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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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31 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhancing scalability of a matrix-free eigensolver for studying many-body localization

We propose several techniques to enhance the parallel scalability of a matrix-free eigensolver designed for studying many-body localization (MBL) of quantum spin chain models with nearest-neighbor interactions and on-site disorder. This type of problem is computationally challenging because the dimension of the associated Hamiltonian matrix grows exponentially with respect to the number of spins L, and we need to average over different realizations of the random disorder to obtain relevant statistical behavior. For each disorder realization, we need to compute eigenvalues from different regions of the spectrum and their corresponding eigenvectors. In previous work, the interior eigenstates for a single eigenvalue problem are computed via the shift-and-invert Lanczos algorithm. Due to the extremely high memory footprint of the LU factorizations, this technique is not well suited for large L’s. For example, we need thousands of compute nodes on modern high performance computing infrastructures to go beyond L = 24. The matrix-free approach does not suffer from this memory bottleneck, however, its scalability is limited by a computation and communication load imbalance. To reduce this imbalance and to significantly enhance the scalability of the matrix-free eigensolver, we reorder the matrix and leverage the consistent space runtime, CSPACER. We also show its efficiency in managing irregular communication patterns at scale compared to optimized MPI non-blocking two-sided and one-sided RMA implementation variants. This effort enables us to study MBL for spin chains with a larger number of spins. The efficiency and effectiveness of the proposed algorithm is demonstrated by computing eigenstates on a massively parallel many-core high performance computer.

METIS↗
NASA NTRS1994

Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results

In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.

Meuer, Hans-Werner↗
DOE OSTI2017

Effective g factor of low-density two-dimensional holes in a Ge quantum well

Here we report the measurements of the effective g factor of low-density two-dimensional holes in a Ge quantum well. Using the temperature dependence of the Shubnikov-de Haas oscillations, we extract the effective g factor in a magnetic field perpendicular to the sample surface. Very large values of the effective g factor, ranging from ~13 to ~28, are observed in the density range of 1.4×10 10 cm -2 – 1.4×10 11 cm -2 . When the magnetic field is oriented parallel to the sample surface, the effective g factor is obtained from a protrusion in the magneto-resistance data that signify full spin polarization. In the latter orientation, a small effective g factor, ~1.3-1.4, is measured in the density range of 1.5×10 10 cm -2 –2×10 10 cm -2 . Finally, this very strong anisotropy is consistent with theoretical predictions and previous measurements in other 2D hole systems, such as InGaAs and GaSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

ELSI — An open infrastructure for electronic structure solvers

Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn–Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. As a result, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Individual and Simultaneous Imaging of ⁹⁹mTc and ¹⁷⁷Lu With a Preclinical Broad Energy-Spectrum CZT-Based SPECT

Radiopharmaceutical therapy has demonstrated a high efficacy in the treatment of various tumor types. One of the radionuclides already used in the clinic is 177Lu, a beta emitter that also emits several photons imageable with SPECT. Quantitative imaging of 177Lu is critical for developing new radiopharmaceuticals. Energy resolution is an important factor when imaging multiple photon emissions. Solid-state detectors offer a superior performance over scintillators, that are commonly used in commercially-available preclinical SPECT scanners. This study demonstrates the feasibility of 99m Tc and 177Lu quantitative imaging in mouse phantoms, individually and simultaneously, with a SPECT prototype built with four CdZnTe (CZT) detector heads and a custom-designed and energy-optimized parallel-hole tungsten collimator. With a custom implementation of the one-step late (OSL) image reconstruction algorithm, the system is capable of imaging energies from ~70 keV to 250 keV. Above 250 keV, images were significantly affected by septal penetration, consistent with the collimator design. A recovery coefficient within 25% was obtained for activities as low as 2 kBq/mL for 99m Tc and 45% for 177Lu. Compared to a commercial NaI-based preclinical SPECT (VECTor4/CT), our prototype showed a superior energy resolution (< 5% at 140 keV), a similar uniformity with a high-compact design.

