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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Matminer: An open source toolkit for materials data mining

As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Assessing the Sensitivity of Pourbaix Diagrams to Computational Protocols: Electrochemical Stability of Ni Oxides as a Case Study

Pourbaix diagrams stand as a useful tool in assessing and visualizing materials’ electrochemical stability and are widely used for electrocatalyst design. However, their reliability hinges on the accuracy of the chemical potentials of involved phases, which may bear uncertainties and can be significantly impacted by decision-making steps in the computational protocol. Here, this study introduces a robust sensitivity analysis framework, exemplified through a detailed examination of the computational Pourbaix diagram of Ni, the oxides of which are used as high-activity and cost-friendly catalysts for many electrochemical reactions. Quantities of interest derived from the Pourbaix diagram include the appearance and stability domain of the catalytically active Ni oxide phases along with the onset electrochemical potentials of phase transitions. These metrics can guide the design of operational conditions for Ni oxide electrocatalysts. We find that the employed DFT exchange-correlation functional has the most significant influence on the computed Pourbaix diagram. Uncertainties on crystal structures, along with their related ab initio energetics, are also found to affect the size of the phase stability domain. Higher-order coupling among input parameters is found to play a crucial role in influencing the appearance and distribution of Ni phases in the diagram. Our findings suggest a need to consider variations and uncertainties associated with the computational procedures on predicted Pourbaix diagrams for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Data refactoring↗
DOE OSTI2017

A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization: An Interim Report of Sandia Sub-Team Contributions

As we look ahead to next generation high performance computing platforms, the placement and movement of data is becoming the key-limiting factor on both performance and energy efficiency. Furthermore, the increased quantities of data the systems are capable of generating, in conjunction with the insufficient rate of improvements in the supporting I/0 infrastructure, is forcing applications away from the off-line post-processing of data towards techniques based on in ,situ analysis and visualization. Together, these challenges are shaping how we will both design and develop effective, performant and energy-efficient software. In particular, the challenges highlight the need for data and data-centric operations to be fundamental in the reasoning about, and optimization of, scientific workflows on extreme-scale architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Chen, Jieyang↗
DOE OSTI2015

D and D knowledge management information tool feasibility study for cross-platform mobile applications - 15704

The D and D Knowledge Management Information tool (D and D KM- IT) is a web-based knowledge management information tool built for the D and D user community. A feasibility study is being conducted on cross-platform application frameworks for their viability to the D and D KM-IT mobile needs. Currently, three main Operating Systems comprise the majority of the mobile market IOS, Android, and Windows, requiring a separate application for each device. Cross-development software allows the development of one application using one language, that can be ported or deployed on multiple devices with little effort. Using Xamarin, a native cross-platform framework, create a shared mobile application using Visual Studio. Build a D and D KMIT mobile application designed for the three major mobile platforms. Use Xamarin to compile the application into native applications for the three target platforms. Build and deploy the application on all three mobile platforms. Perform benchmark tests of the developed applications to analyze the performance on the three platforms. A large portion of the business logic of the application has been shared, eliminating development redundancy and minimizing planning, design, and validation time. The user interface development could not fully be shared cross-platform and some platform specific code must be individually implemented for each device. Maintenance, testing and design phases of the software engineering process were reduced from one for each device to having just one shared cycle processes. A less diverse skill-set for developers is required with cross-platform development. Some processes within the development cycle still require redundant activities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Increasing Radon Daughter Plate-out onto Superconducting Qubits

Radon daughter plate-out may pose a fundamental limitation to realizing large-scale superconducting quantum computers. Radon daughters plated-out on a superconducting qubit can decay, releasing energy into the substrate, producing phonons. Phonon-induced quasiparticles then generate bit-flip errors and reduce coherence times. We seek to increase plate-out on chips to enable future study of the impact of radon on coherence times. In this project, we utilize COMSOL Multiphysics simulations to visualize electric field configuration and model ion transport to finalize design of a device to increase radon plate-out on qubit chips.

