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DOE OSTI2020

Interfacial electronic states of misfit heterostructure between hexagonal ZnO and cubic NiO

The combination of materials with dissimilar symmetries can induce a large amount of stress at the interfacial layer of films, thereby promoting the appearance of novel properties in related devices. The study of the interfacial state is critical for determining the inner mechanism. In this work, the misfit heterostructure between cubic NiO films and wurtzite ZnO is investigated. A NiO film grown using molecular beam epitaxy on a ZnO substrate shows a highly (100)-oriented texture featuring three domains with a rotation angle of 30°, which is in agreement with first principles calculations. Misfit-induced dislocations and lattice distortions within the interfacial layers of the NiO film give rise to interfacial electronic states, which are different from those in bulk; these electronic states are analyzed by in situ synchrotron-based x-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, x-ray absorption spectroscopy, and ex situ electron energy loss spectroscopy. Additionally, the origin of these interfacial states is discussed. This work aims to provide insights for the integration of semiconducting hexagonal ZnO with other functional materials that have a cubic symmetry. Additionally, we investigate the integration of photon and electron-based techniques to explore the interfacial states of complex interfaces, which is an important aspect of material science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Flexible Data-Aware Scheduling for Workflows over an In-Memory Object Store

This paper explores novel techniques for improving the performance of many-task workflows based on the Swift scripting language. We propose novel programmer options for automated distributed data placement and task scheduling. These options trigger a data placement mechanism used for distributing intermediate workflow data over the servers of Hercules, a distributed key-value store that can be used to cache file system data. We demonstrate that these new mechanisms can significantly improve the aggregated throughput of many-task workflows with up to 86x, reduce the contention on the shared file system, exploit the data locality, and trade off locality and load balance.

Duro, Francisco Rodrigo↗

DOE OSTI2016

DISP: Optimizations towards Scalable MPI Startup

Despite the popularity of MPI for high performance computing, the startup of MPI programs faces a scalability challenge as both the execution time and memory consumption increase drastically at scale. We have examined this problem using the collective modules of Cheetah and Tuned in Open MPI as representative implementations. Previous improvements for collectives have focused on algorithmic advances and hardware off-load. In this paper, we examine the startup cost of the collective module within a communicator and explore various techniques to improve its efficiency and scalability. Accordingly, we have developed a new scalable startup scheme with three internal techniques, namely Delayed Initialization, Module Sharing and Prediction-based Topology Setup (DISP). Our DISP scheme greatly benefits the collective initialization of the Cheetah module. At the same time, it helps boost the performance of non-collective initialization in the Tuned module. We evaluate the performance of our implementation on Titan supercomputer at ORNL with up to 4096 processes. The results show that our delayed initialization can speed up the startup of Tuned and Cheetah by an average of 32.0% and 29.2%, respectively, our module sharing can reduce the memory consumption of Tuned and Cheetah by up to 24.1% and 83.5%, respectively, and our prediction-based topology setup can speed up the startup of Cheetah by up to 80%.

Fu, Huansong↗

DOE OSTI2014

Visualizations for Real-time Pricing Demonstration

In this paper, the visualization tools created for monitoring the operations of a real-time pricing demonstration system that runs at a distribution feeder level are presented. The information these tools provide gives insights into demand behavior from automated price responsive devices, distribution feeder characteristics, impact of weather on system’s development, and other significant dynamics. Given the large number of devices that bid into a feeder-level real-time electricity market, new techniques are explored to summarize the present state of the system and contrast that with previous trends as well as future projections. To better understand the system behavior and correctly inform decision-making procedures, effective visualization of the data is imperative.

Marinovici, Maria C.↗

DOE OSTI2021

Multiscale Data-Driven Seismic Full-Waveform Inversion With Field Data Study

Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration geophysics. In recent years, the computational cost of FWI has grown exponentially due to the increasing size and resolution of seismic data. Moreover, it is a nonconvex problem and can encounter local minima due to the limited accuracy of the initial velocity models or the absence of low frequencies in the measurements. To overcome these computational issues, we develop a multiscale data-driven FWI method based on fully convolutional networks (FCNs). In preparing the training data, we first develop a real-time style transform method to create a large set of synthetic subsurface velocity models from natural images. We then develop two convolutional neural networks with encoder-decoder structures to reconstruct the low- and high-frequency components of the subsurface velocity models, separately. To validate the performance of our data-driven inversion method and the effectiveness of the synthesized training set, we compare it with conventional physics-based waveform inversion approaches using both synthetic and field data. Finally, these numerical results demonstrate that, once our model is fully trained, it can significantly reduce the computation time and yield more accurate subsurface velocity models in comparison with conventional FWI.