Encarnação, Pedro M C C↗
DOE OSTI2023

Scaled ILU Smoothers for Navier-Stokes Pressure Projection

Incomplete LU (ILU) smoothers are effective in the algebraic multigrid (AMG) V-cycle for reducing high-frequency components of the error. However, the requisite direct triangular solves are comparatively slow on GPUs. Previous work has demonstrated the advantages of Jacobi iteration as an alternative to direct solution of these systems. Depending on the threshold and fill-level parameters chosen, the factors can be highly nonnormal and Jacobi is unlikely to converge in a low number of iterations. We demonstrate that row scaling can reduce the departure from normality, allowing us to replace the inherently sequential solve with a rapidly converging Richardson iteration. There are several advantages beyond the lower compute time. Scaling is performed locally for a diagonal block of the global matrix because it is applied directly to the factor. Further, an ILUT Schur complement smoother maintains a constant GMRES iteration count as the number of MPI ranks increases, and thus parallel strong-scaling is improved. Our algorithms have been incorporated into hypre, and we demonstrate improved time to solution for linear systems arising in the Nalu-Wind and PeleLM pressure solvers. For large problem sizes, GMRES+AMG executes at least five times faster when using iterative triangular solves compared with direct solves on massively parallel GPUs.

algebraic multigrid↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2017

Intrinsically low thermal conductivity from a quasi-one-dimensional crystal structure and enhanced electrical conductivity network via Pb doping in SbCrSe 3

The development of new routes for the production of thermoelectric materials with low-cost and high-performance characteristics has been one of the long-term strategies for saving and harvesting thermal energy. We report a new approach for improving thermoelectric properties by employing the intrinsically low thermal conductivity of a quasi-one-dimensional (quasi-1D) crystal structure and optimizing the power factor with aliovalent ion doping. As an example, we demonstrated that SbCrSe 3 , in which two parallel chains of CrSe 6 octahedra are linked by antimony atoms, possesses a quasi-1D property that resulted in an ultra-low thermal conductivity of 0.56 W m -1 K -1 at 900 K. After maximizing the power factor by Pb doping, the peak ZT value of the optimized Pb-doped sample reached 0.46 at 900 K, which is an enhancement of 24 times that of the parent SbCrSe 3 structure. The mechanisms that lead to low thermal conductivity derive from anharmonic phonons with the presence of the lone-pair electrons of Sb atoms and weak bonds between the CrSe 6 double chains. Our results shed new light on the design of new and high-performance thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗
NASA NTRS1994

Particle-in-cell simulations of the critical ionization velocity effect in finite size clouds

The critical ionization velocity (CIV) mechanism in a finite size cloud is studied with a series of electrostatic particle-in-cell simulations. It is observed that an initial seed ionization, produced by non-CIV mechanisms, generates a cross-field ion beam which excites a modified beam-plasma instability (MBPI) with frequency in the range of the lower hybrid frequency. The excited waves accelerate electrons along the magnetic field up to the ion drift energy that exceeds the ionization energy of the neutral atoms. The heated electrons in turn enhance the ion beam by electron-neutral impact ionization, which establishes a positive feedback loop in maintaining the CIV process. It is also found that the efficiency of the CIV mechanism depends on the finite size of the gas cloud in the following ways: (1) Along the ambient magnetic field the finite size of the cloud, L (sub parallel), restricts the growth of the fastest growing mode, with a wavelength lambda (sub m parallel), of the MBPI. The parallel electron heating at wave saturation scales approximately as (L (sub parallel)/lambda (sub m parallel)) (exp 1/2); (2) Momentum coupling between the cloud and the ambient plasma via the Alfven waves occurs as a result of the finite size of the cloud in the direction perpendicular to both the ambient magnetic field and the neutral drift. This reduces exponentially with time the relative drift between the ambient plasma and the neutrals. The timescale is inversely proportional to the Alfven velocity. (3) The transvers e charge separation field across the cloud was found to result in the modulation of the beam velocity which reduces the parallel heating of electrons and increases the transverse acceleration of electrons. (4) Some energetic electrons are lost from the cloud along the magnetic field at a rate characterized by the acoustic velocity, instead of the electron thermal velocity. The loss of energetic electrons from the cloud seems to be larger in the direction of plasma drift relative to the neutrals, where the loss rate is characterized by the neutral drift velocity. It is also shown that a factor of 4 increase in the ambient plasma density, increases the CIV ionization yield by almost 2 orders of magnitude at the end of a typical run. It is concluded that a larger ambient plasma density can result in a larger CIV yield because of (1) larger seed ion production by non-CIV mechanisms, (2) smaller Alfven velocity and hence weak momentum coupling, and (3) smaller ratio of the ion beam density to the ambient ion density, and therefore a weaker modulation of the beam velocity. The simulation results are used to interpret various chemical release experiments in space.