Kay, Dax [Fermilab; Northwestern U.]↗
DOE OSTI2017

Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures

Visualizing the dynamical response of material heterointerfaces is increasingly important for the design of hybrid materials and structures with tailored properties for use in functional devices. In situ characterization of nanoscale heterointerfaces such as metal-semiconductor interfaces, which exhibit a complex interplay between lattice strain, electric potential, and heat transport at subnanosecond time scales, is particularly challenging. Here in this work, we use a laser pump/X-ray probe form of Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension the deformation of the core of a model core/shell semiconductor-metal (ZnO/Ni) nanorod following laser heating of the shell. We observe a rich interplay of radial, axial, and shear deformation modes acting at different time scales that are induced by the strain from the Ni shell. We construct experimentally informed models by directly importing the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical continuum model. The model elucidates the origin of the deformation modes observed experimentally. Our integrated imaging approach represents an invaluable tool to probe strain dynamics across mixed interfaces under operando conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Gibbs Energy Minimization Model for Solvent Extraction with Application to Rare-Earths Recovery

The emergence of technologies in which rare-earth elements provide critical functionality has increased the demand for these materials, with important implications for supply security. Recycling provides an option for mitigating supply risk and for creating economic value from the resale of recovered materials. While solvent extraction is a proven technology for rare-earth recovery and separation, its application often requires extensive trial-and-error experimentation to estimate parameter values and determine experimental design configurations. We describe a modeling strategy based on Gibbs energy minimization that incorporates parameter estimation for required thermodynamic properties as well as process design for solvent extraction and illustrate its applicability to rare earths separation. Visualization analysis during parameter estimation revealed a linear relationship between the standard enthalpies of the extractant and respective organo-metal complexes, analogous to the additivity principle for predicting molar volumes of organic compounds. Establishing this relationship reduced the size of the parameter estimation problem and yielded good agreement between model predictions and reported equilibrium extraction data, validating the property estimates for the organic phase species. Design exploration and optimization results map the space of feasible solvent extraction column configurations and identify the set of optimal design parameter values that meet recovery and purity targets.

Critical materials↗
DOE OSTI2018

Evaluation of Visualization Heuristics

Heuristics have been used since the early 1990's in the Human Computer Interaction (HCI) domain, for evaluating user interfaces. Most notably, heuristics developed by Nielsen and Molich (1990) have been used by the HCI community. Forsell and Johansson (2010) used the same methodology as Nielsen and Molich and developed a set of 10 heuristics for information visualization. Currently, neither the information visualization or the visual analytics community has adopted these heuristics. However, several studies have been conducted using heuristics. Hearst et al. (2015) found that using the heuristics for visualizations along with asking questions about the data resulted in complementary results as the questions about the data could compensate for heuristics that were difficult to understand and apply. Heli Väätäjä et al. (2016) found that heuristics related to interaction, veracity, and aesthetics needed to be added to the Forsell and Johansson (2010) set. They also noted that a lack of domain knowledge caused the evaluators issues in conducting a heuristic evaluation. We conducted a controlled experiment to determine what factors might impact the expert evaluators' capability to conduct a heuristic evaluation of a static information visualization. In particular, we wanted to understand how their familiarity with the visualizations and their experience in conducting heuristic evaluations impacted their evaluations of visualizations. We recruited 10 participants who were domain experts in the visualization field each having experience with one of more of the following: user experience design or research, user interface development, and human computer interaction research. We used a heuristic set proposed by Forsell and Johansson. Participants were also asked to complete a demographic survey in which they rated their experience with each visualization type generally, their experience conducting heuristic evaluations, their experience using each visualization type to extract information, and their experience developing and creating each visualization type. The participants were shown a series of 5 common visualizations (Scatterplots, Sunbursts, Tree Maps, Parallel Sets, and Area Graphs) all displaying the VAST 2008 Mini Challenge Two- Migrant Boats data . Participants were given a suggested analytical question related to each visualization to keep in mind as they applied the 10 heuristics to each visualization. They were asked if they could find any usability problems in the visualizations and which heuristic(s) helped them to identify these problems. The participants were asked to rate how relevant each heuristic was for evaluating each visualization along with rating how confident they felt in their ability to apply the heuristic to evaluate each visualization. At the conclusion of the study, participants provided qualitative feedback on the usability issues of each visualization. Additionally, we collected eye tracking data on 6 of the 10 participants. We will be using this data to determine how long participants looked at the various visualizations and what parts of the visualizations they focused on. We had two hypotheses for this empirical evaluation: 1.The Forsell and Johansson heuristics of Orientation and help, Data set reduction, and Prompting are less useful for static visualizations because they require some interaction in order to test completely. 2.Participants that do not have experience with heuristic evaluation will provide lower evaluation scores for the heuristics compared to those that have experience. Related to hypothesis 1, as our study used only static visualizations, interaction-related usability challenges should be harder to identify. This should result in lower usefulness ratings for those heuristics. Preliminary results indicate that participants found it more difficult to apply heuristics to unfamiliar visualizations.

