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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Charting the relationship between phase type-surface area-interactions between the constituent atoms and oxygen reduction activity of Pd–Cu nanocatalysts inside fuel cells by in operando high-energy X-ray diffraction

The activity and stability of nanoalloy catalysts for chemical reactions driving devices for clean energy conversion, in particular the oxygen reduction reaction (ORR), depend critically on optimizing major structural characteristics of the nanoalloys, such as the phase composition, surface area and bonding interactions between the constituent atoms, for the harsh operating conditions inside the devices. The effort requires good knowledge of the potential effect of changes in these characteristics on the catalytic functionality of the nanoalloys and, hence, on the devices' performance. We present the results from an in operando high-energy X-ray diffraction (HE-XRD) study on the concurrent changes in the structural characteristics and ORR activity of Pd–Cu nanoalloy catalysts as they function at the cathode of a proton exchange membrane fuel cell (PEMFC). We find that the as-prepared Pd–Cu nanoalloys with a chemical composition close to Pd1Cu1 are better ORR catalysts in comparison with Pd1Cu2, i.e. Pd-poor, and Pd3Cu1, i.e. Pd-rich, nanoalloys. Under operating conditions though, the former suffers a big loss in ORR activity appearing as a slow-mode oscillation in the current output of the PEMFC. Losses in ORR activity suffered by the latter also exhibit sudden drops and rises during the PEMFC operation. Through atomic pair distribution function (PDF) analysis of the in operando HE-XRD data, we identify the structural changes of Pd–Cu alloy NPs that are behind the peculiar decay of their ORR activity. The results uncover the instant link between the ever-adapting structural state of ORR nanocatalysts inside an operating PEMFC and the performance of the PEMFC. Besides, our results indicate that, among others, taking control over the intra-particle diffusion of metallic species in nanoalloy catalysts may improve the performance of PEMFCs significantly and, furthermore, in operando HE-XRD can be an effective tool to guide the effort. Finally, we argue that, though showing less optimal ORR activity in the as-prepared state, monophase Pd–Cu alloy catalysts with a composition ranging between Pd1Cu1 and Pd3Cu1 may deliver optimal performance inside operating PEMFCs.

Maswadeh, Yazan↗
DOE OSTI2016

A quantitative model of application slow-down in multi-resource shared systems

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job is characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Life-cycle mediated effects of urbanization on parasite communities in the estuarine fish, Fundulus heteroclitus

This study examined the relationship between urbanization and parasite community structure in the estuarine fish, Fundulus heteroclitus. We measured landscape and physicochemical factors associated with urbanization at 6 sites from 4 collection periods. Concurrently, we quantified the metazoan parasite community in F. heteroclitus collected at those sites, with 105 fish studied per site during the 4 collection periods. Parasite community composition differed among sites. Host size was the most important variable for direct life-cycle parasite assemblages and indirect life-cycle parasites at the individual fish level, while landscape and physicochemical factors determined the structure of indirect life-cycle parasite assemblages at the population scale. Variation in the prevalence and intensity of infection of two indirect life-cycle parasites, Lasiocotus minutus and Glossocercus caribaensis, were the primary parasites that drove differences across sites. Variation in the presence/absence of these indirect life-cycle parasite species was associated with sediment Ni concentrations, patch density, and marsh size. Our data support the hypothesis that urbanization, acting at both landscape and physicochemical scales, can have a significant impact on parasite community structure. This, however, varied by parasite life history: there was little effect of urbanization on the prevalence and intensity of direct life-cycle parasites, but significant variation was detected for indirect life-cycle parasites. This study demonstrates how anthropogenically driven landscape change influences fine-scale population dynamics of parasites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Baseline Assessment of TREAT for Modeling and Analysis Needs

TREAT is an air-cooled, graphite moderated, thermal, heterogeneous test facility designed to evaluate reactor fuels and structural materials under conditions simulating various types of nuclear excursions and transient undercooling situations that could occur in a nuclear reactor. After 21 years in a standby mode, TREAT is being re-activated to revive transient testing capabilities. Given the time elapsed and the concurrent loss of operating experience, current generation and advanced computational methods are being applied to begin TREAT modeling and simulation prior to renewed at-power operations. Such methods have limited value in predicting the behavior of TREAT without proper validation. Hence, the U.S. DOE has developed a number of programs to support development of benchmarks for both critical and transient operations. Extensive effort has been expended at INL to collect detailed descriptions, drawings and specifications for all aspects of TREAT, and to resolve conflicting data found through this process. This report provides a collection of these data, with updated figures that are significantly more readable than historic drawings and illustrations, compositions, and dimensions based on the best available sources. This document is not nor should it be considered to be a benchmark report. Rather, it is intended to provide one-stop shopping, to the extent possible, for other work that seeks to prepare detailed, accurate models of the core and its components. Given the nature of the variety of historic documents available and the loss of institutional memory, the only completely accurate database of TREAT data is TREAT itself. Unfortunately, disassembly of TREAT for inspection, assay, and measurement is highly unlikely. Hence the data provided herein is intended serve as a best-estimate substitute.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

