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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Modulated heat pulse propagation and partial transport barriers in chaotic magnetic fields

Direct numerical simulations of the time dependent parallel heat transport equation modeling heat pulses driven by power modulation in three-dimensional chaotic magnetic fields are presented. The numerical method is based on the Fourier formulation of a Lagrangian-Green's function method that provides an accurate and efficient technique for the solution of the parallel heat transport equation in the presence of harmonic power modulation. The numerical results presented provide conclusive evidence that even in the absence of magnetic flux surfaces, chaotic magnetic field configurations with intermediate levels of stochasticity exhibit transport barriers to modulated heat pulse propagation. In particular, high-order islands and remnants of destroyed flux surfaces (Cantori) act as partial barriers that slow down or even stop the propagation of heat waves at places where the magnetic field connection length exhibits a strong gradient. Results on modulated heat pulse propagation in fully stochastic fields and across magnetic islands are also presented. In qualitative agreement with recent experiments in large helical device and DIII-D, it is shown that the elliptic (O) and hyperbolic (X) points of magnetic islands have a direct impact on the spatio-temporal dependence of the amplitude of modulated heat pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Conversion of Resonance Parameters Between Wigner-Eisenbud R-matrix and Transition Matrix Pole Representation

The goal of this research is to develop a numerical code for translation between the current standard, Wigner-Eisenbud R-matrix parameters and a novel pole-representation of cross sections. The method follows Ducru et al. and constructs the conversion between these parametric representations of the scattering and reaction data. This pole representation, which expresses cross sections as a sum of simple poles (and their attendant residues), is examined in the context of the advantages provided by this compact, computationally efficient representation. These advantages include the ability to doppler broaden cross sections on-the-fly as well as a lower memory footprint when generating cross sections, an attractive feature to those interested in parallel GPU based Monte Carlo. Some conversion methods between R-matrix parameters and S-matrix poles have relied on curve fitting techniques. It is unknown weather these numerical methods necessarily preserve certain underlying physics properties of the standard R-matrix cross section model (such as unitarity). The direct conversion studied here aim to preserve such properties. This knowledge is of interest for future work into the generation of resonance parameter sensitivities.

CLUTCH↗
DOE OSTI2021

Metallization of conductive wires for solar cells

Methods of fabricating a solar cell, and system for electrically coupling solar cells, are described. In an example, the methods for fabricating a solar cell can include placing conductive wires in a wire guide, where conductive wires are placed over a first semiconductor substrate having first doped regions and second doped regions. The method can include aligning the conductive wires over the first and second doped regions, where the wire guide aligns the conductive wires substantially parallel to the first and second doped regions. The method can include bonding the conductive wires to the first and second doped regions. The bonding can include applying a mechanical force to the semiconductor substrate via a roller or bonding head of the wire guide, where the wire guide inhibits lateral movement of the conductive wires during the bonding.

Sewell, Richard Hamilton↗
DOE OSTI2020

A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet

We consider the scientifically challenging and policy-relevant task of understanding the past and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has shown a highly nonlinear threshold response to past climate forcings. Triggering such a threshold response through anthropogenic greenhouse gas emissions would drive drastic and potentially fast sea level rise with important implications for coastal flood risks. Previous studies have combined information from ice sheet models and observations to calibrate model parameters. These studies have broken important new ground but have either adopted simple ice sheet models or have limited the number of parameters to allow for the use of more complex models. These limitations are largely due to the computational challenges posed by calibration as models become more computationally intensive or when the number of parameters increases. Here, we propose a method to alleviate this problem: a fast sequential Monte Carlo method that takes advantage of the massive parallelization afforded by modern high-performance computing systems. We use simulated examples to demonstrate how our sample-based approach provides accurate approximations to the posterior distributions of the calibrated parameters. The drastic reduction in computational times enables us to provide new insights into important scientific questions, for example, the impact of Pliocene era data and prior parameter information on sea level projections. These studies would be computationally prohibitive with other computational approaches for calibration such as Markov chain Monte Carlo or emulation-based methods. We also find considerable differences in the distributions of sea level projections when we account for a larger number of uncertain parameters. For example, based on the same ice sheet model and data set, the 99th percentile of the Antarctic ice sheet contribution to sea level rise in 2300 increases from 6.5 m to 13.1 m when we increase the number of calibrated parameters from three to 11. With previous calibration methods, it would be challenging to go beyond five parameters. Here, this work provides an important next step toward improving the uncertainty quantification of complex, computationally intensive and decision-relevant models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hexagonal Geometries in MPACT

