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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

From PeleC to PeleACC, to PeleC++

PeleC is an Exascale Computing Project application for simulating compressible combustion in complex geometries. It has been built on top of the popular AMReX library. In the beginning of the Exascale Computing Project, PeleC was focused on KNL. It uses a mixture of C++, C, and kernels written in Fortran to obtain performance by focusing on vectorization. Recently we have taken two approaches in deciding PeleC's future for obtaining performance on exascale GPU machines. In the first programming model, we decorated the Fortran kernels with OpenACC directives. This expedited our ability to run at large scales on Summit's GPUs, where we achieved a significant speedup over the CPUs on Summit. The second programming model involved rewriting the Fortran kernels in C++ and using AMReX's Kokkos-like lambda abstractions for running on the GPU. This resulted in similar speedups on Summit's GPUs over merely utilizing the CPUs. Both approaches involved AMReX's management of memory transfers between the device and host. In this work, we compare and contrast the benefits and pitfalls to both programming approaches regarding performance, performance portability, and productivity. We also discuss advantages we have found in taking the time to modernize our code and why have chosen a specific pathway to prepare our code for the future DOE exascale machines.

exascale computing↗
DOE OSTI2023

Grid Event Signature Library Analytics Report: Signature Matching Tool Development Efforts

This report describes the purpose and features of the Signature Matching Tool (SMT), employed in the Department of Energy (DOE) Grid Event Signature Library (GESL). The SMT supports a user of GESL to identify snippets of electric signatures, usually from sensor devices measuring electric characteristics such as phase voltages and currents, frequency, etc., suspected to represent certain events in the power grid but are not known to the user. The SMT uses a classification method to identify an event of the unknown signature, using the repository of known and labeled signatures in the GESL. The classifier applies a local binary classifier per node (LCN) approach to the unique event tag taxonomy used in the GESL, where training phases are separated based on the Primary labels in the taxonomy, sensor type, and voltage level. Results show that this method helps with computing time during training, in comparison to a flat, multinomial classifier, and produces acceptable average accuracy of 83% across all Primary labels. The report concludes with planned future work including integration to the web interface and API.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Teaching Computational Reproducibility for Neuroimaging

We describe a project-based introduction to reproducible and collaborative neuroimaging analysis. Traditional teaching on neuroimaging usually consists of a series of lectures that emphasize the big picture rather than the foundations on which the techniques are based. The lectures are often paired with practical workshops in which students run imaging analyses using the graphical interface of specific neuroimaging software packages. Our experience suggests that this combination leaves the student with a superficial understanding of the underlying ideas, and an informal, inefficient, and inaccurate approach to analysis. To address these problems, we based our course around a substantial open-ended group project. This allowed us to teach: (a) computational tools to ensure computationally reproducible work, such as the Unix command line, structured code, version control, automated testing, and code review and (b) a clear understanding of the statistical techniques used for a basic analysis of a single run in an MR scanner. The emphasis we put on the group project showed the importance of standard computational tools for accuracy, efficiency, and collaboration. The projects were broadly successful in engaging students in working reproducibly on real scientific questions. We propose that a course on this model should be the foundation for future programs in neuroimaging. We believe it will also serve as a model for teaching efficient and reproducible research in other fields of computational science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Memory Errors in Modern Systems: The Good, The Bad, and The Ugly

Several recent publications have shown that hardware faults in the memory subsystem are commonplace. These faults are predicted to become more frequent in future systems that contain orders of magnitude more DRAM and SRAM than found in current memory subsystems. These memory subsystems will need to provide resilience techniques to tolerate these faults when deployed in high-performance computing systems and data centers containing tens of thousands of nodes. Therefore, it is critical to understand the efficacy of current hardware resilience techniques to determine whether they will be suitable for future systems. In this paper, we present a study of DRAM and SRAM faults and errors from the field. We use data from two leadership-class high-performance computer systems to analyze the reliability impact of hardware resilience schemes that are deployed in current systems. Our study has several key findings about the efficacy of many currently deployed reliability techniques such as DRAM ECC, DDR address/command parity, and SRAM ECC and parity. We also perform a methodological study, and find that counting errors instead of faults, a common practice among researchers and data center operators, can lead to incorrect conclusions about system reliability. Lastly, we use our data to project the needs of future large-scale systems. We find that SRAM faults are unlikely to pose a significantly larger reliability threat in the future, while DRAM faults will be a major concern and stronger DRAM resilience schemes will be needed to maintain acceptable failure rates similar to those found on today's systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electronic Properties of Ultra‐Wide Bandgap B x Al 1− x N Computed from First‐Principles Simulations