General Line Ampacity State Solver

INL’s General Line Ampacity State Solver (GLASS) is a high performance software platform that enables advanced grid system operations and planning efforts to be computed in real time. It enables the combination of advanced sensors and sensor networks, communication and data transfer channels, secure and reliable data management, and real-time processing through a flexible system architecture, with the ability to support and integrate with any utility enterprise system. GLASS is designed to help resolve the problems associated with thermally limited transmission and distribution networks, namely bare overhead power transmission lines. GLASS enables the methodology of Concurrent Cooling (Dynamic Line Rating) by reducing the need of using a cost-prohibited number of weather stations (reduce the number of weather stations per mile of overhead power line) to achieve the resolution necessary for individual electric transmission line span capacity calculations. GLASS achieves this by coupling real-time grid operations data and infrastructure architecture information with real-time field deployed weather station measurements and pre-computed Computational Fluid Dynamics (CFD)-based wind modeling interpolation parameters (look-up tables). GLASS uses mathematical models based on the IEEE 738 standard and builds off of the provided iterative solution using modern software paradigms and programming styles to provide a more robust and modular software system. GLASS also interfaces in real-time with utility companies using known transmission line spans and structures. GLASS provides real-time ampacity calculations based on recent weather station data as well as transmission line specifications. GLASS also allows the user to interact graphically with internal databases, which include information such as transmission line conductor types and thermal rating limits, weather station names and locations, specific transmission line span and structure locations, as well as recent ampacity calculations.

Gentle, Jake↗
DOE OSTI2022

Fast redox switches lead to rapid transformation of goethite in humid tropical soils: A Mössbauer spectroscopy study

Abstract Humid tropical forest soils experience frequent rainfall, which limits oxygen diffusion and creates redox heterogeneity in upland soils. In this study we gauged the effect of short‐term anoxic conditions on Fe mineralogy of relatively Fe‐ and C‐rich surface soils (C/Fe mole ratio ∼5) from a humid tropical forest in Puerto Rico. Soils subjected to 4‐d oxic/anoxic oscillation were characterized by selective chemical extractions, Mössbauer spectroscopy (MBS), and X‐ray diffraction. Chemical extraction data suggested that rapidly switching redox conditions had subtle effects on bulk Fe mineralogy. Mössbauer, on the other hand, indicated that (a) the soil Fe is a mixture of goethites of varying characteristics with minor contributions from ferrihydrite (<5%) and Fe(III)‐organic matter (OM) phases (∼10%), and (b) anoxic conditions rapidly transformed all forms of goethite to relatively stable Fe oxides. Such fast changes in goethite features could be due to rapid depletion and sorption of bio‐released structural Al or sorbed OM onto residual soil components. The rapid temporal changes in MBS parameters and corresponding pore water nominal oxidation state of C values suggest that Fe‐C transformations in these upland tropical soils are complex and intricately coupled. A comprehensive understanding of the fate of Fe, Al, and OM (Fe‐organic moieties) during redox switches and concurrent changes in pore water chemistry is critical for development of robust transport models in humid tropical soils, which are subject to episodic low‐redox events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An Efficient Wait-Free Vector

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector, and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Bayesian Conavigation: Dynamic Designing of the Material Digital Twins via Active Learning

