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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distributed Macroscopic Traffic Simulation with Open Traffic Models

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

macro-scopic traffic simulation↗
NASA NTRS1990

Distributed deformation and block rotation in 3D

The authors address how block rotation and complex distributed deformation in the Earth's shallow crust may be explained within a stationary regional stress field. Distributed deformation is characterized by domains of sub-parallel fault-bounded blocks. In response to the contemporaneous activity of neighboring domains some domains rotate, as suggested by both structural and paleomagnetic evidence. Rotations within domains are achieved through the contemporaneous slip and rotation of the faults and of the blocks they bound. Thus, in regions of distributed deformation, faults must remain active in spite of their poor orientation in the stress field. The authors developed a model that tracks the orientation of blocks and their bounding faults during rotation in a 3D stress field. In the model, the effective stress magnitudes of the principal stresses (sigma sub 1, sigma sub 2, and sigma sub 3) are controlled by the orientation of fault sets in each domain. Therefore, adjacent fault sets with differing orientations may be active and may display differing faulting styles, and a given set of faults may change its style of motion as it rotates within a stationary stress regime. The style of faulting predicted by the model depends on a dimensionless parameter phi = (sigma sub 2 - sigma sub 3)/(sigma sub 1 - sigma sub 3). Thus, the authors present a model for complex distributed deformation and complex offset history requiring neither geographical nor temporal changes in the stress regime. They apply the model to the Western Transverse Range domain of southern California. There, it is mechanically feasible for blocks and faults to have experienced up to 75 degrees of clockwise rotation in a phi = 0.1 strike-slip stress regime. The results of the model suggest that this domain may first have accommodated deformation along preexisting NNE-SSW faults, reactivated as normal faults. After rotation, these same faults became strike-slip in nature.

Scotti, Oona↗
DOE OSTI2025

Parallel sorting algorithm classification: is manual instrumentation necessary?

Understanding parallel algorithms is crucial for accelerating scientific simulations on complex, distributed memory, high-performance computers. Modern algorithm classification approaches learn semantics directly from source code to differentiate between algorithms, however, accessing source code is not always possible. We can learn about parallel algorithms from observing their performance, as programs running the same algorithms and using the same hardware should exhibit similar performance characteristics. We present an approach to learn algorithm classes from parallel performance data directly in order to classify algorithms without access to the source code. We extend previous work to enable classifying parallel sorting algorithms using automatic instrumentation instead of requiring manual region annotations in the source code. In this work, we design and demonstrate a study for classification of parallel sorting algorithms using parallel performance data collected from automatic instrumentation, and evaluate the performance of our new methodology on classification. We leverage Caliper to collect the performance data, Thicket for our exploratory data analysis (EDA), and PyTorch and Scikit-learn to evaluate the effectiveness of random forests, support vector machines (SVMs), decision trees, neural networks, and logistic regressions on parallel performance data. Additionally, we study noise in parallel performance data, whether the removal of noise and pre-processing of the data is necessary to accurately classify parallel sorting algorithms, and determine the effectiveness of features created from performance data. In conclusion, we demonstrate classification accuracy for these five different models of up to 97.7% across four different parallel algorithm classes.

Algorithm Classification↗
NASA NTRS1999

Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D showed that HPF has potential to be a high level language for parallelization of CFD applications. The use of HPF requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement and data granularity. Since HPF hides data movement from the user even with this knowledge it is easy to overlook pieces of the code causing low performance of the application. In order to simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and partially implemented ADAPT (Automatic Data Distribution and Placement Tool). The ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level or inter application level. ADAPT is designed to annotate existing CFD FORTRAN application performing computations on single or multiple grids. On each grid the application can considered as a sequence of operators each applied to a set of variables defined in a particular grid domain. The operators can be classified as implicit, having data dependences, and explicit, without data dependences. In order to parallelize an explicit operator it is sufficient to create a template for the domain of the operator, align arrays used in the operator with the template, distribute the template, and declare the loops over the distributed dimensions as INDEPENDENT. In order to parallelize an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator then the loop which implements the operator can be declared as INDEPENDENT.