The MPACT code is a high-fidelity light-water reactor analysis code using whole-core pin-resolved neutron transport calculations on modern parallel-computing hardware. MPACT uses the 2D/1D method to solve 3D neutron transport problems by decomposing the problem into a stack of 2D slices, each of which is solved independently using the method of characteristics (MOC). The slices are then coupled axially using the P3 nodal expansion method (NEM-P3) for the 1D axial calculations. MPACT also employs the coarse mesh finite difference (CMFD) method to accelerate calculations. This manuscript details work supporting advanced reactor designs using hexagonal pins and hexagonal assemblies such as the VVER-1000. If performed correctly, MOC is geometry agnostic. However, MPACT previously had optimizations in place for Cartesian geometries, specifically in the modularization and current calculations. Sections 2 and 3 detail the changes made to MPACT to support MOC and CMFD calculations on hexagonal geometries. Section 4 reports results demonstrating solution consistency for problems run with and without CMFD acceleration, results demonstrating solution consistency when run in serial and parallel, and pincell results using the Monte Carlo code, McCard’s benchmark results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

WE-EF-303-04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies

Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed X-ray radiography convolved with a Gaussian kernel equal to the proton beam spot-size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set-up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non-optimized radiographies. These results represent a major step towards clinical application of proton radiography.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Multigrid Reduction in Time for Chaotic and Hyperbolic Problems (Final Report)

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations (PDEs), which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures. The chosen methodology for solving these problems parallel-in-time is multigrid, because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. Multigrid is already commonly used in many DOE simulations for scalably and optimally solving space-only PDE problems. The areas of hyperbolic and chaotic problems are chosen because of their relevance to problems of programmatic interest to DOE. However, these problems are also well-known to be difficult for parallelin-time methods, with the most common method, parareal, diverging in many cases. The current state-of-the-art for parallel-in-time at LLNL is the multigrid reduction in time (MGRIT) XBraid package, which also struggles for such problems, while still showing some improvement over parareal. In summary, new methods are needed for an efficient parallel-in-time scheme for hyperbolic and chaotic problems, and this work shall research promising new multigrid methods in this area. In particular, this work shall continue researching the directions from the current collaboration with Dr. Falgout, which are laid out in the work Toward Parallel in Time for Chaotic Dynamical Systems and showed the first known results of a parallel-in-time speedup for a chaotic problem. This work outlines two key improvements to XBraid for chaotic problems, the so-called “theta” and “delta-correction” methods. Here, these two improvements will be implemented in a high-performance but general way in XBraid and explored for more complicated problems. We will additionally research, as time allows, improvements to these techniques, as well as multigrid relaxation techniques based on Least Squares Shadowing (LSS by Wang) and a nonintrusive block tridiagonal solver based on MGRIT, called TriMGRIT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Methods for controlling pore morphology in aerogels using electric fields and products thereof

In one embodiment, an aerogel or xerogel includes column structures of a material having minor pores therein and major pores devoid of the material positioned between the column structures, where longitudinal axes of the major pores are substantially parallel to one another. In another embodiment, a method includes heating a sol including aerogel or xerogel precursor materials to cause gelation thereof to form an aerogel or xerogel and exposing the heated sol to an electric field, wherein the electric field causes orientation of a microstructure of the sol during gelation, which is retained by the aerogel or xerogel. In one approach, an aerogel has elongated pores extending between a material arranged in column structures having structural characteristics of being formed from a sol exposed to an electric field that causes orientation of a microstructure of the sol during gelation which is retained by the elongated pores of the aerogel.

