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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Highly multicolored light-emitting arrays for compressive spectroscopy

Miniaturized, multicolored light-emitting device arrays are promising for applications in sensing, imaging, computing, and more, but the range of emission colors achievable by a conventional light-emitting diode is limited by material or device constraints. In this work, we demonstrate a highly multicolored light-emitting array with 49 different, individually addressable colors on a single chip. The array consists of pulsed-driven metal-oxide-semiconductor capacitors, which generate electroluminescence from microdispensed materials spanning a diverse range of colors and spectral shapes, enabling facile generation of arbitrary light spectra across a broad wavelength range (400 to 1400 nm). When combined with compressive reconstruction algorithms, these arrays can be used to perform spectroscopic measurements in a compact manner without diffractive optics. As an example, we demonstrate microscale spectral imaging of samples using a multiplexed electroluminescent array in conjunction with a monochrome camera.

42 ENGINEERING↗
DOE OSTI2018

Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices

Variance-based sensitivity analysis provides a quantitative measure of how uncertainty in a model input contributes to uncertainty in the model output. Such sensitivity analyses arise in a wide variety of applications and are typically computed using Monte Carlo estimation, but the many samples required for Monte Carlo to be sufficiently accurate can make these analyses intractable when the model is expensive. This paper presents a multifidelity approach for estimating sensitivity indices that leverages cheaper low-fidelity models to reduce the cost of sensitivity analysis while retaining accuracy guarantees via recourse to the original, expensive model. This paper develops new multifidelity estimators for variance and for the Sobol' main and total effect sensitivity indices. We discuss strategies for dividing limited computational resources among models and specify a recommended strategy. Results are presented for the Ishigami function and a convection-diffusion-reaction model that demonstrate up to $10\times$ speedups for fixed convergence levels. Finally, for the problems tested, the multifidelity approach allows inputs to be definitively ranked in importance when Monte Carlo alone fails to do so.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities

Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may even be willing to accept a high level of lossiness in the compression provided that the compressed data respect certain invariants, such as mass conservation. In the current work, we develop a mathematical framework and techniques that enable data to be adaptively compressed while maintaining a specified tolerance on a class of user-prescribed quantities. Here, the algorithm is used to augment the functionality of the data reduction package MGARD developed in previous work and the functionality is illustrated by a range of application including data from computational simulation of autocatalytic reaction simulation, turbulent combustion simulation, experimental data obtained from magnetic confinement fusion experiment, and simulation of turbulent flow along a rectangular channel. In each case, we consider one or more relevant quantities of interest and reduce the data so as to preserve these quantities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Single-node Partitioned-Memory for Huge Graph Analytics: Cost and Performance Trade-offs

Nonvolatile memory NVDIMMs, available as Intel Optane, are less expensive than DRAM and bring large byte-addressable storage within reach to many applications. Evaluations on graph analytics have shown promising performance only when DRAM is used as a hardware cache (Memory mode). An open question is whether graph applications can exploit Optane and DRAM directly (AppDirect mode) and achieving better-than-DRAM average bandwidth and run times. We evaluate Optane as a volatile pool on two large-scale graph applications with very different computational patterns, Grappolo and Ripples. We show that AppDirect mode can deliver better-than-DRAM performance, by allocating data structures to Optane and DRAM according to their access characteristics, resulting in higher average memory bandwidth and lower average latency. Memory mode provides DRAM-competitive performance with capacity equal to persistent memory. We demonstrate occasional 4x improvement using the latest AppDirect option and frequently observe competitive performance between Optane AppDirect Memory modes and DRAM.

Ghosh, Sayan↗
DOE OSTI2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2014

MiniAero

MiniAero is an MPl+X proxy app for gas dynamics problems. MiniAero can be used as a representative limited gas dynamics application to assess future computer architectures and programming models

Howard, Micah↗
DOE OSTI2016

Draco,Version 6.x.x

Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.

Thompson, Kelly↗
DOE OSTI2022

DGTile

SAND2022-12898 O DGTile is a lightweight C++17 adaptive mesh library meant to support explicit discontinuous Galerkin applications on high performance computing machines. DGTile uses a block-based adaptive mesh refinement approach, where the underlying mesh data structure is an octree in three dimensions, where each leaf node of the tree represents a Cartesian grid. Over each grid, DGTile provides modal discontinuous Galerkin basis functions to facilitate simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Granzow, Brian↗
DOE OSTI2025

ASCENT-TRAME BRIDGE

SF-25-116 Bridge for accessing Ascent extracts in a Trame application to create intuitive computational steering interfaces for HPC simulations.