Frumkin, Michael↗
NASA NTRS1980

Evidence for parallel electric field particle acceleration in the dayside auroral oval

Electron and ion energy spectra and electron pitch angle distributions are presented for two sounding rocket flights in the dayside auroral zone. At times, effects of dc electric fields parallel to the magnetic field are evident in that: (1) within precipitation features, protons are decelerated by an amount of energy consistent with that which electrons gain and (2) electrons are sometimes aligned to within 3 deg (full width at half maximum) of the magnetic field. A maximum altitude for the accelerating region of several thousand kilometers is deduced from the narrow width of the pitch angle distribution and also from time-of-flight delays between the observation of accelerated electrons and decelerated protons.

Torbert, R. B.↗
DOE OSTI2020

Genarris 2.0: A Random Structure Generator for Molecular Crystals

Genarris is an open source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. A MPI-based parallelization scheme has been implemented, which facilitates the seamless sequential execution of user-defined workflows. A new method for estimating the unit cell volume based on the single molecule structure has been developed using a machine-learned model trained on experimental structures. A new algorithm has been implemented for generating crystal structures with molecules occupying special Wyckoff positions. A new hierarchical structure check procedure has been developed to detect unphysical close contacts efficiently and accurately. New intermolecular distance settings have been implemented for strong hydrogen bonds. To demonstrate these new features, we study two specific cases: benzene and glycine. Genarris finds the experimental structures of the two polymorphs of benzene and the three polymorphs of glycine. Program summary Program Title: Genarris 2.0 Program Files doi: http://dx.doi.org/10.17632/grx6mz4pjn.1 Licensing provisions: BSD-3 Clause Programming language: Python, C External routines/libraries: Spglib, ASE, pymatgen, SciPy, mpi4py, scikit-learn, PyTorch, FHI-aims. Nature of problem: Molecular crystal structure prediction. Solution method: Genarris 2.0 generates molecular crystal structures over the 230 space groups, on general and special Wyckoff positions, using physical constraints. Down-sampling of the generated structures may be performed subsequently, based on molecular crystal packing descriptors and an unsupervised machine learning algorithm. Lastly, ab initio structure relaxation may be performed for the final pool. Depending on the user-defined workflow implemented, Genarris may be used to generate diverse molecular crystal datasets to seed evolutionary algorithms or to train machine learning algorithms or as a standalone crystal structure prediction method. Restrictions: For crystal structure generation, the molecule of interest must be semi-rigid with no bond rotational degrees of freedom. Unusual features: Genarris 2.0 is a highly distributed program, making use of MPI for Python parallelization. The user has the ability to design and implement workflows by executing a user-defined list of procedures. Genarris 2.0 offers new features including a machine learning model for estimating the molecular volume in the solid state from the single molecule structure, structure generation in special Wyckoff positions of space groups, hierarchical structure checks including rigorous treatment of non-orthogonal structures, and clustering and down-selection workflows combining first principles simulations with machine learning. (C) 2020 Elsevier B.V. All rights reserved.

Crystal structure prediction↗
NASA NTRS1985

LANDSAT-D investigations in snow hydrology

Work undertaken during the contract and its results are described. Many of the results from this investigation are available in journal or conference proceedings literature - published, accepted for publication, or submitted for publication. For these the reference and the abstract are given. Those results that have not yet been submitted separately for publication are described in detail. Accomplishments during the contract period are summarized as follows: (1) analysis of the snow reflectance characteristics of the LANDSAT Thematic Mapper, including spectral suitability, dynamic range, and spectral resolution; (2) development of a variety of atmospheric models for use with LANDSAT Thematic Mapper data. These include a simple but fast two-stream approximation for inhomogeneous atmospheres over irregular surfaces, and a doubling model for calculation of the angular distribution of spectral radiance at any level in an plane-parallel atmosphere; (3) incorporation of digital elevation data into the atmospheric models and into the analysis of the satellite data; and (4) textural analysis of the spatial distribution of snow cover.

