenging: i) transport protocols perform differently in various network environments, and the protocol choice is not straightforward; ii) even for a given protocol in a given environment, different parameter settings of the protocol may lead to significantly different performance and oftentimes the default setting does not yield the best performance. However, it is prohibitively time-consuming to conduct exhaustive transport profiling due to the large parameter space. In this paper, we propose a PRofiling Optimization Based DAta Transfer Advisor (ProbData) to help end users determine the most effective transport method with the most appropriate parameter settings to achieve satisfactory performance for big data transfer over dedicated connections in HPNs. ProbData employs a fast profiling scheme based on the Simultaneous Perturbation Stochastic Approximation algorithm, namely, FastProf, to accelerate the exploration of the optimal operational zones of various transport methods to improve profiling efficiency. We first present a theoretical background of the optimized profiling approach in ProbData and then detail its design and implementation. The advising procedure and performance benefits of FastProf and ProbData are illustrated and evaluated by both extensive emulations based on real-life performance measurements and experiments over various physical connections in existing production HPNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN

Physics-informed neural network (PINN) has been successfully applied in solving a variety of nonlinear non-convex forward and inverse problems. However, the training is challenging because of the non-convex loss functions and the multiple optima in the Bayesian inverse problem. In this work, we propose a multi-variance replica exchange stochastic gradient Langevin dynamics method to tackle the challenge of the multiple local optima in the optimization and the challenge of the multiple modal posterior distribution in the inverse problem. Replica exchange methods are capable of escaping from the local traps and accelerating the convergence; two chains with different temperatures are designed where the low temperature chain aims for the local convergence, and the target of the high temperature chain is to travel globally and explore the whole loss function entropy landscape. However, it may not be efficient to solve mathematical inversion problems by using the vanilla replica method directly since the method doubles the computational cost in evaluating the forward solvers (likelihood functions) in the two chains. To address this issue, we propose to make different assumptions on the energy function estimation and this facilities one to use solvers of different fidelities in the likelihood function evaluation. More precisely, one can use a solver with low fidelity in the high temperature chain while using a solver with high fidelity in the low temperature chain. Our proposed method significantly lowers the computational cost in the high temperature chain, meanwhile preserving the accuracy and converging very fast. Here we give an unbiased estimate of the swapping rate and give an estimation of the discretization error of the scheme. To verify our idea, we design and solve four inverse problems which have multiple modes. The proposed method is also employed to train the Bayesian PINN to solve the forward and inverse problems; faster and more accurate convergence has been observed when compared to the stochastic gradient Langevin dynamics (SGLD) method and vanilla replica exchange methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Unifying Quantum Materials Modeling and Experiments: The Role of Machine Learning Interatomic Potentials

Computational experiments have emerged as a powerful complement to traditional experiments in the design of new materials. The development of machine learning (ML) and deep learning techniques, combined with database construction and data mining, has significantly enhanced traditional quantum mechanical methods. This synergy enables the rapid development of structure-property relationships. In this talk, I will discuss our recent efforts in applying Machine Learning Interatomic Potentials (MLIAPs) to accelerate materials modeling across various material classes and challenging applications where traditional methods fall short. First, I will highlight the success of MLIAPs in accurately modeling the melting behavior of complex materials. Our results demonstrate high fidelity with experimental observations and also with calculated reference melting temperatures. In the second application, I will discuss how MLIAPs are trained and applied to elucidate the interplay between segregation tendencies and surface reconstructions in CuNi alloys under oxidizing conditions. A key factor in the success of these MLIAP applications is the design of minimalistic yet flexible datasets along with a computational framework for training MLIAPs.

Saidi, Wissam↗
DOE OSTI2026

Experimental longitudinal emittance manipulation using laser-based photoionization in the Fermilab Linac

A series of simulations and beam studies were conducted at Fermilab’s linear accelerator to evaluate the effectiveness of longitudinal emittance control via laser-induced photoionization. While similar laser techniques have been employed at Fermilab to enhance injection and extraction efficiency into the Booster, the work presented here focuses on extending these methods to bunch-by-bunch manipulation. This approach utilizes fine-scale correction of the H- bunches’ longitudinal spatial distribution. In theory, loosely confined particles in longitudinal phase space contribute to emittance growth during acceleration. By selectively removing these outlying particles through laser scraping (H- + γ → H + e-), this growth can be reduced. This report presents experimental results from both symmetric and asymmetric longitudinal scraping of H⁻ bunches in the Fermilab linac, which were subsequently injected into Booster, and evaluates the broader applicability of this method for future high-intensity accelerator operations.