58 GEOSCIENCES↗

DOE OSTI2017

On Parallelizing Single Dynamic Simulation Using HPC Techniques and APIs of Commercial Software

Time-domain simulations are heavily used in today’s planning and operation practices to assess power system transient stability and post-transient voltage/frequency profiles following severe contingencies to comply with industry standards. Because of the increased modeling complexity, it is several times slower than real time for state-of-the-art commercial packages to complete a dynamic simulation for a large-scale model. With the growing stochastic behavior introduced by emerging technologies, power industry has seen a growing need for performing security assessment in real time. This paper presents a parallel implementation framework to speed up a single dynamic simulation by leveraging the existing stability model library in commercial tools through their application programming interfaces (APIs). Several high performance computing (HPC) techniques are explored such as parallelizing the calculation of generator current injection, identifying fast linear solvers for network solution, and parallelizing data outputs when interacting with APIs in the commercial package, TSAT. The proposed method has been tested on a WECC planning base case with detailed synchronous generator models and exhibits outstanding scalable performance with sufficient accuracy.

Diao, Ruisheng↗

DOE OSTI2014

TH-C-BRF-01: The Promise and Potential Pitfalls of Deformable Image Registration in Clinical Practice

Accurate and robust deformable image registration (DIR) is a key enabling technique in the clinical realization of two approaches for advancing radiation therapy treatment efficacy: adaptive radiation therapy and treatment response assessment. Currently there are a wide variety of DIR methods including the categories of splines, optical/diffusion, free-form, and biomechanical algorithms. All methods aim to translate information between image sets (including multi-modal data) in the presence of spatial deformation of tissues. However, recent research has shown that different DIR algorithms can yield substantially different results for the same reference deformation, and that DIR performance can be site and application dependent. As a result, errors can occur, and subsequent patient treatment can be compromised. There is a clear need for greater understanding of appropriate use of DIR techniques, as well as effective methods of validation, evaluation, and improvement. In this session, we will review the state-of-the-art concerning DIR development, clinical application, and performance evaluation. Novel DIR methods and evaluating technologies will be reviewed. Learning Objectives: To understand the underlying principles and physics of current DIR techniques To explore potential clinical applications and areas of high impact for DIR To investigate sources of uncertainty, appropriate usage, and methods for validating and evaluating DIR performance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-02: Estimation of Radiobiological Doses (BED and EQD2) of Single Fraction Electronic Brachytherapy That Equivalent to I-125 Eye Plaque: By Using Linear-Quadratic and Universal Survival Curve Models

Purpose: To test the radiobiological impact of hypofractionated choroidal melanoma brachytherapy, we calculated single fraction equivalent doses (SFED) of the tumor that equivalent to 85 Gy of I125-BT for 20 patients. Corresponding organs-at-risks (OARs) doses were estimated. Methods: Twenty patients treated with I125-BT were retrospectively examined. The tumor SFED values were calculated from tumor BED using a conventional linear-quadratic (L-Q) model and an universal survival curve (USC). The opposite retina (α/β = 2.58), macula (2.58), optic disc (1.75), and lens (1.2) were examined. The % doses of OARs over tumor doses were assumed to be the same as for a single fraction delivery. The OAR SFED values were converted into BED and equivalent dose in 2 Gy fraction (EQD2) by using both L-Q and USC models, then compared to I125-BT. Results: The USC-based BED and EQD2 doses of the macula, optic disc, and the lens were on average 118 ± 46% (p < 0.0527), 126 ± 43% (p < 0.0354), and 112 ± 32% (p < 0.0265) higher than those of I125-BT, respectively. The BED and EQD2 doses of the opposite retina were 52 ± 9% lower than I125-BT. The tumor SFED values were 25.2 ± 3.3 Gy and 29.1 ± 2.5 Gy when using USC and LQ models which can be delivered within 1 hour. All BED and EQD2 values using L-Q model were significantly larger when compared to the USC model (p < 0.0274) due to its large single fraction size (> 14 Gy). Conclusion: The estimated single fraction doses were feasible to be delivered within 1 hour using a high dose rate source such as electronic brachytherapy (eBT). However, the estimated OAR doses using eBT were 112 ∼ 118% higher than when using the I125-BT technique. Continued exploration of alternative dose rate or fractionation schedules should be followed.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Carbon capture in polymer-based electrolytes

