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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Development of a Subcell Based Modeling Approach for Modeling the Architecturally Dependent Impact Response of Triaxially Braided Polymer Matrix Composites

Understanding the high velocity impact response of polymer matrix composites with complex architectures is critical to many aerospace applications, including engine fan blade containment systems where the structure must be able to completely contain fan blades in the event of a blade-out. Despite the benefits offered by these materials, the complex nature of textile composites presents a significant challenge for the prediction of deformation and damage under both quasi-static and impact loading conditions. The relatively large mesoscale repeating unit cell (in comparison to the size of structural components) causes the material to behave like a structure rather than a homogeneous material. Impact experiments conducted at NASA Glenn Research Center have shown the damage patterns to be a function of the underlying material architecture. Traditional computational techniques that involve modeling these materials using smeared homogeneous, orthotropic material properties at the macroscale result in simulated damage patterns that are a function of the structural geometry, but not the material architecture. In order to preserve heterogeneity at the highest length scale in a robust yet computationally efficient manner, and capture the architecturally dependent damage patterns, a previously-developed subcell modeling approach where the braided composite unit cell is approximated as a series of four adjacent laminated composites is utilized. This work discusses the implementation of the subcell methodology into the commercial transient dynamic finite element code LS-DYNA (Livermore Software Technology Corp.). Verification and validation studies are also presented, including simulation of the tensile response of straight-sided and notched quasi-static coupons composed of a T700/PR520 triaxially braided [0deg/60deg/-60deg] composite. Based on the results of the verification and validation studies, advantages and limitations of the methodology as well as plans for future work are discussed.

finite element method↗
DOE OSTI2019

Spatially Resolving Lithiation in Silicon–Graphite Composite Electrodes via in Situ High-Energy X-ray Diffraction Computed Tomography

Optimizing the chemical and morphological parameters of lithium-ion (Li-ion) electrodes is extremely challenging, due in part to the absence of techniques to construct spatial and temporal descriptions of chemical and morphological heterogeneities. We present the first demonstration of combined high-speed X-ray diffraction (XRD) and XRD computed tomography (XRD-CT) to probe, in 3D, crystallographic heterogeneities within Li-ion electrodes with a spatial resolution of 1 um. The local charge-transfer mechanism within and between individual particles was investigated in a silicon(Si)-graphite composite electrode. Here, high-speed XRD revealed charge balancing kinetics between the graphite and Si during the minutes following the transition from operation to open circuit. Subparticle lithiation heterogeneities in both Si and graphite were observed using XRD-CT, where the core and shell structures were segmented, and their respective diffraction patterns were characterized.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters

The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.

Pindera, Marek-Jerzy↗
DOE OSTI2019

Photocatalytic Transformation of Amines to Imines by Meso-Porous Copper Sulfides

We have demonstrated a visible-light-driven catalytic process for amine to imine transformations, using a hydrothermal procedure based mesoporous copper sulfide material. The surface chemistry of this heterogeneously catalyzed process, which was further supported by computational calculations, was determined by the reaction kinetics, and reactive oxygen determination studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Experimental and Computational Studies of the Production of 1,3-Butadiene from 2,3-Butanediol Using SiO2-Supported H3PO4 Derivatives

Silica-supported phosphoric acid and metal phosphate catalyzed 1,3-butadiene (BDE) production from 2,3-butanediol (2,3-BDO) was studied using experimental and computational techniques. The catalyst was initially tested in a continuous flow reactor using commercially available 2,3-BDO, leading to maximum BDE yields of 63C%. Quantum chemical mechanistic studies revealed 1,2-epoxybutane is a kinetically viable and thermodynamically stable intermediate, supported by experimental demonstration that this epoxide can be converted to BDE under standard reaction conditions. Newly proposed E2 and SN2' elementary steps were studied to rationalize the formation of BDE and all detected side-products. Additionally, using quantum mechanics/molecular mechanics (QM/MM) calculations, we modeled silica-supported phosphate catalysts to study the effect of the alkali metal center. Natural population analysis showed that phosphate oxygen atoms are more negatively charged in CsH2PO4/SiO2 than in H3PO4/SiO2. In combination with temperature-programmed desorption experiments using CO2, the results of this study suggest that the improved selectivity achieved when adding the metal center is related to an increase in the basicity of the catalyst.