Landon, Parker [Boston U.; Fermilab]↗
DOE OSTI2020

thornado-transport: Anderson- and GPU-accelerated nonlinear solvers for neutrino-matter coupling

Algorithms for neutrino-matter coupling in core-collapse supernovae (CCSNe) are investigated in the context of a spectral two-moment model, which is discretized in space with the discontinuous Galerkin method, integrated in time with implicit-explicit (IMEX) methods, and implemented in the toolkit for high-order neutrino-radiation hydrodynamics (thornado). The model considers electron neutrinos and antineutrinos and tabulated opacities from Bruenn (1985), which includes neutrino-electron scattering and pair processes. The nonlinear system arising from implicit time discretization of the equations governing neutrino-matter coupling is iterated to convergence using Anderson-accelerated fixed-point methods, which avoid formation of Jacobians and inversion of dense linear systems. Numerical experiments show that, for a given tolerance, a nested iteration scheme which aims to reduce opacity evaluations can lower the computational cost. Our initial port to GPUs, using both OpenMP and OpenACC, shows an overall speedup of up to ~ 100× when compared to results using a single CPU core. These results indicate that the algorithms implemented in thornado are well-suited to GPU acceleration.

Laiu, Paul↗
NASA NTRS2016

Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

Several improvements to the mixed-elementUSM3Ddiscretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

Pandya, Mohagna J.↗
NASA NTRS2016

Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

Several improvements to the mixed-element USM3D discretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

Pandya, Mohagna J.↗
DOE OSTI2021

Efficient Nonthermal Ion and Electron Acceleration Enabled by the Flux-Rope Kink Instability in 3D Nonrelativistic Magnetic Reconnection

The relaxation of field-line tension during magnetic reconnection gives rise to a universal Fermi acceleration process involving the curvature drift of particles. However, the efficiency of this mechanism is limited by the trapping of energetic particles within flux ropes. Using 3D fully kinetic simulations, we demonstrate that the flux-rope kink instability leads to strong field-line chaos in weak-guide-field regimes where the Fermi mechanism is most efficient, thus allowing particles to transport out of flux ropes and undergo further acceleration. As a consequence, both ions and electrons develop clear power-law energy spectra that contain a significant fraction of the released energy. The low-energy bounds are determined by the injection physics, while the high-energy cutoffs are limited only by the system size. Furthermore, these results have strong relevance to observations of nonthermal particle acceleration in space and astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Erosion rate diagnostics in ion thrusters using laser-induced fluorescence

We have used laser-induced fluorescence (LIF) to monitor the charge-exchange ion erosion of the molybdenum accelerator electrode in ion thrusters. This real-time, nonintrusive method was implemented by operating a 30cm-diam ring-cusp thruster using xenon propellant. With the thruster operating at a total power of 5 kW, laser radiation at a wavelength of 390 nm (corresponding to a ground state atomic transition of molybdenum) was directed through the extracted ion beam adjacent to the downstream surface of the molybdenum accelerator electrode. Molybdenum atoms, sputtered from this surface as a result of charge-exchange ion erosion, were excited by the laser radiation. The intensity of the laser-induced fluorescence radiation, which is proportional to the sputter rate of the molybdenum atoms, was measured and correlated with variations in thruster operating conditions such as accelerator electrode voltage, accelerator electrode current, and test facility background pressure. We also demonstrated that the LIF technique has sufficient sensitivity and spatial resolution to evaluate accelerator electrode lifetime in ground-based test facilities.

Gaeta, C. J.↗
NASA NTRS1993

Methods for evaluation of the microgravity environment aboard Space Station Freedom

Space Station Freedom will be a platform for microgravity research. For superior microgravity science, the experiment locations must experience very little acceleration in the quasi-steady, structural dynamic, and vibroacoustic frequency ranges. This paper presents the methods that were developed for evaluation of the microgravity environment in the structural dynamic range. An integrated finite element model of the space station was used to conduct analysis for the on-orbit microgravity environment. Methods were developed to evaluate sinusoidal, random, and transient disturbances. Sources of disturbances aboard the Space Station were quantified and forcing functions were assembled. The resulting acceleration levels at the experiment locations due to these disturbances were computed and assessed against the microgravity acceleration requirement curve.

Wetzel, John P.↗
DOE OSTI2026

Artificial intelligence methods for protein structure and interaction prediction: Recent advances and challenges

Recent advances in artificial intelligence have introduced novel methods for high-accuracy prediction of protein tertiary structures, protein complex structures, and interactions between proteins and other biomolecules, such as small molecules and nucleic acids. Such advancements are accelerating biomedical research and the development of new protein design and bioengineering methods among many other important biotechnology applications. Here, in this review, we outline the recent advances in protein-centric biomolecular structure and interaction prediction, highlight some major challenges in the field, and discuss potential directions to address them.

