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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High-rate electroreduction of carbon monoxide to multi-carbon products

Carbon monoxide electrolysis has previously been reported to yield enhanced multi-carbon (C 2+ ) Faradaic efficiencies of up to ~55%, but only at low reaction rates. This is due to the low solubility of CO in aqueous electrolytes and operation in batch-type reactors. Here, we present a high-performance CO flow electrolyser with a well controlled electrode–electrolyte interface that can reach total current densities of up to 1 A cm –2 , together with improved C 2+ selectivities. Computational transport modelling and isotopic C 18 O reduction experiments suggest that the enhanced activity is due to a higher surface pH under CO reduction conditions, which facilitates the production of acetate. Here, at optimal operating conditions, we achieve a C 2+ Faradaic efficiency of ~91% with a C 2+ partial current density over 630 mA cm –2 . Further investigations show that maintaining an efficient triple-phase boundary at the electrode–electrolyte interface is the most critical challenge in achieving a stable CO/CO 2 electrolysis process at high rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Control over emergence and alignment of transient blisters in thermo-responsive gels using hierarchically patterned substrates

Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.

42 ENGINEERING↗
DOE OSTI2016

Photoelectron imaging spectroscopy of niobium mononitride anion NbN{sup −}

In this gas-phase photoelectron spectroscopy study, we present the electron binding energy spectrum and photoelectron angular distributions of NbN{sup −} by the velocity-map imaging technique. The electron binding energy of NbN{sup −} is measured to be 1.42 ± 0.02 eV from the X band maximum which defines the 0-0 transition between ground states of anion and neutral. Theoretical binding energies which are the vertical and adiabatic detachment energies are computed by density functional theory to compare them with experiment. The ground state of NbN{sup −} is assigned to the {sup 2}Δ{sub 3/2} state and then the electronic transitions originating from this state into X{sup 3}Δ{sub Ω} (Ω = 1-3), a{sup 1}Δ{sub 2}, A{sup 3}Σ{sub 1}{sup −}, and b{sup 1}Σ{sub 0}{sup +} states of NbN are reported to interpret the spectral features. As a prospective study for catalytic materials, spectral features of NbN{sup −} are compared with those of isovalent ZrO{sup −} and Pd{sup −}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Ab initio spectroscopy and ionic conductivity of water under Earth mantle conditions

The phase diagram of water at extreme conditions plays a critical role in Earth and planetary science, yet remains poorly understood. Here we report a first-principles investigation of the liquid at high temperature, between 11 GPa and 20 GPa—a region where numerous controversial results have been reported over the past three decades. Our results are consistent with the recent estimates of the water melting line below 1,000 K and show that on the 1,000-K isotherm the liquid is rapidly dissociating and recombining through a bimolecular mechanism. We found that short-lived ionic species act as charge carriers, giving rise to an ionic conductivity that at 11 GPa and 20 GPa is six and seven orders of magnitude larger, respectively, than at ambient conditions. Conductivity calculations were performed entirely from first principles, with no a priori assumptions on the nature of charge carriers. Despite frequent dissociative events, we observed that hydrogen bonding persists at high pressure, up to at least 20 GPa. Our computed Raman spectra, which are in excellent agreement with experiment, show no distinctive signatures of the hydronium and hydroxide ions present in our simulations. Instead, we found that infrared spectra are sensitive probes of molecular dissociation, exhibiting a broad band below the OH stretching mode ascribable to vibrations of complex ions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Measurements of tungsten migration in the DIII-D divertor