butadiene↗
DOE OSTI2017

Energy level alignment at molecule-metal interfaces from an optimally tuned range-separated hybrid functional

The alignment of the frontier orbital energies of an adsorbed molecule with the substrate Fermi level at metal-organic interfaces is a fundamental observable of significant practical importance in nanoscience and beyond. Typical density functional theory calculations, especially those using local and semi-local functionals, often underestimate level alignment leading to inaccurate electronic structure and charge transport properties. Here, we develop a new fully self-consistent predictive scheme to accurately compute level alignment at certain classes of complex heterogeneous molecule-metal interfaces based on optimally tuned range-separated hybrid functionals. Starting from a highly accurate description of the gas-phase electronic structure, our method by construction captures important nonlocal surface polarization effects via tuning of the long-range screened exchange in a range-separated hybrid in a non-empirical and system-specific manner. We implement this functional in a plane-wave code and apply it to several physisorbed and chemisorbed molecule-metal interface systems. Our results are in quantitative agreement with experiments, the both the level alignment and work function changes. This approach constitutes a new practical scheme for accurate and efficient calculations of the electronic structure of molecule-metal interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Accelerating DCA++ (Dynamical Cluster Approximation) Scientific Application on the Summit supercomputer

Optimizing scientific applications on today’s accelerator-based high performance computing systems can be challenging, especially when multiple GPUs and CPUs with heterogeneous memories and persistent non-volatile memories are present. An example is Summit, an accelerator-based system at the Oak Ridge Leadership Computing Facility (OLCF) that is rated as the world’s fastest supercomputer to-date. New strategies are thus needed to expose the parallelism in legacy applications, while being amenable to efficient mapping to the underlying architecture.In this paper we discuss our experiences and strategies to port a scientific application, DCA++, to Summit. DCA++ is a highperformance research application that solves quantum manybody problems with a cutting edge quantum cluster algorithm, the dynamical cluster approximation.Our strategies aim to synergize the strengths of the different programming models in the code. These include: (a) streamlining the interactions between the CPU threads and the GPUs, (b) implementing computing kernels on the GPUs and decreasing CPU-GPU memory transfers, (c) allowing asynchronous GPU communications, and (d) increasing compute intensity by combining linear algebraic operations.Full-scale production runs using all 4600 Summit nodes attained a peak performance of 73.5 PFLOPS with a mixed precision implementation.We observed a perfect strong and weak scaling for the quantum Monte Carlo solver in DCA++, while encountering about 2× input/output (I/O) and MPI communication overhead on the time-to-solution for the full machine run. Our hardware agnostic optimizations are designed to alleviate the communication and I/O challenges observed, while improving the compute intensity and obtaining optimal performance on a complex, hybrid architecture like Summit.

Balduzzi, Giovanni↗
DOE OSTI2024

GraphCH: A Deep Framework for Assessing Cyber-Human Aspects in Insider Threat Detection

Insider threat is one of the most damaging cyber attacks that could cause the loss of intellectual property and enterprise data security breaches. Action sequence data such as host logs are used to investigate such threats and develop anomaly-based AI detectors. However, insider threat actions are similar to legitimate user activities, causing AI detectors to fail and suffer from high false alarm rates. Therefore, user cyber activity logs are inadequate to fully unfold insider threats. In this study, we adopt human psychological principles of risk-taking and impulsiveness along with host data to assess the influence and usefulness of human behavioral aspects in insider threat detection. Here, we hypothesize that individuals' impulsive and risk-taking behavior correlates with cyberspace activities. To validate our hypothesis, we conducted an IRB-approved study recruiting 35 participants who work in a large U.S. university and collected their cyber and psychological data for 90 days. Host and human-behavioral data analysis and mapping indicate that impulsive and risk-taking users trigger more system errors causing (un)intentional insider threats and are susceptible to attackers' social engineering and cognitive hacking. Utilizing cyber-human aspects, we introduce a Cyber-Human Graph Neural Network (GNN) based framework GraphCH to identify abnormal user behaviors and detect insider threats.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-T-477: An Efficient Dose Correction Algorithm Accounting for Tissue Heterogeneities in LDR Brachytherapy