Williams, Ryan G.↗
DOE OSTI2018

Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures

A key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visual exploration and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory. This paper examines several key design and performance issues related to the idea of in situ processing at extreme scale on modern platforms: Scalability, overhead, performance measurement and analysis, comparison and contrast with a traditional post hoc approach, and interfacing with simulation codes. We illustrate these principles in practice with studies, conducted on large-scale HPC platforms, that include a miniapplication and multiple science application codes, one of which demonstrates in situ methods in use at greater than 1M-way concurrency.

Ayachit, Utkarsh↗
DOE OSTI2021

Stable, high-performance, dendrite-free, seawater-based aqueous batteries

Metal anode instability, including dendrite growth, metal corrosion, and hetero-ions interference, occurring at the electrolyte/electrode interface of aqueous batteries, are among the most critical issues hindering their widespread use in energy storage. Herein, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals). An in-situ optical visualization coupled with finite element analysis is utilized to mimic actual electrochemical environments analogous to the actual aqueous batteries and analyze the complex electrochemical behaviors. The Zn-Mn alloy anodes achieved stability over thousands of cycles even under harsh electrochemical conditions, including testing in seawater-based aqueous electrolytes and using a high current density of 80 mA cm –2 . The proposed design strategy and the in-situ visualization protocol for the observation of dendrite growth set up a new milestone in developing durable electrodes for aqueous batteries and beyond.

25 ENERGY STORAGE↗
DOE OSTI2015

Quantitative impact characterization of aeronautical CFRP materials with non-destructive testing methods

In recent years, an increasing number of safety-relevant structures are designed and manufactured from carbon fiber reinforced polymers (CFRP) in order to reduce weight of airplanes by taking the advantage of their specific strength into account. Non-destructive testing (NDT) methods for quantitative defect analysis of damages are liquid- or air-coupled ultrasonic testing (UT), phased array ultrasonic techniques, and active thermography (IR). The advantage of these testing methods is the applicability on large areas. However, their quantitative information is often limited on impact localization and size. In addition to these techniques, Airbus Group Innovations operates a micro x-ray computed tomography (μ-XCT) system, which was developed for CFRP characterization. It is an open system which allows different kinds of acquisition, reconstruction, and data evaluation. One main advantage of this μ-XCT system is its high resolution with 3-dimensional analysis and visualization opportunities, which enables to gain important quantitative information for composite part design and stress analysis. Within this study, different NDT methods will be compared at CFRP samples with specified artificial impact damages. The results can be used to select the most suitable NDT-method for specific application cases. Furthermore, novel evaluation and visualization methods for impact analyzes are developed and will be presented.

42 ENGINEERING↗
DOE OSTI2025

Novel Results Visualization for Dynamic PSA and New Modeling Features in EMRALD

The Event Modeling Risk Assessment Linked Diagram (EMRALD) tool, developed at the Idaho National Laboratory (INL), was designed to simplify the creation of dynamic models and support various research projects. One of the primary goals of EMRALD was to provide visual methods for modeling. EMRALD consists of two main components: a web-based user interface for model development and a solve engine for running model simulations. Over time, it has evolved to meet the diverse needs of its users. Initially, EMRALD's results were simple text outputs with final key state percentages and uncertainty bounds. However, because EMRALD utilizes a three-phase discrete event simulation and tracks the paths of each simulation run leading to a key state, there is significant potential to analyze large sets of path results data, including state paths, events, and timing. Visualizing this data meaningfully posed a challenge. To address this, a novel time-based Sankey diagram was developed. EMRALD exports results data in a format that can be opened in this Sankey viewer, allowing users to visualize paths, occurrences, events, and probability data for the entire simulation run in a single diagram. Moreover, when EMRALD was first created, there were limited tools capable of meeting its graphical requirements, many of which are no longer supported. In 2024, a new web-based interface was developed using modern graphing tools, enabling additional modeling features. This paper discusses the new dynamic PSA results visualization capability and the enhanced modeling tools available in EMRALD.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Tuning Catalyst Activation and Utilization Via Controlled Electrode Patterning for Low-Loading and High-Efficiency Water Electrolyzers

