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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Implosion dynamics of triple-nozzle gas-puff z pinches on COBRA

Experiments on the 1-MA, 220-ns COBRA generator at Cornell University were conducted to provide detailed measurements of structured cylindrical gas-puff z pinches. In the experiments, a 7 cm diameter triple-nozzle gas valve assembly with concentric outer and inner annular nozzles and a central gas jet initialize the z-pinch load with various working gases, radial density profiles, and externally applied axial magnetic fields. Planar laser-induced fluorescence provides a measure of the initial neutral gas density of the load, while three-frame laser shearing interferometry and multi-frame extreme ultraviolet (XUV) cameras reveal the formation and propagation of a magneto-Rayleigh–Taylor (MRT) unstable shock layer. Implosion trajectories are compared to simple, experimentally informed models and found to be in good agreement. Differences in the structure of the accelerating plasma sheath and evolution of the MRT instability are observed for different gas species and axial magnetic field strengths, correlating with differences in pinch uniformity and x-ray emission. Here, the average instability growth is compared to linear MRT theory predictions using the instantaneous acceleration of the best-fit implosion models and characteristic instability wavelength, with the effective Atwood number and seed perturbation size as fit parameters. For high density argon center jets, ionization prior to the arrival of the imploding plasma sheath suggests a heating mechanism consistent with photoionization by XUV self-emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Magnetically Levitated and Constrained Flywheel Energy Storage System

The concept of using linear induction motors to lift, constrain, accelerate, and decelerate a large-scale flywheel is proposed, and some of the advantages are investigated. Calculations for a Magnetically Levitated Energy Storage System (MLES) are performed that compare a single large scale MLES with a current state of the art flywheel energy storage system in order to show the relative differences and advantages of such a system. The system that is used for comparison is a typical Beacon Power flywheel energy system. This is currently one of the state-of-the-art flywheel energy storage systems and so it can be used to provide a basic data set to compare to an MLES system.

VanOsdol, John↗
DOE OSTI2021

Data-driven acceleration of thermal radiation transfer calculations with the dynamic mode decomposition and a sequential singular value decomposition

In this work, we present a method for accelerating discrete ordinates radiative transfer calculations for radiative transfer. Our method works with nonlinear positivity fixes, in contrast to most acceleration schemes. The method is based on the dynamic mode decomposition (DMD) and using a sequence of rank-one updates to compute the singular value decomposition needed for DMD. Using a sequential method allows us to automatically determine the number of solution vectors to include in the DMD acceleration. We present results for slab geometry discrete ordinates calculations with the standard temperature linearization. Compared with positive source iteration, our results demonstrate that our acceleration method reduces the number of transport sweeps required to solve the problem by a factor of about 3 on a standard diffusive Marshak wave problem, a factor of several thousand on a cooling problem where the effective scattering ratio approaches unity, and a factor of 20 improvement in a realistic, multimaterial radiating shock problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Advanced Modeling of Plasma-based Particle Accelerators

Plasma-based acceleration (PBA) driven by an intense laser (LWFA) or particle beam (PWFA) can produce ultra-high accelerating fields in excess of a GV/cm. PBA could substantially reduce the size and cost of future linear collider facilities if deployed successfully. PBA enables compact tabletop accelerators that can provide lower energy GeV-class beams in a laboratory setting. PBA enables high quality beam generation suitable for x-ray free electron lasers (XFEL) via controllable methods of self-injection. Challenges in modeling and optimization of multi-stage PBA motivate the need for exascale computing and state-of-the-art PIC codes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis

Integrating renewable resources within the transmission grid at a wide scale poses significant challenges for economic dispatch as it requires analysis with more optimization parameters, constraints, and sources of uncertainty. This motivates the investigation of more efficient computational methods, especially those for solving the underlying linear systems, which typically take more than half of the overall computation time. In this paper, we present our work on sparse linear solvers that take advantage of hardware accelerators, such as graphical processing units (GPUs), and improve the overall performance when used within economic dispatch computations. We treat the problems as sparse, which allows for faster execution but also makes the implementation of numerical methods more challenging. We present the first GPU-native sparse direct solver that can execute on both AMD and NVIDIA GPUs. We demonstrate significant performance improvements when using high-performance linear solvers within alternating current optimal power flow (ACOPF) analysis. Furthermore, we demonstrate the feasibility of getting significant performance improvements by executing the entire computation on GPU-based hardware. Finally, we identify outstanding research issues and opportunities for even better utilization of heterogeneous systems, including those equipped with GPUs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

High-order matrix-free incompressible flow solvers with GPU acceleration and low-order refined preconditioners