MARRINAN, THOMASJOHN [Argonne National Laboratory ↗
DOE OSTI2015

Nitrogen and silicon defect incorporation during homoepitaxial CVD diamond growth on (111) surfaces

Chemical Vapor Deposited (CVD) diamond growth on (111)-diamond surfaces has received increased attention lately because of the use of N-V related centers in quantum computing as well as application of these defect centers in sensing nano-Tesla strength magnetic fields. We have carried out a detailed study of homoepitaxial diamond deposition on (111)-single crystal diamond (SCD) surfaces using a 1.2 kW microwave plasma CVD (MPCVD) system employing methane/hydrogen/nitrogen/oxygen gas phase chemistry. We have utilized Type Ib (111)-oriented single crystal diamonds as seed crystals in our study. The homoepitaxially grown diamond films were analyzed by Raman spectroscopy, Photoluminescence Spectroscopy (PL), X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). The nitrogen concentration in the plasma was carefully varied between 0 and 1500 ppm while a ppm level of silicon impurity is present in the plasma from the quartz bell jar. The concentration of N-V defect centers with PL zero phonon lines (ZPL) at 575nm and 637nm and the Si-defect center with a ZPL at 737nm were experimentally detected from a variation in CVD growth conditions and were quantitatively studied. As a result, altering nitrogen and oxygen concentration in the plasma was observed to directly affect N-V and Si-defect incorporation into the (111)-oriented diamond lattice and these findings are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Metal Artifact Reduction for CT-based Luggage Screening

This report describes research on active problems in computed tomography (CT) scanning applications. The problems are metal artifact reduction in CT images for medical imaging and luggage screening, and methods to evaluate segmentation of CT images. The research forms the basis of a PhD dissertation topic at UCSD, and is sponsored by LLNL.

42 ENGINEERING↗
DOE OSTI2014

The feasibility of mobile computing for on-site inspection.

With over 5 billion cellphones in a world of 7 billion inhabitants, mobile phones are the most quickly adopted consumer technology in the history of the world. Miniaturized, power-efficient sensors, especially video-capable cameras, are becoming extremely widespread, especially when one factors in wearable technology like Apple s Pebble, GoPro video systems, Google Glass, and lifeloggers. Tablet computers are becoming more common, lighter weight, and power-efficient. In this report the authors explore recent developments in mobile computing and their potential application to on-site inspection for arms control verification and treaty compliance determination. We examine how such technology can effectively be applied to current and potential future inspection regimes. Use cases are given for both host-escort and inspection teams. The results of field trials and their implications for on-site inspections are discussed.

Horak, Karl Emanuel↗
DOE OSTI2014

Memory Optimization for Phase-field Simulations

Phase-field simulations are computationally and memory intensive applications. Many of the phase-field simulations being conducted in support of NEAMS were not capable of running on “normal clusters” with 2-4GB of RAM per core, and instead required specialized “big-memory” clusters with 64GB per core. To address this issue, the MOOSE team developed a new Python-based utility called MemoryLogger, and applied it to locate, diagnose, and eradicate memory bottlenecks within the MOOSE framework. MemoryLogger allows for a better understanding of the memory usage of an application being run in parallel across a cluster. Memory usage information is captured for every individual process in a parallel job, and communicated to the head node of the cluster. Console text output from the application itself is automatically matched with this memory usage information to produce a detailed picture of memory usage over time, making it straightforward to identify the subroutines which contribute most to the application’s peak memory usage. The information produced by the MemoryLogger quickly and effectively narrows the search for memory optimizations to the most data-intensive parts of the simulation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

GEOS. User Tutorials

GEOS is a massively parallel, multi-physics simulation application utilizing high performance computing (HPC) to address subsurface reservoir stimulation activities with the goal of optimizing current operations and evaluating innovative stimulation methods. GEOS enables coupling of di erent solvers associated with the various physical processes occurring during reservoir stimulation in unique and sophisticated ways, adapted to various geologic settings, materials and stimulation methods. Developed at the Lawrence Livermore National Laboratory (LLNL) as a part of a Laboratory-Directed Research and Development (LDRD) Strategic Initiative (SI) project, GEOS represents the culmination of a multi-year ongoing code development and improvement e ort that has leveraged existing code capabilities and sta expertise to design new computational geosciences software.