Dozier, J.↗
NASA NTRS1989

Some fast elliptic solvers on parallel architectures and their complexities

The discretization of separable elliptic partial differential equations leads to linear systems with special block tridiagonal matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconstant coefficients. A method was recently proposed to parallelize and vectorize BCR. In this paper, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational compelxity lower than that of parallel BCR.

Gallopoulos, E.↗
NASA NTRS1982

DE-2 photoelectron measurements consistent with a large scale parallel electric field over the polar cap

Winningham and Heikkila (1974) presented observations of various polar cap particle morphologies. They interpreted observations of 'anomalous' photoelectron angular distribution over the polar caps to be indicative of a large scale, outwardly directed, parallel electric field over the polar cap. The parallel field was observed to be spatially and/or temporarily variable. However, results obtained by Winningham and Heikkila have one weakness, which is related to the lack of simultaneous observations at many pitch angles. The present investigation is, therefore, concerned with the presentation of results from Dynamics Explorer 2 (DE-2) which confirm the experimental results of Winningham and Heikkila. It is concluded that the earth's polar caps act much like any conductor immersed in a plasma and illuminated by sunlight. DE-1 and DE-2 would then represent tiny point probes examining the internal details in the sheath region of the polar cap.

Winningham, J. D.↗
DOE OSTI2023

Separation of rare earth element radioisotopes by reverse-phase high-speed counter-current chromatography

Analytical scale purification of rare earth element (REE) radioisotopes is typically accomplished using cation-exchange resins (e.g. AG 50W-X8) and high-performance liquid chromatography (HPLC). Despite the variety of improvements made since the development of this separation process in the 1950s, nearest neighbor separations remain a challenge, as does the issue of irreversible sample adsorption. Herein, we report a study that evaluates the potential of high-speed counter-current chromatography (HSCCC) as an alternative method for purifying REE elements, with specific reference to separations of fission product REE of interest to nuclear forensics. Complementary HSCCC REE separation experiments, one spiked with radiotracer and REE fission product activity, allowed for in depth analysis of resulting fractions from both an elemental (inductively coupled plasma atomic emission spectroscopy, ICP-AES) and radiological (gamma-ray spectrometry, beta counting) purity perspective. The highly reproducible nature of separation profiles generated from HSCCC instruments was leveraged to simplify work-up of samples containing radioisotopes. Subsequent radioanalytical evaluation revealed minimal carryover of Eu into neighboring Sm and Tb fractions (as indicated by presence of 150Eu), and trace contamination of the Tb fraction with Y (as indicated by presence of 91Y). Subtle differences in stationary phase retention across the two columns were reflected in significant variations in decontamination factors of duplicate parallel separations. Furthermore, these differences paired with obtained distribution of radioisotopes provided valuable insights into future improvements. Collectively, this study represents a significant step forward in development of HSCCC technology for task specific REE radioisotope purification.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

PETSc DMNetwork: A Library for Scalable Network PDE-Based Multiphysics Simulations

We present DMNetwork, a high-level package included in the PETSc library for the simulation of multiphysics phenomena over large-scale networked systems. The library aims at applications that have networked structures such as those in electrical, gas, and water distribution systems. DMNetwork provides data and topology management, parallelization for multiphysics systems over a network, and hierarchical and composable solvers to exploit the problem structure. DMNetwork eases the simulation development cycle by providing the necessary infrastructure through simple abstractions to define and query the network components. This article presents the design of DMNetwork, illustrates its user interface, and demonstrates its ability to solve multiphysics systems, such as an electric circuit, a network of power grid and water subnetworks, and transient hydraulic systems over large networks with more than 2 billion variables on extreme-scale computers using up to 30,000 processors.