In this work, we present a matrix-free flow solver for high-order finite element discretizations of the incompressible Navier-Stokes and Stokes equations with GPU acceleration. For high polynomial degrees, assembling the matrix for the linear systems resulting from the finite element discretization can be prohibitively expensive, both in terms of computational complexity and memory. For this reason, it is necessary to develop matrix-free operators and preconditioners, which can be used to efficiently solve these linear systems without access to the matrix entries themselves. The matrix-free operator evaluations utilize GPU-accelerated sum-factorization techniques to minimize memory movement and maximize throughput. The preconditioners developed in this work are based on a low-order refined methodology with parallel subspace corrections, as described for diffusion problems in [1]. The saddle-point Stokes system is solved using block-preconditioning techniques, which are robust in mesh size, polynomial degree, time step, and viscosity. For the incompressible Navier-Stokes equations, we make use of projection (fractional step) methods, which require Helmholtz and Poisson solves at each time step. The performance of our flow solvers is assessed on several benchmark problems in two and three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Compact, Achromatic Non-scaling FFAG Accelerator for HEP, Commercial and Medical Applications (CRADA FRA-2008-0005 Final Report)

Proton and light-ion accelerators have many research and medical applications, but the current state of technology in accelerators severely limits their widespread use: (1) synchrotrons have an intrinsic low duty cycle and become quite large for light ions; and (2) cyclotrons do not have energy variability and require complex superconducting magnets for high energy. A new concept in non-scaling Fixed-Field Alternating-Gradient (FFAGs) has been invented that incorporates both the energy variability of the synchrotron and the high duty cycle of the cyclotron. The concept uses normal-conducting, combined-function magnets that apply only constant (dipole) and linear-gradient (quadrupole) fields to stabilize the accelerator. This project will develop an optimized design for a new non-scaling and cost-effective innovation in FFAG accelerators. The accelerator design will have optics that can stably accelerate protons to 250 MeV (or higher) and carbon ions to =200 MeV, an energy considered ideal for radiation therapy. Phase I will optimize, fully simulate, and demonstrate the feasibility of this accelerator. Commercial Applications and other Benefits as described by the awardee: The fixed-field acceleration concept should eliminate some of the most pronounced technical difficulties, expense, maintenance, and required expertise faced in conventional proton and light-ion accelerators. In addition to the application for high energy physics, these accelerators should have application in cancer treatment, radiopharmaceuticals, and medical isotope production, and materials science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Optimization Stability in Excited-State-Specific Variational Monte Carlo

Here, we investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method's stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

GPU acceleration of all-electron electronic structure theory using localized numeric atom-centered basis functions

We present an implementation of all-electron density-functional theory for massively parallel GPU-based platforms, using localized atom-centered basis functions and real-space integration grids. Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the update of the electron density, the integration of the real-space Hamiltonian matrix, and calculation of Pulay forces. To assess the performance of our GPU implementation, we performed benchmarks on three different architectures using a 103-material test set. We find that operations which rely on dense serial linear algebra show dramatic speedups from GPU acceleration: in particular, SCF iterations including force and stress calculations exhibit speedups ranging from 4.5 to 6.6. For the architectures and problem types investigated here, this translates to an expected overall speedup between 3–4 for the entire calculation (including non-GPU accelerated parts), for problems featuring several tens to hundreds of atoms. Additional calculations for a 375-atom Bi2Se3 bilayer show that the present GPU strategy scales for large-scale distributed-parallel simulations.

42 ENGINEERING↗
DOE OSTI2023

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗
DOE OSTI2022

Deep uGMRT observations of the ELAIS-North 1 field: statistical properties of radio–infrared relations up to z ∼ 2

ABSTRACT Comprehending the radio–infrared (IR) relations of the faint extragalactic radio sources is important for using radio emission as a tracer of star formation in high redshift (z) star-forming galaxies (SFGs). Using deep uGMRT observations of the ELAIS-N1 field in the 0.3–0.5 GHz range, we study the statistical properties of the radio–IR relations and the variation of the ‘q-parameter’ up to z = 2 after broadly classifying the faint sources as SFGs and AGN. We find the dust temperature (Tdust) to increase with z. This gives rise to $q_{\rm 24\,\mu m}$, measured at $24\, \mu$m, to increase with z as the peak of IR emission shifts towards shorter wavelengths, resulting in the largest scatter among different measures of q-parameters. $q_{\rm 70\,\mu m}$ measured at $70\, \mu$m, and qTIR using total-IR (TIR) emission are largely unaffected by Tdust. We observe strong, non-linear correlations between the radio luminosities at 0.4 and 1.4 GHz with $70\, \mu$m luminosity and TIR luminosity(LTIR). To assess the possible role of the radio-continuum spectrum in making the relations non-linear, for the first time we study them at high z using integrated radio luminosity (LRC) in the range 0.1–2 GHz. In SFGs, the LRC–LTIR relation remains non-linear with a slope of 1.07 ± 0.02, has a factor of 2 lower scatter compared to monochromatic radio luminosities, and $q^{\rm RC}_{\rm TIR}$ decreases with z as $q^{\rm RC}_{\rm TIR}= (2.27 \pm 0.03)\, (1+z)^{-0.12 \pm 0.03}$. A redshift variation of q is a natural consequence of non-linearity. We suggest that a redshift evolution of magnetic field strengths and/or cosmic ray acceleration efficiency in high-z SFGs could give rise to non-linear radio–IR relations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Perspectives on the generation of electron beams from plasma-based accelerators and their near and long term applications