Scientific advancement is universally based on the dynamic interplay between theoretical insights, modeling, and experimental discoveries. However, this feedback loop is often slow, including delayed community interactions and the gradual integration of experimental data into theoretical frameworks. This challenge is particularly exacerbated in domains dealing with high-dimensional object spaces, such as molecules and complex microstructures. Hence, the integration of theory within automated and autonomous experimental setups, or theory in the loop-automated experiment, is emerging as a crucial objective for accelerating scientific research. The critical aspect is to use not only theory but also on-the-fly theory updates during the experiment. Furthermore, we introduce a method for integrating theory into the loop through Bayesian conavigation of theoretical model space and experimentation. Our approach leverages the concurrent development of surrogate models for both simulation and experimental domains at the rates determined by latencies and costs of experiments and computation, alongside the adjustment of control parameters within theoretical models to minimize epistemic uncertainty over the experimental object spaces. This methodology facilitates the creation of digital twins of material structures, encompassing both the surrogate model of behavior that includes the correlative part and the theoretical model itself. While being demonstrated here within the context of functional responses in ferroelectric materials, our approach holds promise for broader applications, such as the exploration of optical properties in nanoclusters, microstructure-dependent properties in complex materials, and properties of molecular systems.

Microscopy↗
DOE OSTI2022

Towards Superior Software Portability with SHAD and HPX C++ Libraries

As hardware architectures and software stacks complexity grows, development productivity, performance and software portability, quickly evolve from desirable features to actual needs. SHAD, the Scalable High-performance Algorithms and Data-structures C++ library is designed to mitigate these issues: it provides general purpose building blocks as well as high-level custom utilities, and offers a shared-memory programming abstraction which facilitates the programming of complex systems, scaling up to High Performance Computing clusters. SHAD’s portability is achieved through an abstract runtime interface, which decouples the upper layers of the library and hides the low level details of the underlying architecture. This layer enables SHAD to interface with different runtime/threading systems, e.g. Intel TBB and Global Memory and Threading (GMT). However, current backends targeting distributed systems, rely on a centralized controller which may possibly limit scalability up to hundreds of nodes and creates a network hot spot due to all to one communication for synchronization, and possibly resulting in degraded performance at high process counts. In this research, we explore HPX, the C++ standard library for parallelism and concurrency, as an additional backend in support of the SHAD library, and present the methodologies in support of local and remote task executions in SHAD with respect to HPX. Finally, we evaluate the proposed system by comparing against existing backends of SHAD and analyzing their performance on C++ Standard Template Library algorithms.

Wu, Nanmiao↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
DOE OSTI2015

NSTX-U Advances in Real-Time C++11 on Linux

Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation's real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Evaluation of an in vitro three-dimensional HepaRG spheroid model for genotoxicity testing using the high-throughput CometChip platform

Three-dimensional (3D) culture systems are increasingly being used for genotoxicity studies due to improved cell-to-cell interactions and tissue-like structures that are limited or lacking in 2D cultures. The present study optimized a 3D culture system using metabolically competent HepaRG cells for in vitro genotoxicity testing. 3D HepaRG spheroids, formed in 96- or 384-well ultra-low attachment plates, were exposed to various concentrations of 34 test articles, including 8 direct-acting and 11 indirect-acting genotoxicants/carcinogens as well as 15 compounds that show different genotoxic responses in vitro and in vivo. DNA damage was evaluated using the high-throughput CometChip assay with concurrent cytotoxicity assessment by the ATP assay in both 2D and 3D cultures. 3D HepaRG spheroids maintained a stable phenotype for up to 30 days with higher levels of albumin secretion, cytochrome P450 gene expression, and enzyme activities compared to 2D cultures. 3D spheroids also demonstrated a higher sensitivity than 2D cultures for detecting both direct- and indirect-acting genotoxicants/carcinogens, indicating a better prediction of in vivo genotoxicity responses. When DNA damage dose-response data were quantified using PROAST software, 3D spheroids generally had lower or similar benchmark dose values compared to 2D HepaRG cells and were more comparable with primary human hepatocytes. These results demonstrate that 3D models can be adapted to the CometChip technology for high-throughput genotoxicity testing and that 3D HepaRG spheroids may be used as a reliable and pragmatic in vitro approach to better support the hazard identification and risk assessment of potential human genotoxic carcinogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Metagenomic Insights into the Degradation of Resistant Starch by Human Gut Microbiota