36 MATERIALS SCIENCE↗
DOE OSTI2018

An overlapping domain decomposition method for large-scale problems

Discretization of dynamical models defined through partial differential equations leads to large-scale systems. Time-depending condition involves an iterative integration of such kind of systems. In this paper, a novel technique based on overlapped domain decomposition, without preconditioner and scalable, is presented. Due to the domain decomposition, subproblems are solved in parallel without communications, cutting off the computation time and optimizing the computational cost. This direct method describes an optimized parallel strategy to solve the initial problem, providing the exact solution, up to rounding errors. Moreover, it takes into account both physical nature of the problem and deriving numerical properties of the system. It is highly recommended in case of band matrices and a long time interval because of an increasing gain in terms of performance and computational cost with the number of integrations. A deep analysis of the computational cost concludes the paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Pilot study for compact microbeam radiation therapy using a carbon nanotube field emission micro-CT scanner

Purpose: Microbeam radiation therapy (MRT) is defined as the use of parallel, microplanar x-ray beams with an energy spectrum between 50 and 300 keV for cancer treatment and brain radiosurgery. Up until now, the possibilities of MRT have mainly been studied using synchrotron sources due to their high flux (100s Gy/s) and approximately parallel x-ray paths. The authors have proposed a compact x-ray based MRT system capable of delivering MRT dose distributions at a high dose rate. This system would employ carbon nanotube (CNT) field emission technology to create an x-ray source array that surrounds the target of irradiation. Using such a geometry, multiple collimators would shape the irradiation from this array into multiple microbeams that would then overlap or interlace in the target region. This pilot study demonstrates the feasibility of attaining a high dose rate and parallel microbeam beams using such a system. Methods: The microbeam dose distribution was generated by our CNT micro-CT scanner (100μm focal spot) and a custom-made microbeam collimator. An alignment assembly was fabricated and attached to the scanner in order to collimate and superimpose beams coming from different gantry positions. The MRT dose distribution was measured using two orthogonal radiochromic films embedded inside a cylindrical phantom. This target was irradiated with microbeams incident from 44 different gantry angles to simulate an array of x-ray sources as in the proposed compact CNT-based MRT system. Finally, phantom translation in a direction perpendicular to the microplanar beams was used to simulate the use of multiple parallel microbeams. Results: Microbeams delivered from 44 gantry angles were superimposed to form a single microbeam dose distribution in the phantom with a FWHM of 300μm (calculated value was 290 μm). Also, during the multiple beam simulation, a peak to valley dose ratio of ∼10 was found when the phantom translation distance was roughly 4x the beam width. The first prototype CNT-based x-ray tube dedicated to the development of compact MRT technology development was proposed and planned based on the preliminary experimental results presented here and the previous corresponding Monte Carlo simulations. Conclusions: The authors have demonstrated the feasibility of creating microbeam dose distributions at a high dose rate using a proposed compact MRT system. The flexibility of CNT field emission x-ray sources could possibly bring compact and low cost MRT devices to the larger research community and assist in the translational research of this promising new approach to radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Neoclassical parallel flow calculation in the presence of external parallel momentum sources in Heliotron J

A moment approach to calculate neoclassical transport in non-axisymmetric torus plasmas composed of multiple ion species is extended to include the external parallel momentum sources due to unbalanced tangential neutral beam injections (NBIs). The momentum sources that are included in the parallel momentum balance are calculated from the collision operators of background particles with fast ions. This method is applied for the clarification of the physical mechanism of the neoclassical parallel ion flows and the multi-ion species effect on them in Heliotron J NBI plasmas. It is found that parallel ion flow can be determined by the balance between the parallel viscosity and the external momentum source in the region where the external source is much larger than the thermodynamic force driven source in the collisional plasmas. This is because the friction between C{sup 6+} and D{sup +} prevents a large difference between C{sup 6+} and D{sup +} flow velocities in such plasmas. The C{sup 6+} flow velocities, which are measured by the charge exchange recombination spectroscopy system, are numerically evaluated with this method. It is shown that the experimentally measured C{sup 6+} impurity flow velocities do not contradict clearly with the neoclassical estimations, and the dependence of parallel flow velocities on the magnetic field ripples is consistent in both results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Non-Abelian 𝜈 =$\frac{1}{2}$ quantum Hall state in $Γ$ 8 valence band hole liquid