Purpose: Seed brachytherapy is currently used for adjuvant radiotherapy of early stage prostate and breast cancer patients. The current standard for calculation of dose surrounding the brachytherapy seeds is based on American Association of Physicist in Medicine Task Group No. 43 (TG-43 formalism) which generates the dose in homogeneous water medium. Recently, AAPM Task Group No. 186 emphasized the importance of accounting for tissue heterogeneities. This can be done using Monte Carlo (MC) methods, but it requires knowing the source structure and tissue atomic composition accurately. In this work we describe an efficient analytical dose inhomogeneity correction algorithm implemented using MIM Symphony treatment planning platform to calculate dose distributions in heterogeneous media. Methods: An Inhomogeneity Correction Factor (ICF) is introduced as the ratio of absorbed dose in tissue to that in water medium. ICF is a function of tissue properties and independent of source structure. The ICF is extracted using CT images and the absorbed dose in tissue can then be calculated by multiplying the dose as calculated by the TG-43 formalism times ICF. To evaluate the methodology, we compared our results with Monte Carlo simulations as well as experiments in phantoms with known density and atomic compositions. Results: The dose distributions obtained through applying ICF to TG-43 protocol agreed very well with those of Monte Carlo simulations as well as experiments in all phantoms. In all cases, the mean relative error was reduced by at least 50% when ICF correction factor was applied to the TG-43 protocol. Conclusion: We have developed a new analytical dose calculation method which enables personalized dose calculations in heterogeneous media. The advantages over stochastic methods are computational efficiency and the ease of integration into clinical setting as detailed source structure and tissue segmentation are not needed. University of Toronto, Natural Sciences and Engineering Research Council of Canada.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

BoBa

BoBa is a C++ software library for working with large matrices, tensors, and tensor decompositions. The library provides tools for dense matrix and tensor operations, tensor decompositions, and tensor decomposition methods that support modern CPU and GPU architectures. It includes portable abstractions for linear algebra, tensor algebra, and multidimensional computation. BoBa is intended for scientific computing applications that involve large multidimensional data sets or high dimensional mathematical models. Its capabilities support tasks such as data compression, linear algebra, efficient numerical computation, and the development of scalable algorithms for heterogeneous hardware. Tutorials, tests, and example applications are included to help users learn and apply the library.

Yao, Jin [Lawrence Livermore National Laboratory (↗
DOE OSTI2023

EMMA: a new method for computing multiple sequence alignments given a constraint subset alignment

Abstract Background Adding sequences into an existing (possibly user-provided) alignment has multiple applications, including updating a large alignment with new data, adding sequences into a constraint alignment constructed using biological knowledge, or computing alignments in the presence of sequence length heterogeneity. Although this is a natural problem, only a few tools have been developed to use this information with high fidelity. Results We present EMMA (Extending Multiple alignments using MAFFT--add) for the problem of adding a set of unaligned sequences into a multiple sequence alignment (i.e., a constraint alignment). EMMA builds on MAFFT--add, which is also designed to add sequences into a given constraint alignment. EMMA improves on MAFFT--add methods by using a divide-and-conquer framework to scale its most accurate version, MAFFT-linsi--add, to constraint alignments with many sequences. We show that EMMA has an accuracy advantage over other techniques for adding sequences into alignments under many realistic conditions and can scale to large datasets with high accuracy (hundreds of thousands of sequences). EMMA is available at https://github.com/c5shen/EMMA . Conclusions EMMA is a new tool that provides high accuracy and scalability for adding sequences into an existing alignment.