Moghaddam-Taaheri, E.↗
DOE OSTI2021

Mechanistic understanding of support effect on the activity and selectivity of indium oxide catalysts for CO 2 hydrogenation

Herein we present a mechanistic study on the support effect (ZrO 2 and CeO 2 ) of In 2 O 3 catalysts in CO 2 hydrogenation by a combined experimental and computational approach. Kinetic experiments and surface characterization suggested that the activity of In 2 O 3 catalysts cannot be simply correlated with the abundance of surface oxygen vacancies (O v ) formed by either H 2 -reduction or thermal treatment, which has been frequently invoked in previous studies. The support effect should originate from the electronic interactions between In 2 O 3 and the support oxide, rather than geometric factors or the difference in the particle size of In 2 O 3 . Theoretical modelling revealed that surface O v facilitate the formation and stabilization of the formate (HCOO*) intermediate. While a carbonate-like structure is favored for CO 2 adsorption on CeO 2 -supported or unsupported In 2 O 3 catalysts, CO 2 tends to bind strongly in a bent configuration on the O v site at the In 2 O 3 -ZrO 2 interface. The distinct CO 2 adsorption structures on different supported In 2 O 3 catalysts may account for the different reaction energy profiles in the subsequent hydrogenation reactions, especially the rate-limiting step, i.e., hydrogenation of HCOO* to CH 2 O* and methoxy (CH 3 O*). The relatively higher methanol selectivity of In 2 O 3 catalyst supported on ZrO 2 with respect to that on CeO 2 are suggested to stem from the greater energy difference (Δ$E_a$) between the parallel hydrogenation and C-O bond cleavage of HCOO*, which leads to the formation of methanol and CO, respectively. We report this study underlines the important role of metal-oxide-interface in determining the catalytic behavior of oxide-supported In 2 O 3 catalysts in CO 2 conversion.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Extreme Transverse Magnetoresistance in TiZn 16

Extreme magnetoresistance (XMR) is a phenomenon characterized by an increase in resistance by factors of 10 4 –10 7 % when a magnetic field is applied. This phenomenon is found in a number of semimetals such as WTe 2 , PtSn 4 , Cd 3 As 2 , and LaSb. The origin of XMR is still hotly debated, possibly with different materials having different (or multiple) explanations. Extreme transverse magnetoresistance of up to 8000% at 14 T and 1.8 K is measured in TiZn 16 , a semimetal with a multitude of bands crossing the Fermi energy, akin to PtSn 4 . The magnetoresistance is suppressed when the magnetic field is rotated to be parallel to the applied current, similar to PtSn 4 and PdSn 4 . The resistance of TiZn 16 follows Kohler's rule, but displays different behavior under an applied transverse field and under a longitudinal magnetic field, suggesting distinct electrical phases. Also present are Shubnikov-de Haas and de Haas-van Alphen oscillations with a transverse magnetic field up to 43 T, showing that despite an insulator-like temperature-resistance curve, charge carriers are still present. This positions TiZn 16 as an interesting addition to the investigation of XMR materials as a multi-band metal with complex Fermi surface geometries.

extreme magnetoresistance↗