In the search for states with non-Abelian statistics, we explore the fractional quantum Hall effect in a system of two-dimensional (2D) charge carrier holes. We propose a method of mapping states of holes confined to a finite width quantum well in a perpendicular magnetic field to states in a spherical shell geometry. We take into account strong coupling between the spin and motion of charge parallel and perpendicular to the 2D layer. This method gives the single-particle hole states used in the exact diagonalization of systems with a small number of holes in the presence of Coulomb interactions, density matrix renormalization group, and topological entanglement entropy calculations. Furthermore, the hole quantum Hall state at half filling of the ground state in a magnetic field near the crossing of single-hole states is likely the Moore-Read Pfaffian state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Parallel Multigrid in Time and Space for Extreme-Scale Computational Science: Chaotic and Hyperbolic Problems

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations (PDEs), which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures. The chosen methodology for solving these problems parallel-in-time is multigrid, because multigrid (when it works) is a powerful, optimal, and scalable solver for discretized PDEs. Multigrid is already commonly used in many DOE simulations for scalably and optimally solving space-only PDE problems. The areas of hyperbolic and chaotic problems are chosen because of their relevance to problems of programmatic interest to DOE. However, these problems are also well-known to be difficult for parallelin-time methods, with the most common method, parareal, diverging in many cases. The current stateof-the-art for parallel-in-time at LLNL is the multigrid reduction in time (MGRIT) XBraid package, which also struggles for such problems, while still showing some improvement over parareal. In summary, new methods are needed for an efficient parallel-in-time scheme for hyperbolic and chaotic problems, and this work shall research promising new multigrid methods in this area. In particular, we take inspiration from the Least Squares Shadowing (LSS by Wang) approach for solving chaotic problems. Here, an optimization approach is able to find “well-conditioned” shadow trajectories/solutions to the original “ill-conditioned” chaotic problem. Thus, the new multigrid methods researched here also arise in an optimization context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Alternating Anderson–Richardson method: An efficient alternative to preconditioned Krylov methods for large, sparse linear systems

Here, we present the Alternating Anderson–Richardson (AAR) method: an efficient and scalable alternative to preconditioned Krylov solvers for the solution of large, sparse linear systems on high performance computing platforms. Specifically, we generalize the recently proposed Alternating Anderson–Jacobi (AAJ) method (Pratapa et al., 2016) to include preconditioning, discuss efficient parallel implementation, and provide serial MATLAB and parallel C/C++ implementations. In serial applications to nonsymmetric systems, we find that AAR is comparably robust to GMRES, using the same preconditioning, while often outperforming it in time to solution; and find AAR to be more robust than Bi-CGSTAB for the problems considered. In parallel applications to the Helmholtz and Poisson equations, we find that AAR shows superior strong and weak scaling to GMRES, Bi-CGSTAB, and Conjugate Gradient (CG) methods, using the same preconditioning, with consistently shorter times to solution at larger processor counts. Finally, in massively parallel applications to the Poisson equation, on up to 110,592 processors, we find that AAR shows superior strong and weak scaling to CG, with shorter minimum time to solution. We thus find that AAR offers a robust and efficient alternative to current state-of-the-art solvers, with increasing advantages as the number of processors grows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Distributed Reinforcement Learning with ADMM-RL

This paper presents a new algorithm for distributed Reinforcement Learning (RL). RL is an artificial intelligence (AI) control strategy such that controls for highly nonlinear systems over multi-step time horizons may be learned by experience, rather than directly computed on the fly by optimization. Here we introduce ADMM-RL, a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning that allows for integrating learned controllers as subsystems in generally convergent distributed control applications. ADMM has become the workhorse algorithm for distributed control, combining the advantages of dual decomposition (namely, enabling decoupled, parallel, distributed solution) with the advantages of the method of multipliers (namely, convexification/stability). Our ADMM-RL algorithm replaces one or more of the subproblems in ADMM with several steps of RL. When the nested iterations converge, we are left with a pretrained subsolver that can potentially increase the efficiency of the deployed distributed controller by orders of magnitude. We illustrate ADMM-RL in both distributed wind farm yaw control and distributed grid-aware demand aggregation for water heaters.