Abstract Ultra‐wide bandgap (UWBG) materials such as AlN and BN hold great promise for future power electronics due to their exceptional properties. They exhibit large bandgaps, high breakdown fields, high thermal conductivity, and high mechanical strengths. AlN and BN have been extensively researched, however, their alloys, B x Al 1− x N, are much less studied despite their ability to offer tunable properties by adjusting x . In this article, the electronic properties of 17 recently predicted ground states of B x Al 1− x N in the x = 0 − 1 range are predicted using first‐principles density functional theory and many‐body perturbation theory within GW approximation. All the B x Al 1− x N structures are found to be UWBG materials and have bandgaps that vary linearly from that of wurtzite‐phase ( w ) AlN (6.19 eV) to that of w ‐BN (7.47 eV). The bandstructures of B x Al 1− x N show that a direct‐to‐indirect bandgap crossover occurs near x = 0.25. Furthermore, it is found that B x Al 1− x N alloys have much larger dielectric constants than the constituent bulk materials (AlN = 9.3 ɛ 0 or BN = 7.3 ɛ 0 ), with values reaching as high as 12.1 ɛ 0 . These alloys are found to exhibit large dielectric breakdown fields in the range 9–35 MV cm −1 with a linear dependence on x . This work provides the much needed advancement in the understanding of the properties of B x Al 1− x N to aid their application in next‐generation devices.

Milne, Cody L.↗
DOE OSTI2014

Scaling To A Million Cores And Beyond: Using Light-Weight Simulation to Understand The Challenges Ahead On The Road To Exascale

As supercomputers scale to 1,000 PFlop/s over the next decade, investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices for high-performance computing (HPC) hardware/software co-design is crucial. This paper summarizes recent efforts in designing and implementing a novel HPC hardware/software co-design toolkit. The presented Extreme-scale Simulator (xSim) permits running an HPC application in a controlled environment with millions of concurrent execution threads while observing its performance in a simulated extreme-scale HPC system using architectural models and virtual timing. This paper demonstrates the capabilities and usefulness of the xSim performance investigation toolkit, such as its scalability to 2^27 simulated Message Passing Interface (MPI) ranks on 960 real processor cores, the capability to evaluate the performance of different MPI collective communication algorithms, and the ability to evaluate the performance of a basic Monte Carlo application with different architectural parameters.

Engelmann, Christian↗
DOE OSTI2015

Computational chemistry for NH 3 synthesis, hydrotreating, and NO x reduction: Three topics of special interest to Haldor Topsøe

Computational chemistry, especially density functional theory, has experienced a remarkable growth in terms of application over the last few decades. This is attributed to the improvements in theory and computing infrastructure that enable the analysis of systems of unprecedented size and detail at an affordable computational expense. In this perspective, we discuss recent progress and current challenges facing electronic structure theory in the context of heterogeneous catalysis. We specifically focus on the impact of computational chemistry in elucidating and designing catalytic systems in three topics of interest to Haldor Topsøe – ammonia, synthesis, hydrotreating, and NO x reduction. Furthermore, we then discuss the common tools and concepts in computational catalysis that underline these topics and provide a perspective on the challenges and future directions of research in this area of catalysis research.