Nanoparticle organic hybrid materials (NOHMs) have been proposed as excellent electrolytes for combined CO 2 capture and electrochemical conversion due to their conductive nature and chemical tunability. However, CO 2 capture behavior and transport properties of these electrolytes after CO 2 capture have not yet been studied. Here, we use a variety of nuclear magnetic resonance (NMR) techniques to explore the carbon speciation and transport properties of branched polyethylenimine (PEI) and PEI-grafted silica nanoparticles (denoted as NOHM-I-PEI) after CO 2 capture. Quantitative 13 C NMR spectra collected at variable temperatures reveal that absorbed CO 2 exists as carbamates (RHNCOO – or RR'NCOO – ) and carbonate/bicarbonate (CO 3 2– /HCO 3 – ). The transport properties of PEI and NOHM-I-PEI studied using 1 H pulsed-field-gradient NMR, combined with molecular dynamics simulations, demonstrate that coulombic interactions between negatively and positively charged chains dominate in PEI, while the self-diffusion in NOHM-I-PEI is dominated by silica nanoparticles. These results provide strategies for selecting adsorbed forms of carbon for electrochemical reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Preserving Contextual Awareness during Selection of Moving Targets in Animated Stream Visualizations

In many types of dynamic interactive visualizations, it is often desired to interact with moving objects. Stopping moving objects can make selection easier, but pausing animated content can disrupt perception and understanding of the visualization. To address such problems, we explore selection techniques that only pause a subset of all moving targets in the visualization. We present various designs for controlling pause regions based on cursor trajectory or cursor position. We then report a dual-task experiment that evaluates how different techniques affect both target selection performance and contextual awareness of the visualization. Our findings indicate that all pause techniques significantly improved selection performance as compared to the baseline method without pause, but the results also show that pausing the entire visualization can interfere with contextual awareness. However, the problem with reduced contextual awareness was not observed with our new techniques that only pause a limited region of the visualization. Thus, our research provides evidence that region-limited pause techniques can retain the advantages of selection in dynamic visualizations without imposing a negative effect on contextual awareness.

Ragan, Eric↗

DOE OSTI2026

Progress and Perspectives: Zirconium Electrodeposition from Different Electrolytes

Zirconium (Zr) possesses outstanding properties, including exceptional chemical resistance and a high melting point, and is therefore desirable for use in a wide variety of challenging environments, such as in nuclear reactors and the chemical processing industry. To minimize the amount of Zr required for any given application, developing methods for generating metallic Zr coatings is highly advantageous. Owing to Zr’s highly negative reduction potential, electrodeposition in traditional solvents at near ambient temperatures remains challenging and thus not well understood. Due to the extreme conditions required to deposit this metal, extensive work has been conducted in molten salt electrolytes, however the broad applicability of this methodology is limited due to its corrosivity. The primary focus of this article is to present an overview of Zr’s electrochemical behavior and to consolidate the efforts of researchers in exploring electrodeposition techniques for Zr involving aqueous, organic, ionic liquid, deep eutectic, and molten salt solvents. With this information, we highlight trends across solvent systems and opportunities for future research.

42 ENGINEERING↗

DOE OSTI2014

Geothermal Case Studies

The US Geological Survey (USGS) resource assessment (Williams et al., 2009) outlined a mean 30GWe of undiscovered hydrothermal resource in the western US. One goal of the Geothermal Technologies Office (GTO) is to accelerate the development of this undiscovered resource. The Geothermal Technologies Program (GTP) Blue Ribbon Panel (GTO, 2011) recommended that DOE focus efforts on helping industry identify hidden geothermal resources to increase geothermal capacity in the near term. Increased exploration activity will produce more prospects, more discoveries, and more readily developable resources. Detailed exploration case studies akin to those found in oil and gas (e.g. Beaumont, et al, 1990) will give operators a single point of information to gather clean, unbiased information on which to build geothermal drilling prospects. To support this effort, the National Renewable Energy laboratory (NREL) has been working with the Department of Energy (DOE) to develop a template for geothermal case studies on the Geothermal Gateway on OpenEI. In fiscal year 2013, the template was developed and tested with two case studies: Raft River Geothermal Area (http://en.openei.org/wiki/Raft_River_Geothermal_Area) and Coso Geothermal Area (http://en.openei.org/wiki/Coso_Geothermal_Area). In fiscal year 2014, ten additional case studies were completed, and additional features were added to the template to allow for more data and the direct citations of data. The template allows for: Data - a variety of data can be collected for each area, including power production information, well field information, geologic information, reservoir information, and geochemistry information. Narratives ? general (e.g. area overview, history and infrastructure), technical (e.g. exploration history, well field description, R&D activities) and geologic narratives (e.g. area geology, hydrothermal system, heat source, geochemistry.) Exploration Activity Catalog - catalog of exploration activities conducted in the area (with dates and references.) NEPA Analysis ? a query of NEPA analyses conducted in the area (that have been catalogued in the OpenEI NEPA database.) In fiscal year 2015, NREL is working with universities to populate additional case studies on OpenEI. The goal is to provide a large enough dataset to start conducting analyses of exploration programs to identify correlations between successful exploration plans for areas with similar geologic occurrence models.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Achieving the hydrogen shot: Interrogating ionomer interfaces