ADMM↗
DOE OSTI2018

Python-based in situ analysis and visualization

This work focuses on enabling the use of Python-based methods for the purpose of performing in situ analysis and visualization. This approach facilitates access to and use of a rapidly growing collection of Python-based, third-party libraries for analysis and visualization, as well as lowering the barrier to entry for user-written Python analysis codes. Beginning with a simulation code that is instrumented to use the SENSEI in situ interface, we present how to couple it with a Python-based data consumer, which may be run in situ, and in parallel at the same concurrency as the simulation. We present two examples that demonstrate the new capability. One is an analysis of the reaction rate in a proxy simulation of a chemical reaction on a 2D substrate, while the other is a coupling of an AMR simulation to Yt, a parallel visualization and analysis library written in Python. In the examples, both the simulation and Python in situ method run in parallel on a large-scale HPC platform.

Loring, Burlen↗
DOE OSTI2015

SU-E-T-350: Effective Point of Measurement and Total Perturbation Correction P for Parallel-Plate Ion Chambers in High-Energy Photon Beams

Purpose: This paper aims to determine the effective point of measurement and the total perturbation correction p of parallel-plate chambers for clinical photon dosimetry. Methods: The effective point of measurement (EPOM) was calculated using the EGSnrc Monte Carlo code system with the EGSnrc user code egs- chamber. Depth dose curves of the ionization chambers were calculated in a water phantom for several high energy photon spectra (4, 6, 10, 15, 18 MV-X). Different normalization criterions (normalization to the maximum of the depth dose curve and normalization to the value in 10 cm depth) have been applied. The EPOM was determined by shifting the normalized depth dose curve of a small water voxel against the depth ionization curve until the disagreement (calculated by the root mean square deviation) reaches a minimum. In addition, the total perturbation correction p was calculated by the ratio of the dose to water and the product of the dose determined in the chamber and the water to air stopping power ratio. Results: The EPOM varied slightly depending on the chosen normalization criterion. For all chambers the necessary shift of the EPOM decreased linearly with increasing beam quality specifier TPR{sub 20/10}. For the Roos and NACP chamber, the results were positive suggesting that the chambers need to be shifted towards the focus. For the Markus chamber, the required shift was negative and for the Advanced Markus chamber partly negative and partly positive. The total perturbation correction p was almost independent of the depth. Only for regions below 1 cm the perturbation correction deviated significantly from unity. Conclusion: In the present study, the effective point of measurement and the total perturbation correction p was determined for four parallel-plate ionization chambers and five clinical relevant photon spectra. Applying the calculated EPOM, the residual perturbation correction p was mostly depth independent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Crystal plasticity model of residual stress in additive manufacturing using the element elimination and reactivation method

Selective laser melting is receiving increasing interest as an additive manufacturing technique. Residual stresses induced by the large temperature gradients and inhomogeneous cooling process can favour the generation of cracks. In this work, a crystal plasticity finite element model is developed to simulate the formation of residual stresses and to understand the correlation between plastic deformation, grain orientation and residual stresses in the additive manufacturing process. The temperature profile and grain structure from thermal-fluid flow and grain growth simulations are implemented into the crystal plasticity model. An element elimination and reactivation method is proposed to model the melting and solidification and to reinitialize state variables, such as the plastic deformation, in the reactivated elements. The accuracy of this method is judged against previous method based on the stiffness degradation of liquid regions by comparing the plastic deformation as a function of time induced by thermal stresses. The method is used to investigate residual stresses parallel and perpendicular to the laser scan direction, and the correlation with the maximum Schmid factor of the grains along those directions. The magnitude of the residual stress can be predicted as a function of the depth, grain orientation and position with respect to the molten pool. The simulation results are directly comparable to X-ray diffraction experiments and stress–strain curves.

316 stainless steel↗