ABSTRACT Several studies monitoring alterations in the community structure upon resistant starch (RS) interventions are available, although comprehensive function-based analyses are lacking. Recently, a multiomics approach based on 16S rRNA gene sequencing, metaproteomics, and metabolomics on fecal samples from individuals subjected to high and low doses of type 2 RS (RS2; 48 g and 3 g/2,500 kcal, respectively, daily for 2 weeks) in a crossover intervention experiment was performed. In the present study, we did pathway-based metagenomic analyses on samples from a subset of individuals ( n = 12) from that study to obtain additional detailed insights into the functional structure at high resolution during RS2 intervention. A mechanistic framework based on obtained results is proposed where primary degradation was governed by Firmicutes , with Ruminococcus bromii as a major taxon involved, providing fermentation substrates and increased acetate concentrations for the growth of various major butyrate producers exhibiting the enzyme butyryl-coenzyme A (CoA):acetate CoA-transferase. H 2 -scavenging sulfite reducers and acetogens concurrently increased. Individual responses of gut microbiota were noted, where seven of the 12 participants displayed all features of the outlined pattern, whereas four individuals showed mixed behavior and one subject was unresponsive. Intervention order did not affect the outcome, emphasizing a constant substrate supply for maintaining specific functional communities. IMPORTANCE Manipulation of gut microbiota is increasingly recognized as a promising approach to reduce various noncommunicable diseases, such as obesity and type 2 diabetes. Specific dietary supplements, including resistant starches (RS), are often a focus, yet comprehensive insights into functional responses of microbiota are largely lacking. Furthermore, unresponsiveness in certain individuals is poorly understood. Our data indicate that distinct parts of microbiota work jointly to degrade RS and successively form health-promoting fermentation end products. It highlights the need to consider both primary degraders and specific more-downstream-acting bacterial groups in order to achieve desired intervention outcomes. The gained insights will assist the design of personalized treatment strategies based on an individual's microbiota.

Vital, Marius↗
DOE OSTI2021

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Here, we report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

42 ENGINEERING↗
DOE OSTI2016

The effect of millisecond flash lamp annealing on electrical and structural properties of ZnO:Al/Si structures

The effect of millisecond flash lamp annealing (FLA) on aluminum doped ZnO (AZO) films and their interface with Si have been studied. The AZO films were deposited by magnetron sputtering on Si (100) substrates. The electrical and structural properties of the film and AZO/Si structures were characterized by current–voltage, capacitance–voltage, and deep level transient spectroscopy measurements, X-ray diffraction, and secondary ion mass spectrometry. The resistivity of the AZO film is reduced to a close to state-of-the-art value of 2 × 10{sup −4} Ω cm after FLA for 3 ms with an average energy density of 29 J/cm{sup 2}. In addition, most of the interfacial defects energy levels are simultaneously annealed out, except for one persisting shallow level, tentatively assigned to the vacancy-oxygen complex in Si, which was not affected by FLA. Subsequent to the FLA, the samples were treated in N{sub 2} or forming gas (FG) (N{sub 2}/H{sub 2}, 90/10%{sub mole}) ambient at 200–500 °C. The latter samples maintained the low resistivity achieved after the FLA, but not the former ones. The interfacial defect level persisting after the FLA is removed by the FG treatment, concurrently as another level emerges at ∼0.18 eV below the conduction band. The electrical data of the AZO films are discussed in term of point defects controlling the resistivity, and it is argued that the FLA promotes formation of electrically neutral clusters of Zink vacancies (V{sub Zn}'s) rather than passivating/compensating complexes between the Al donors and V{sub Zn}'s.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Task-based Parallel Computation of the Density Matrix in Quantum-based Molecular Dynamics using Graph Partitioning

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms. These constraints arise due to expensive self-consistent ground-state electronic structure calculations that can often scale cubically with the number of atoms. Linearly scaling methods depend on computing the density matrix P from the Hamiltonian matrix H by exploiting the sparsity in both matrices. The second-order spectral projection (SP2) algorithm is an O(N) algorithm that computes P with a sequence of 40 - 50 matrix-matrix multiplications. In this paper, we present task-based implementations of a recently developed data-parallel graph-based approach to the SP2 algorithm, G-SP2. We represent the density matrix P as an undirected graph and use graph partitioning techniques to divide the computation into smaller independent tasks. The partitions thus obtained are generally not of equal size and give rise to undesirable load imbalances in standard MPI-based implementations. This load-balancing challenge can be mitigated by dynamically scheduling parallel computations at runtime using task-based programming models. We develop task-based implementations of the data-parallel G-SP2 algorithm using both Intel's Concurrent Collections (CnC) as well as the Charm++ programming model and evaluate these implementations for future use. Scaling and performance results of our implementations are investigated for representative segments of QMD simulations for solvated protein systems containing more than 10,000 atoms.

97 MATHEMATICS AND COMPUTING↗