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

Anticipating impacts of introducing aluminum-cerium alloys into the United States automotive market

Increasing demand of abundant co-product rare earths such as cerium and lanthanum has become a focus for improving mine economics. The recent development of an aluminum-cerium (Al-Ce) alloy targeted toward broad market adoption in the automotive industry is one recent example. This alloy has shown exceptional mechanical properties and cost-saving potential. However, since market adoption is unknown, impacts of this alloy on Ce demand remains uncertain. We estimate Al-Ce impacts by simulating adoption in different automotive sectors using a dynamic material flow analysis model. We then project future Ce content in the recycled Al stream given current recycling practices. We also compute the required segregation given different Ce impurity tolerances of existing automotive Al alloys. Finally, once secondary supply is derived from segregation, we calculate primary Ce demand. Results showed that segregation of Al-Ce components from non-AlCe automotive Al components is needed for most adoption scenarios and impurity thresholds. Ce metal demand was found to be lowest at 1000 mt/yr if the target market is light duty trucks. If Al-Ce could penetrate the High Efficiency Spark Ignition market (i.e., turbocharger market), Ce demand could reach 23,200 mt Ce/year in 2045, without accounting for Chinese and Australian Ce primary production capacity. Furthermore, when accounting for primary Ce production capacity, demand could reach up to 16,200 mt/yr.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Computationally Guided Discovery of Axis-Dependent Conduction Polarity in NaSnAs Crystals

Most electronic materials exhibit a single dominant charge carrier type, either holes or electrons, along all crystallographic directions. However, there are a small number of compounds, mostly metals, that exhibit simultaneous p-type and n-type conduction behavior along different crystallographic directions. We demonstrate that the experimental discovery of semiconductors with this axis-dependent conduction polarity can be facilitated by identifying a large anisotropy of either the electron or hole effective masses (m*) or both, providing the electron and hole masses dominate along different crystallographic directions. We calculated the layered semiconductor NaSnAs to have a lower electron m* in-plane than the cross-plane and a very large hole m* in-plane and small hole m* cross-plane. We established the growth of >3 mm-sized NaSnAs crystals via Sn flux and confirmed the band gap to be 0.65 eV, in agreement with theory. NaSnAs exhibits p-type thermopowers cross-plane and n-type thermopowers in-plane, confirming that the large anisotropy in the effective mass at the band edges is an excellent indicator for axis-dependent conduction polarity. Altogether, this work shows that the discovery of semiconductors with such a phenomenon can be accelerated by computationally evaluating the anisotropic curvatures of the band edges, paving the way for their future discovery and application.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Concentration-Dependent Solvation Structure and Dynamics of Aqueous Sulfuric Acid Using Multinuclear NMR and DFT

Sulfuric acid is a ubiquitous compound for industrial processes and aqueous sulfate solutions also play a critical role in electrolytes for many prominent battery chemistries. While the thermodynamic literature for it is quite well-developed, comprehensive studies of the solvation structure, and particularly molecular-scale dynamical and transport properties, are less available. This study applies a multinuclear NMR approach to the elucidation of the solvation structure and dynamics over a wide temperature (-10 – 50?C) and concentration (0 – 18 M) range, combining 17O shift, linewidth, and T1 relaxation measurements, 33S shift and linewidth measurements, and 1H PFG-NMR measurements of the proton self-diffusivity. In conjunction, these results indicate a crossover between two regimes of solvation structure and dynamics, occurring above the concentration associated with the deep eutectic point (~ 4.5 M), with the high-concentration regime dominated by strong water-sulfate correlation. This description was borne out in detail by the activation energy trends with increasing concentration derived from the relaxation of both the H2O/H3O+ and H2SO4/HSO4-/SO42- 17O resonances and the 1H self-diffusivity. However, the 17O chemical shift difference between the H2O/H3O+ and H2SO4/HSO4-/SO42- resonances across the entire temperature range is nevertheless strikingly linear. A computational approach coupling MD simulations and DFT NMR shift calculations to reproduce this trend is presented, which will be the subject of further development. This combination of multinuclear, dynamical NMR and computational methods, and the results furnished by this study, will provide a platform for future studies on battery electrolytes where aqueous sulfate chemistry plays a central role in the solution structure.