58 GEOSCIENCES↗
DOE OSTI2016

Experimental and Computational Investigation of High Entropy Alloys for Elevated-Temperature Applications

To create and design novel structural materials with enhanced creep-resistance, fundamental studies have been conducted on high-entropy alloys (HEAs), using (1) thermodynamic calculations, (2) mechanical tests, (3) neutron diffraction, (4) characterization techniques, and (5) crystal-plasticity finite-element modeling (CPFEM), to explore future candidates for next-generation power plants. All the constituent binary and ternary systems of the Al-Cr-Cu-Fe-Mn-Ni and Al-Co-Cr-Fe-Ni systems were thermodynamically modeled within the whole composition range. Comparisons between the calculated phase diagrams and literature data are in good agreement. Seven types of HEAs were fabricated from Al-Cr-Cu-Fe-Mn-Ni and Al-Co-Cr-Fe-Ni systems. The Al x CrCuFeMnNi HEAs have disordered [face-centered cubic (FCC) + body-centered cubic (BCC)] crystal structures, not FCC or BCC single structure. Excessive alloying of the Al element results in the change of both microstructural and mechanical properties in Al x CoCrFeNi HEAs. There are mainly three structural features in Al x CoCrFeNi: (1) the morphology, (2) the volume fractions of the constitute phases, and (3) existing temperatures of all six phases. After homogenization, the Al 0.3 CoCrFeNi material is a pure FCC solid solution. After aging at 700 °C for 500 hours, the optimal microstructure combinations, the FCC matrix, needle-like B2 phase within grains, and granular σ phase along grain boundary, is achieved for Al 0.3 CoCrFeNi. The cold-rolling process is utilized to reduce the grain size of Al 0.1 CoCrFeNi and Al 0.3 CoCrFeNi. The chemical elemental partitioning of FCC, BCC, B2, and σphases at different temperatures, before and after mechanical tests, in Al-Cr-Cu-Fe-Mn-Ni and Al-Co-Cr-Fe-Ni systems are quantitatively characterized by both synchrotron X-ray diffraction, neutron diffraction with levitation, scanning electron microscopy (SEM), advanced atom probe tomography (APT), and transmission electron microscopy (TEM). In-situ neutron diffraction experiments were conducted to study the strengthening effect of B2 phase on tensile properties of Al 0.3 CoCrFeNi HEAs directly. The results shows the creep behavior of Al 0.3 CoCrFeNi is superior to conventional alloys, and the heat treatment introduces secondary B2 phase into the FCC matrix, which increase the yielding strength, decrease the ductility, diminish the serrated flow during compression tests at high temperatures. In summary, the outcomes of the development of the HEAs with creep resistance include: (1) Suitable candidates, for the application to boilers and steam and gas turbines at temperatures above 760 °C and a stress of 35 MPa. (2) Fundamental understanding on the precipitate stability and deformation mechanisms of both single-phase and precipitate-strengthened alloys at room and elevated temperatures, and (3) The demonstration of an integrated approach, coupling modeling [thermodynamic calculations and crystal-plasticity finite-element modeling (CPFEM)] and focused experiments, to identify HEAs that outperform conventional alloys for high-temperature applications, which will be applicable for the discovery and development of other high-temperature materials in the power-generating industry.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Advances in Cross-Cutting Ideas for Computational Climate Science

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Existing Fortran interfaces to Trilinos in preparation for exascale ForTrilinos development

This report summarizes the current state of Fortran interfaces to the Trilinos library within several key applications of the Exascale Computing Program (ECP), with the aim of informing developers about strategies to develop ForTrilinos, an exascale-ready, Fortran interface software package within Trilinos. The two software projects assessed within are the DOE Office of Science's Accelerated Climate Model for Energy (ACME) atmosphere component, CAM, and the DOE Office of Nuclear Energy's core-simulator portion of VERA, a nuclear reactor simulation code. Trilinos is an object-oriented, C++ based software project, and spans a collection of algorithms and other enabling technologies such as uncertainty quantification and mesh generation. To date, Trilinos has enabled these codes to achieve large-scale simulation results, however the simulation needs of CAM and VERA-CS will approach exascale over the next five years. A Fortran interface to Trilinos that enables efficient use of programming models and more advanced algorithms is necessary. Where appropriate, the needs of the CAM and VERA-CS software to achieve their simulation goals are called out specifically. With this report, a design document and execution plan for ForTrilinos development can proceed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