An anode electrode concept of thin catalyst-coated liquid/gas diffusion layers (CCLGDLs), by integrating Ir catalysts with Ti thin tunable LGDLs with facile electroplating in proton exchange membrane electrolyzer cells (PEMECs), is proposed. The CCLGDL design with only 0.08 mg Ir cm -2 can achieve comparative cell performances to the conventional commercial electrode design, saving ~97% Ir catalyst and augmenting a catalyst utilization to ~24 times. CCLGDLs with regulated patterns enable insight into how pattern morphology impacts reaction kinetics and catalyst utilization in PEMECs. A specially designed two-sided transparent reaction-visible cell assists the in situ visualization of the PEM/electrode reaction interface for the first time. Oxygen gas is observed accumulating at the reaction interface, limiting the active area and increasing the cell impedances. In this work, it is demonstrated that mass transport in PEMECs can be modified by tuning CCLGDL patterns, thus improving the catalyst activation and utilization. The CCLGDL concept promises a future electrode design strategy with a simplified fabrication process and enhanced catalyst utilization. Furthermore, the CCLGDL concept also shows great potential in being a powerful tool for in situ reaction interface research in PEMECs and other energy conversion devices with solid polymer electrolytes.

08 HYDROGEN↗
DOE OSTI2016

Institutional Transformation (IX) 2.5 Building Module Help Manual

The Institutional Transformation (IX) building module is a software tool developed at Sandia National Laboratories to evaluate energy conservation measures (ECMs) on hundreds of DOE-2 building energy models simultaneously. In IX, ECMs can be designed through parameterizing DOE-2 building models and doing further processing via visual basic for applications subroutines. IX provides the functionality to handle multiple building models for different years, which enables incrementally changing a site of hundreds of buildings over time. It also enables evaluation of the effects of changing climate, comparisons between data and modeling results, and energy use of centralized utility buildings (CUBs). IX consists of a Microsoft Excel® user interface, Microsoft Access® database, and Microsoft Excel® CUB build utility whose functionalities are described in detail in this report. In addition to descriptions of the user interfaces, descriptions of every ECM already designed in IX is included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Visualization of flow interaction in a channel flow produced by a pair of helically coiled rods

Helically coiled tubes have been considered in the design of steam generators or heat exchangers of next generation nuclear power plants. Its compactness, efficiency, and the capability to absorb thermal expansion are desirable for nuclear reactor designs. However, the complex flow generated by the helically coiled geometry can result in flow induced vibration (FIV). In order to predict the FIV, there have been efforts using Computational Fluid dynamics (CFD)4, 5 to be coupled with multi-mechanics simulations. However, it is required to validate CFD to have confidence in capturing the flow structure characteristics of the transient complex flow behavior and fluctuation. In the present study, a simplified helically coiled steam generator (HCSG) design experiment was built acquiring data for CFD validation purpose. It is not perfect representation of the multiple rods, however, the current test facility produced transient data of the flow interaction between the rods and flow fluctuations near the rods. Particle Image Velocimetry (PIV) was applied to visualize the turbulent flow in a channel with slant rods. The two dimensional turbulent flow fields were analyzed. The velocity components were defined as below. u = U + u' (1) v = V + v' (2) where u is the lateral velocity on x-axis, v is the vertical velocity on y-axis, U and V are the mean velocities, and u' and v' are the fluctuation. Reynolds number, Re, was calculated using the rod diameter, d = 15.9 mm, and the upstream approach velocity, V{sub 0} = 0.5 m/s. Re = V{sub 0} d/η (3) where η is the kinematic viscosity of water. The experiment was conducted at Re ≅ 9,000 considering the currently reasonable computing power. Flow visualization in a flow channel produced by helically coiled rods was performed using PIV. The mean velocity field and streamlines were presented in this paper. The vortical flow structures in the cavity between rods were observed. Because of the asymmetric geometry, the flow profile was skewed. Additional measurements and transient analysis will be conducted to produce benchmark data for FIV study using CFD. Also, a test facility with a 5-rod heat exchanger design is operating to produce more data as a further work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