extreme-scale computing↗
DOE OSTI2026

HydraGNN v5.0

HydraGNN v5.0 expands the code base into a more portable, scalable, and flexible framework for scientific graph learning, with particular strength in atomistic machine-learning interatomic potentials and large-scale distributed training. The release adds Fully Sharded Data Parallel (FSDP) support alongside existing DDP and DeepSpeed paths, including FSDP-aware checkpointing and optimizer integration, and introduces a configurable multi-precision training workflow supporting FP32, BF16, and FP64 across GPUs and Intel XPUs. For atomistic modeling, HydraGNN v5.0 strengthens its MLIP capabilities through dynamic graph construction at every forward pass, energy-conserving force prediction via automatic differentiation, and per-atom energy loss formulations, while extending EGNN models to properly handle periodic boundary conditions. The release also broadens model expressiveness through graph-level attribute conditioning, adds new multi-task and model-parallel extensions such as MACE support and encoder/decoder branch optimization, and expands application coverage with integrated examples for datasets including OC25, Nabla2-DFT, QCML, Open Polymers 2026, and OPF. In parallel, HydraGNN v5.0 improves production readiness through performance optimizations for large-scale runs, stratified sampling and linear-regression preprocessing utilities, and tested installation scripts for DOE supercomputers including Frontier, Aurora, Perlmutter, and Andes. Overall, the release advances HydraGNN as a robust software platform for scalable graph neural networks across materials science, chemistry, and scientific machine learning workflows

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
NASA NTRS1974

Dependence of field-aligned electron precipitation occurrence on season and altitude

An examination of factors affecting the occurrence of field-aligned 2.3-keV electron precipitation has been performed by using data from more than 7500 orbits of the polar-orbiting satellite Ogo 4. Both season and altitude were found to be parameters that are directly related to the probability of occurrence. The highest probabilities occurred when the measurements were made at altitudes from 800 km to apogee (914 km), except during summer. In this altitude interval, the electron precipitation was more likely to be field-aligned during winter than during any other season. The analysis suggests the establishment by electrostatic charge layers of localized electric fields parallel to the magnetic field. The resulting potential distribution focuses the electron beam along the field lines in the region between the charge layers but destroys the focused beam below the lower layer, and thus an altitude dependence is created.

Berko, F. W.↗
NASA NTRS1976

Relativistic electrons and whistlers in Jupiter's magnetosphere

The path-integrated gain of parallel propagating whistlers driven unstable by an anisotropic distribution of relativistic electrons in the stable trapping region of Jupiter's inner magnetosphere was computed. The requirement that a gain of 3 e-foldings of power balance the power lost by imperfect reflection along the flux tube sets a stably-trapped flux of electrons which is close to the non-relativistic result. Comparison with measurements shows that observed fluxes are near the stably-trapped limit, which suggests that whistler wave intensities may be high enough to cause significant diffusion of electrons accounting for the observed reduction of phase space densities. A crude estimate of the wave intensity necessary to diffuse electrons on a radial diffusion time scale yields a lower limit for the magnetic field fluctuation intensity.

Barbosa, D. D.↗
NASA NTRS1979

Numerical results for the thermal scattering functions

A recent formulation in radiative transfer defined the thermal scattering functions that characterize radiative transfer from a general plane-parallel finite medium driven solely by an internal distribution of thermal sources. Exiting diffuse intensities are expressed as space convolutions of the thermal scattering functions with any thermal source distribution. A parametric study is presented to obtain the basic structure of these scattering functions. The independent variables of these azimuthally independent functions are the direction cosine and source location, while the parameters are the single-scattering albedo, total optical depth, and the asymmetry factor in the Henyey-Greenstein phase function. The basic functional trends are discussed by using various parametric plots, and selected results are given to allow numerical checks. The computational method is invariant imbedding.

Cogley, A. C.↗
NASA NTRS1980

Charged particle anisotropics in Saturn's magnetosphere

The paper deals with observations of anisotropies and pitch angle distributions for 0.5 to 1.8 MeV protons and 7 to 17 MeV electrons in Saturn's magnetosphere. In the outer magnetosphere (L = 6), there is clear evidence for corotation of the proton flux. The pitch-angle distribution shows maximum flux perpendicular to the magnetic field ('pancake' distribution). Observed changes in the amplitude and shape of the pitch angle distributions suggest the existence of substantial temporal variations in the outer magnetosphere. From L = 6 to L = 4, the proton intensity decreased by more than two orders of magnitude, while the pitch angle distribution shifted to a 'dumbbell' form (maximum flux parallel to magnetic field).

Bastian, T. S.↗