The aim of this study is to enable the hydrogen economy and decarbonize various sectors in our environment that requires less expensive and more durable water electrolyzers, which can meet the Hydrogen-Shot target. The key is to improve the ionomer interfaces in low-temperature water electrolyzers as rapidly as possible, but to do so, it requires a systematic and holistic campaign combining both experiments and theory. In this perspective, we discuss the issues of electrolyzers and needs for translational science. We then present the approach that the Energy EarthShot Research Center: Center for Ionomer-based Water Electrolysis is taking in hopes of inspiring the community with this approach that can be leveraged to multiple problems and technologies.Graphical abstractHighlightsOne way to achieve the Hydrogen-Shot goal of low-cost, clean hydrogen, is advancing research and development on the interfaces of water electrolyzers for both performance and lifetime. The Center for Ionomer-based Water Electrolysis is exploring new techniques and strategies to not only interrogate interfacial phenomena in water electrolyzers to increase efficiency and durability, but also a new paradigm related to synergistic, cojoined experimental and theoretical research.DiscussionCatalyst\ionomer interfaces are complex and not fully understood, but through investigating different interfaces and utilizing digital and physical twins, we can elucidate key mechanisms and understanding.Understanding the dynamic double layer in electrochemical systems that use solid electrolytes is crucial to identifying and mitigating the controlling phenomena to enable increased performance and durability at the technology level.Studying the time and length scales of interfacial changes can be a powerful tool to understand reaction mechanisms and changes in the electrolyzer performance and durability.

Fornaciari, Julie C↗

DOE OSTI2020

Data-Driven Model Reduction of Multiphase Flow in a Single-Hole Automotive Injector

Fuel injector design has a substantial influence on the performance and emissions of direct injection engines. To date, large eddy simulations coupled with a single-fluidmixture modeling approach have shown great success in evaluating the complex interplay among injector design, fuel properties, and operating conditions on the injector performance. However, this simulation approach is too computationally expensive to be used by industry routinely for injector design due to the fine temporal and spatial resolution required to resolve wall-bounded flow within the injector. The work presented in this paper highlights a potential pathway to addressing this issue. To study the influence of injector design, fuel properties, and operating conditions on injector performance, large eddy simulations were performed to model the turbulent multiphase flow development through a side-oriented singlehole diesel injector. Using Latin hypercube sampling, the design space spanning a range of fuel properties, operating conditions, and needle lifts were explored. Two techniques for dimensionality reduction, namely proper orthogonal decomposition and autoencoders, were compared to evaluate their accuracy in representing the flow in a reduced dimensional space. Finally, based on the findings from this work, recommendations are provided in using machine learning approaches within the context of emulation to construct reduced-ordermodels for internal flow development relevant to automotive applications.

42 ENGINEERING↗

DOE OSTI2013

A study of fluid-structure interaction on overlapping grids with a focus on flexible beams