Morehead, Alex [Lawrence Berkeley National Laborat↗
NASA NTRS1993

Observations of the plasma flow in Comet P/Swift-Tuttle

We present direct ground based observations of the plasma flow sunward and tailward of the nucleus of Comet P/Swift-Tuttle. The observations are long-slit high resolution spectra of the H2O(+) emission centered at 6199 A with a velocity resolution of about 7 km/s FWHM and a spatial resolution of about 10 exp 4 km at the comet. Emission is visible from just inside the predicted position of the cometopause on the sunward side of the nucleus out to 5 x 10 exp 5 km on the tailward side. The deceleration of the solar plasma on the sunward side is clearly observed as is the acceleration of cometary ions into the tail. These observations show the effectiveness of ground based methods for the systematic study of cometary plasmas and point to the need for a better theoretical understanding of their acceleration mechanisms.

Brown, Michael E.↗
DOE OSTI2023

The Need for Nb3Sn Coated Cu Cavities for Future Accelerators

Based on current efforts in the U.S. on the novel concept of parallel-feed RF accelerator structures, and in the U.S. and abroad in producing Nb3Sn films on either Cu or bronze, we rec-ommend that the Particle Physics community foster R&D in Superconducting Nb3Sn coated Cu RF Cavities instead of costly bulk Nb. The paper includes methods to process the coated cavi-ties at temperatures consistent with Cu retaining its shape. A devoted global effort in develop-ing Cu cavity structures coated with Nb3Sn would make the ILC or Higgs factories more afforda-ble and more likely to be built. Not only do parallel-feed RF structures enable both higher ac-celerating gradients and higher efficiencies, but they would be applicable to both Cu and Nb3Sn coated Cu cells. Increased effort on these two techniques would synergize expenditures to-wards progress, which will converge on the choice of technology for the RF of an ILC or any fu-ture accelerator. The current methods of Nb3Sn coatings on Cu or bronze can be geared also towards standard cavity cells. In conclusion, the use of distributed coupling structure topology within improved performance parameters together with Nb3Sn coating technology can lead to a paradigm shift for superconducting linacs, with higher gradient, higher temperature of opera-tion, and reduced overall costs for any future collider.

43 PARTICLE ACCELERATORS↗
NASA NTRS1980

Methods for Monte Carlo simulation of the exospheres of the moon and Mercury

A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.

Hodges, R. R., Jr.↗
DOE OSTI2024

Rethinking materials simulations: Blending direct numerical simulations with neural operators

Abstract Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of the underlying evolution equations, the nature of multiscale spatiotemporal interactions, and the need to reach long-time integration. We develop a method that blends direct numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism to enable accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this hybrid framework on simulations of microstructure evolution via the phase-field method. Such simulations exhibit high spatial gradients and the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with large speed-up compared to DNS depending on the hybrid strategy utilized. This methodology is generalizable to a broad range of materials simulations, from solid mechanics to fluid dynamics, geophysics, climate, and more.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Technical Report for Bayesian Optimization and Reinforcement Learning for Beam Polarization Increase in the BNL Hadron Injectors

This project developed and evaluated physics-informed Bayesian learning and machine learning (ML)-based optimization methods for improving beam polarization preservation in the BNL hadron injector chain. The work focused on uncertainty-aware digital twin modeling, Bayesian calibration of accelerator simulations using beam measurements, and data-efficient optimization strategies including Bayesian optimization and reinforcement learning. These methods were applied to injector tuning and RF control problems in realistic accelerator settings to support improved operational robustness and readiness for RHIC operations and future Electron–Ion Collider facilities. No subject inventions were disclosed under this award.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Computational and Experimental Evaluation of Peroxide Oxidants for Amine-Peroxide Redox Polymerization

Amine–peroxide redox polymerization (APRP) is the prevalent method for producing radical-based polymers in the many industrial and medical applications where light or heat activation is impractical. We recently developed a detailed description of the APRP initiation process through a combined computational and experimental effort to show that APRP proceeds through SN2 attack by the amine on the peroxide, followed by the rate-determining homolysis of the resulting intermediate. Using this new mechanistic understanding, a variety of peroxides were computationally predicted to initiate APRP with fast kinetics. In particular, the rate of APRP initiation can be improved by radical and anion stabilization through increased p-electron conjugation or by increasing the electrophilicity of the peroxy bond through the addition of electron-withdrawing groups. On the other hand, the addition of electron-donating groups lowered the initiation rate. These design principles enabled the computational prediction of several new peroxides that exhibited improved initiation rates over the commonly used benzoyl peroxide. For example, the addition of nitro groups (NO2) to the para positions of benzoyl peroxide resulted in a theoretical radical generation rate of 1.9 × 10–9 s–1, which is ~150 times faster than the 1.3 × 10–11 s–1 radical generation rate observed with unsubstituted benzoyl peroxide. These accelerated kinetics enabled the development of a redox-based direct-writing process that exploited the extremely rapid reactivity of an optimized redox pair with a custom inkjet printer, capable of printing custom shapes from polymerizing resins without heat or light. Furthermore, the application of more rapid APRP kinetics could enable the acceleration of existing industrial processes, make new industrial manufacturing methods possible, and improve APRP compatibility with biomedical applications through reduced initiator concentrations that still produce rapid polymerization rates.

functional polymers↗