Shen, Chengze↗
DOE OSTI2012

MOCFE-Bone: The 3D-MOC Mini-Application for Exascale Research

MOCFE-Bone is a mini-application that simulates the main procedures in a 3D method of characteristics (MOC) code for numerical solution of the steady state neutron transport equation. 3D MOC was chosen as a specific methodology of interest in exascale computing for nuclear reactor applications because of its heterogeneous geometry capability, high degree of accuracy, and potential for scalability. In developing the mini-app, we focused on emulating the behavior of a production 3D MOC tool without requiring the input overhead associated with such a code. The MOCFE code at Argonne National Laboratory was used to investigate and characterize the behavior of the mini-app; the results of are presented here. Note that the existing MOCFE code resulted from research forays into the potential of 3D-MOC for large scale parallelism and is not a production level tool nor is it optimally implemented. Parts of the mini-app therefore reflect lessons learned and represent how a production-level tool would be written from this point forward rather than simply duplicating MOCFE, which has known scalability issues (i.e. parallelization in energy).

Wolters, E. R.↗
NASA NTRS1991

NMESys: An expert system for network fault detection

The problem of network management is becoming an increasingly difficult and challenging task. It is very common today to find heterogeneous networks consisting of many different types of computers, operating systems, and protocols. The complexity of implementing a network with this many components is difficult enough, while the maintenance of such a network is an even larger problem. A prototype network management expert system, NMESys, implemented in the C Language Integrated Production System (CLIPS). NMESys concentrates on solving some of the critical problems encountered in managing a large network. The major goal of NMESys is to provide a network operator with an expert system tool to quickly and accurately detect hard failures, potential failures, and to minimize or eliminate user down time in a large network.

Nelson, Peter C.↗
DOE OSTI2019

MULTIPHYSICS STEADY-STATE SIMULATION OF THE HIGH TEMPERATURE TEST REACTOR WITH MAMMOTH, BISON AND RELAP-7

In this work we present a new approach to solving a multiphysics steady-state simulation for the High Temperature Test Reactor (HTTR) using one Super Homogenization (SPH) corrected homogenized 3-D neutronics model in MAMMOTH, multiple heterogeneous 2-D axisymmetric fuel pin models in BISON and several 1-D annular flow thermohydraulics models in RELAP-7. The coupling of the different physics is complicated by the fundamentally disparate models, potentially affecting the stability of the global system. A pseudo-transient to converge the temperature fields is used to circumvent this difficulty. The benefit of doing so as opposed to having fully 3-D heterogenous models for all physics is that the computational burden for reactors as complex as HTTR may quickly become unbearable while coarse models may not capture all the essential phenomena of the problem. The driving purpose of this work is to establish a self-sustaining steady-state solution that can be used to start safety transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

MULTIPHYSICS STEADY-STATE SIMULATION OF THE HIGH TEMPERATURE TEST REACTOR WITH MAMMOTH, BISON AND RELAP-7

In this work we present a new approach to solving a multiphysics steady-state simulation for the High Temperature Test Reactor (HTTR) using one Super Homogenization (SPH) corrected homogenized 3-D neutronics model in MAMMOTH, multiple heterogeneous 2-D axisymmetric fuel pin models in BISON and several 1-D annular flow thermohydraulics models in RELAP-7. The coupling of the different physics is complicated by the fundamentally disparate models, potentially affecting the stability of the global system. A pseudo-transient to converge the temperature fields is used to circumvent this difficulty. The benefit of doing so as opposed to having fully 3-D heterogenous models for all physics is that the computational burden for reactors as complex as HTTR may quickly become unbearable while coarse models may not capture all the essential phenomena of the problem. The driving purpose of this work is to establish a self-sustaining steady-state solution that can be used to start safety transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