Fluid-structure interaction problems appear in many areas of science and engineering. Adequately understanding these problems is crucial to the study of such disciplines as aeroelastic flutter, wind turbine performance, implosions and explosions, and hemodynamics, to name a few. One technique to explore these problems is the use of numerical simulations. Although methods for the accurate and efficient numerical simulation of many problems involving only flexible structures or those involving only fluids have existed for a long time, the simulation of coupled problems, in which a flexible structure (or structures) interact with fluids remains challenging. The source of the difficulty with these problems is the construction of schemes for the coupling between the fluid and the solid that are both accurate and stable. There are two general approaches to designing a coupling procedure. In the first, the so-called monolithic approach, a single solver is implemented that handles both the fluid equations and the solid equations in a single framework. In this scheme, the solver handles the fluid and solid equations simultaneously, resulting in a strong coupling between the two. The second approach, named the partitioned approach, handles the fluid and structure domains separately. Whereas in the monolithic scheme there is a single solver for both the fluid and the structure, in the partitioned scheme there are separate solvers for the fluid and the structure. This separation heavily restricts the communication and coordination that can occur between the two solvers. Typically the only communication done in these schemes is through the application of boundary conditions (where the fluid applies a boundary condition on the fluid, and the solid one (or more) on the fluid). This makes the implementation of partitioned schemes easy, especially because they can take advantage of existing algorithms and software developed for the simulation of fluid flow or computational mechanics. However, they have a weakness – accuracy and stability are much harder to achieve. Stability is a particular problem for these schemes, as they are prone to the so-called added-mass effect.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Solid Oxide Fuel Cell Cathodes: Unraveling the Relationship Between Structure, Surface Chemistry and Oxygen Reduction

In this work we have considered oxygen reduction reaction on LSM and LSCF cathode materials. In particular we have used various spectroscopic techniques to explore the surface composition, transition metal oxidation state, and the bonding environment of oxygen to understand the changes that occur to the surface during the oxygen reduction process. In a parallel study we have employed patterned cathodes of both LSM and LSCF cathodes to extract transport and kinetic parameters associated with the oxygen reduction process.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2016

Predicting Baseline for Analysis of Electricity Pricing

To understand the impact of new pricing structure on residential electricity demands, we need a baseline model that captures every factor other than the new price. The standard baseline is a randomized control group, however, a good control group is hard to design. This motivates us to devlop data-driven approaches. We explored many techniques and designed a strategy, named LTAP, that could predict the hourly usage years ahead. The key challenge in this process is that the daily cycle of electricity demand peaks a few hours after the temperature reaching its peak. Existing methods rely on the lagged variables of recent past usages to enforce this daily cycle. These methods have trouble making predictions years ahead. LTAP avoids this trouble by assuming the daily usage profile is determined by temperature and other factors. In a comparison against a well-designed control group, LTAP is found to produce accurate predictions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Resilience Design Patterns - A Structured Approach to Resilience at Extreme Scale (version 1.2)

We developed a new structured approach to the management of HPC resilience using the concept of resilience-based design patterns. In general, a design pattern is a repeatable solution to a commonly occurring problem. We identified the well-known solutions that are commonly used to deal with faults, errors and failures in HPC systems. In the initial design patterns specification (version 1.0), we described the various solutions, which address specific problems in the design of resilient HPC environments, in the form of patterns. Each pattern describes a problem caused by a fault, error or failure event in an HPC environment, and then describes the core of the solution of the problem in such a way that this solution may be adapted to different systems and implemented at different layers of the system stack. The catalog of these resilience design patterns provides designers with a collection of design elements. To construct complete resilience solutions using combinations of various patterns, we defined a framework that enhances HPC designers’ understanding of the important constraints and the opportunities for the design patterns to be implemented and deployed at various layers of the system stack. The design framework is also useful for establishing interfaces and mechanisms to coordinate flexible fault management across hardware and software components, as well as to consider the trade-off between performance, resilience, and power consumption when constructing a solution. The resilience design patterns specification version 1.1 included more detailed explanations of the pattern solutions, the context in which the patterns are applicable, and the implications for hardware or software design. It also provided several additional examples and detailed case studies to demonstrate the use of patterns to build realistic solutions. In this version 1.2 of the specification document, we have improved the pattern descriptions, including graphical representations of the pattern components. These improvements are largely based on critical comments, feedback and suggestions received from pattern experts and readers of the previous versions of the specification. The pattern classification has been modified to further clarify the relationships between pattern categories. This version of the specification also introduces a pattern language for resilience design patterns. The pattern language presents the patterns in the catalog as a network, revealing the relations among the resilience patterns. The language provides designers with the means to explore alternative techniques for handling a specific fault model that may have different effciency and complexity characteristics. Using the pattern language also enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack. The overall goal of this work is to provide hardware and software designers, as well as the users and operators of HPC systems, a systematic methodology for the design and evaluation of resilience technologies in HPC systems that keep scientific applications running to a correct solution in a timely and cost-effcient manner despite frequent faults, errors, and failures of various types.

97 MATHEMATICS AND COMPUTING↗