This article first gives the authors' perspectives on how the field of plasma-based acceleration (PBA) developed and how the current experiments, theory, and simulations are motivated by long term applications of PBA to a future linear collider and an x-ray free electron laser. Here, we then focus on some early applications that will likely emerge from PBA research such as electron beam radiotherapy, directional but incoherent x-ray beams for science and technology, near single cycle continuously tunable infrared pulses for spectroscopy, and non-perturbative quantum electrodynamics enabled by PBA electron beams. In our opinion, these near term applications could be developed within the next decade with a concerted effort by the community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Modeling and implementation of vertical excursion FFA in the Zgoubi ray-tracing code

Vertical Fixed Field Accelerators (vFFAs) feature complex and highly non-linear magnetic fields, which require simulation codes allowing step-wise particle tracking. Methods to model the 3D magnetic field of scaling vFFAs have been developed in the ray-tracing code Zgoubi. The field modeling and particle tracking methods include the field non-linearities, the fringe fields, and the field superposition of neighboring magnets. The procedure implements the vFFA analytical field expressions, allowing design studies and parameter optimizations using the Zgoubi built-in fit method. The vFFA procedure has been applied to a ten-fold symmetry ring with a triplet focusing structure designed to accelerate protons from 3 MeV to 12 MeV and studied under the ISIS-II proton driver prototype project. Results from particle tracking in externally generated 3D semi-analytical field maps and the developed vFFA analytical model are shown to be in excellent agreement.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Kink-driven magnetic reconnection in relativistic jets: consequences for X-ray polarimetry of BL Lacs

ABSTRACT We investigate with relativistic MHD (magnetohydrodynamic) simulations the dissipation physics of BL Lac jets, by studying the synchrotron polarization signatures of particles accelerated by the kink instability in a magnetically dominated plasma column. The non-linear stage of the kink instability generates current sheets, where particles can be efficiently accelerated via magnetic reconnection. We identify current sheets as regions where s = Jδ/B is above some predefined threshold (where B is the field strength, J is the current density, and δ is the grid scale), and assume that the particle injection efficiency scales as ∝J2. X-ray emitting particles have short cooling times, so they only probe the field geometry of their injection sites. In contrast, particles emitting in the optical band, which we follow self-consistently as they propagate away from their injection sites while cooling, sample a larger volume, and so they may be expected to produce different polarimetric signatures. We find that the degree of polarization is roughly the same between X-ray and optical bands, because even the optical emitting particles do not travel far from the current sheet where they were injected, due to lack of sufficient kink-generated turbulence. The polarization angle shows a different temporal evolution between the two bands, due to the different regions probed by X-ray and optical emitting particles. In view of the upcoming IXPE satellite, our results can help constrain whether kink-induced reconnection (as opposed to shocks) can be the source of multiwavelength emission from BL Lacs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Geant4 based positron beam source (GPos) v1.0

GPos is a software that was created to determine the properties of positron beams resulting from the interaction of the LBNL BELLA center PetaWatt laser-driven plasma-capillary accelerated electron beam and the atoms of a thin solid target. GPos is written in C++, easily compiled with cmake and the spack package manager, which allows for multi-thread and MPI parallel computing. Its functions expand on the Geant4 toolkit library and allow for propagation of the modelled particles through vacuum drift distances with a focusing element (thin lens approximation). Users can change beam-foil-drift-lens parameters - to adapt GPos to other particle sources and infrastructures - in a simple input file. The code particle data output format, openPMD, which is compatible, for example, with the input of the ECP WarpX project code used to explore the physics of particle acceleration in plasmas. Using GPos in conjunction to WarpX allowed us to test various configurations for designing a high-quality and high-energy positron source at BELLA -required for us to address positron acceleration challenges in the development of future linear colliders. GPos can also be advantageous when tackling the physics of muon sources for future muon colliders as well as for the investigation of positron sources in lower energy regimes for applications like annihilation spectroscopy and astrophysical gamma-ray-bursts.

Pinto de Almeida Amorim, Ligia↗
DOE OSTI2025

Ipopt Interface to Re::Solve Linear Solver

The software provides Ipopt optimization package an interface to the Re::Solve linear solver library. Re::Solve features GPU-resident direct and iterative linear solvers that could be used to accelerate optimization computations.

Alam, Maksudul [Oak Ridge National Laboratory (ORN↗