Bazak, Jonathan D.↗
DOE OSTI2025

Automated tabletop exfoliation and identification of monolayer graphene flakes

Over the past two decades, graphene has been intensively studied because of its remarkable mechanical, optical, and electronic properties. Initial studies were enabled by manual “Scotch Tape” exfoliation; nearly two decades later, this method is still widely used to obtain chemically pristine flakes of graphene and other 2D van der Waals materials. Unfortunately, the yield of large, pristine flakes with uniform thickness is inconsistent. Thus, significant time and effort are required to exfoliate and locate flakes suitable for fabricating multilayer van der Waals heterostructures. Here, we describe a relatively affordable tabletop device (the “eXfoliator”) that can reproducibly control key parameters and largely automate the exfoliation process. In a typical exfoliation run, the eXfoliator produces 3 or more large (≥ 400 μm 2 ) high-quality graphene monolayer flakes, allowing new users to produce such flakes at a rate comparable to manual exfoliation by an experienced user. Furthermore, we use an automated mapping system and a computer vision algorithm to locate candidate flakes. Our results provide a starting point for future research efforts to identify more precisely which parameters matter for the success of exfoliation and to optimize them.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

TU-FG-BRB-08: Challenges, Limitations and Future Outlook Towards Clinical Translation of Proton Acoustic Range Verification

Purpose: To report our investigations of proton acoustic imaging, including computer simulations and preliminary experimental studies at clinical facilities. The ultimate achievable accuracy, sensitivity and clinical translation challenges are discussed. Methods: The acoustic pulse due to pressure rise was estimated using finite element model. Since the ionoacoustic pulse is highly dependent on the proton pulse width and energy, multiple pulse widths were studied. Based on the received signal spectrum at piezoelectric ultrasound transducer with consideration of random thermal noise, maximum spatial resolution of the proton-acoustic imaging modality was calculated. The simulation studies defined the design specifications of the system to detect proton acoustic signal from Hitachi and Mevion clinical machines. A 500 KHz hydrophone with 100 dB amplification was set up in a water tank placed in front of the proton nozzle A 40 MHz data acquisition was synchronized by a trigger signal provided by the machine. Results: Given 30–800 mGy dose per pulse at the Bragg peak, the minimum number of protons detectable by the proton acoustic technique was on the order of 10×10^6 per pulse. The broader pulse widths produce signal with lower acoustic frequencies, with 10 µs pulses producing signals with frequency less than 100 kHz. As the proton beam pulse width increases, a higher dose rate is required to measure the acoustic signal. Conclusion: We have established the minimal detection limit for protonacoustic range validation for a variety of pulse parameters. Our study indicated practical proton-acoustic range verification can be feasible with a pulse shorter than 10 µs, 5×10^6 protons/pulse, 50 nA beam current and a highly sensitive ultrasonic transducer. The translational challenges into current clinical machines include proper magnetic shielding of the measurement equipment, providing a clean trigger signal from the proton machine, providing a shorter proton beam pulse and higher dose per pulse.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Bilevel Approach for Identifying the Worst Contingencies for Nonconvex Alternating Current Power Systems

We address the bilevel optimization problem of identifying the most critical attacks to an alternating current (AC) power flow network. The upper-level binary maximization problem consists of choosing an attack that is treated as a parameter in the lower-level defender minimization problem. Instances of the lower-level global minimization problem by themselves are NP-hard due to the nonconvex AC power flow constraints, and bilevel solution approaches commonly apply a convex relaxation or approximation to allow for tractable bilevel reformulations at the cost of underestimating some power system vulnerabilities. Our main contribution is to provide an alternative branch-and-bound algorithm whose upper bounding mechanism (in a maximization context) is based on a reformulation that avoids relaxation of the AC power flow constraints in the lower-level defender problem. Lower bounding is provided with semidefinite programming (SDP) relaxed solutions to the lower-level problem. We establish finite termination with guarantees of either a globally optimal solution to the original bilevel problem, or a globally optimal solution to the SDP-relaxed bilevel problem which is included in a vetted list of upper-level attack solutions, at least one of which is a globally optimal solution to the bilevel problem. We demonstrate through computational experiments applied to IEEE case instances both the relevance of our contribution, and the effectiveness of our contributed algorithm for identifying power system vulnerabilities without resorting to convex relaxations of the lower-level problem. We conclude with a discussion of future extensions and improvements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

HIPPO Software

HIPPO software is a Python implementation of the HIPPO technology. The HIPPO technology provides the computational and modeling capabilities for managing electricity market operations and for designing and prototyping future markets. The current software can solve the day-ahead unit commitment problem and perform simultaneous feasibility test. It can be used to handle industry scale electricity market.

Peng, Fan↗
DOE OSTI2022

Transverse Stability in an Alternating Symmetry Planar Dielectric Wakefield Structure

Dielectric Wakefield Acceleration (DWA) is a promising technique for realizing the next generation of linear colliders. It provides access to significantly higher accelerating gradients than traditional radio-frequency cavities. One impediment to realizing a DWA-powered accelerator is the issue of the transverse stability of the beams within the dielectric structure due to short-range wakefields. These short-range wakefields have a tendency to induce a phenomenon known as single-bunch beam breakup, which acts as its name implies and destroys the relevant beam. We attempt to solve this issue by leveraging the quadrupole mode excited in a planar dielectric structure and then alternating the orientation of said structure to turn an unstable system into a stable one. We examine this issue computationally to determine the limits of stability and based on those simulations describe a future experimental realization of this strategy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

2013 LLNL Nuclear Forensics Summer Program

The Lawrence Livermore National Laboratory (LLNL) Nuclear Forensics Summer Program is designed to give both undergraduate and graduate students an opportunity to come to LLNL for 8–10 weeks for a hands-on research experience. Students conduct research under the supervision of a staff scientist, attend a weekly lecture series, interact with other students, and present their work in poster format at the end of the program. Students also have the opportunity to meet staff scientists one-on-one, participate in LLNL facility tours (e.g., the National Ignition Facility and Center for Accelerator Mass Spectrometry) to gain a better understanding of the multi-disciplinary, on going science at LLNL. Currently called the Nuclear Forensics Summer Program, this program began 13 years ago as the Actinide Sciences Summer Program. The program is run within the Glenn T. Seaborg Institute in the Physical and Life Sciences Directorate at LLNL. The goal of the Nuclear Forensics Summer Program is to facilitate the training of the next generation of nuclear scientists and engineers to solve critical national security problems in the field of nuclear forensics and have the student experience conducting research at the Lab. We select students who are majoring in physics, chemistry, geology, mathematics, nuclear engineering, chemical engineering and environmental sciences. Students engage in research projects in the disciplines of actinide chemistry, radiochemistry, isotopic analysis, computational analysis, radiation detection, and nuclear engineering in order to strengthen the “pipeline” for future scientific disciplines critical to DHS (DNDO), NNSA.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2015

Exploring the Random Phase Approximately for materials chemistry and physics

This proposal focuses on improved accuracy for the delicate energy differences of interest in materials chemistry with the fully nonlocal random phase approximation (RPA) in a density functional context. Could RPA or RPA-like approaches become standard methods of first-principles electronic-structure calculation for atoms, molecules, solids, surfaces, and nano-structures? Direct RPA includes the full exact exchange energy and a nonlocal correlation energy from the occupied and unoccupied Kohn-Sham orbitals and orbital energies, with an approximate but universal description of long-range van der Waals attraction. RPA also improves upon simple pair-wise interaction potentials or vdW density functional theory. This improvement is essential to capture accurate energy differences in metals and different phases of semiconductors. The applications in this proposal are challenges for the simpler approximations of Kohn-Sham density functional theory, which are part of the current “standard model” for quantum chemistry and condensed matter physics. Within this project we already applied RPA on different structural phase transitions on semiconductors, metals and molecules. Although RPA predicts accurate structural parameters, RPA has proven not equally accurate in all kinds of structural phase transitions. Therefore a correction to RPA can be necessary in many cases. We are currently implementing and testing a nonempirical, spatially nonlocal, frequency-dependent model for the exchange-correlation kernel in the adiabatic-connection fluctuation-dissipation context. This kernel predicts a nearly-exact correlation energy for the electron gas of uniform density. If RPA or RPA-like approaches prove to be reliably accurate, then expected increases in computer power may make them standard in the electronic-structure calculations of the future.

74 ATOMIC AND MOLECULAR PHYSICS↗