An experimental study of migration of tungsten in the DIII-D divertor is described, in which the outer strike point of L-mode plasmas was positioned on a toroidal ring of tungsten-coated metal inserts. Net deposition of tungsten on the divertor just outside the strike point was measured on graphite sarnples exposed to various plasma durations using the Divertor Materials Evaluation System (DiMES) system. Tungsten coverage, measured by Rutherford Backscattering Spectroscopy (RBS), was found to be low and nearly independent of both radius and exposure time closer to the strike point, whereas farther from the strike point the W coverage was much larger and increased with exposure time. Depth profiles from RBS show this was due to accumulation of thicker mixed-material deposits farther from the strike point where the plasma temperature is lower. These results are consistent with a low near-surface steady-state coverage on graphite undergoing net erosion, and continuing accumulation in regions of net deposition. This experiment provides data needed to validate, and further improve computational simulations of erosion and deposition of material on plasma-facing components and transport of impurities in magnetic fusion devices. Such simulations are underway and will be reported later.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗
DOE OSTI2020

Fast and Universal Kohn-Sham Density Functional Theory Algorithm for Warm Dense Matter to Hot Dense Plasma

Understanding many processes, e.g., fusion experiments, planetary interiors, and dwarf stars, depends strongly on microscopic physics modeling of warm dense matter and hot dense plasma. This complex state of matter consists of a transient mixture of degenerate and nearly free electrons, molecules, and ions. This regime challenges both experiment and analytical modeling, necessitating predictive ab initio atomistic computation, typically based on quantum mechanical Kohn-Sham density functional theory (KS-DFT). However, cubic computational scaling with temperature and system size prohibits the use of DFT through much of the warm dense matter regime. A recently developed stochastic approach to KS-DFT can be used at high temperatures, with the exact same accuracy as the deterministic approach, but the stochastic error can converge slowly and it remains expensive for intermediate temperatures (< 50 eV). Here we have developed a universal mixed stochastic-deterministic algorithm for DFT at any temperature. This approach leverages the physics of KS-DFT to seamlessly integrate the best aspects of these different approaches. We demonstrate that this method significantly accelerated self-consistent field calculations for temperatures from 3 to 50 eV, while producing stable molecular dynamics and accurate diffusion coefficients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Qubit Assignment Using Time Reversal

As quantum computers with large numbers of qubits become increasingly available, experiments executed on a given device may not utilize all available qubits. In this case, the outcome of executing a quantum program will depend on the ability to efficiently select a subset of high-performing physical qubits. For any given quantum program and device there are many ways to assign physical qubits for execution of the program, and assignments will differ in performance due to the variability in quality across qubits and entangling operations on a single device. Evaluating the performance of each assignment using fidelity estimation introduces significant experimental overhead and will be infeasible for many applications, while relying on standard device benchmarks provides incomplete information about the performance of any specific program. Furthermore, the number of possible assignments grows combinatorially in the number of qubits on the device and in the program, motivating the use of heuristic optimization techniques. We demonstrate a practical solution to the problem of qubit assignment by using simulated annealing with a cost function based on the Loschmidt echo, a diagnostic that measures the reversibility of a quantum process. We provide theoretical justification for this choice of cost function by demonstrating that the optimal qubit assignment coincides with the optimal qubit assignment based on state fidelity in the weak error limit, and we provide experimental justification using diagnostics performed on Google’s superconducting qubit devices. We then establish the performance of simulated annealing for qubit assignment using classical simulations of noisy devices as well as optimization experiments performed on a quantum processor. Our results demonstrate that the use of Loschmidt echoes and simulated annealing provides a scalable and flexible approach to optimizing qubit assignment on near-term hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks.

Decaf↗
DOE OSTI2023

Why is the winner the best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multi- center study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), im- age preprocessing (97%), data curation (79%), and post- processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

Eisenmann, Matthias↗
DOE OSTI2015

3D liver segmentation using multiple region appearances and graph cuts

Purpose: Efficient and accurate 3D liver segmentations from contrast-enhanced computed tomography (CT) images play an important role in therapeutic strategies for hepatic diseases. However, inhomogeneous appearances, ambiguous boundaries, and large variance in shape often make it a challenging task. The existence of liver abnormalities poses further difficulty. Despite the significant intensity difference, liver tumors should be segmented as part of the liver. This study aims to address these challenges, especially when the target livers contain subregions with distinct appearances. Methods: The authors propose a novel multiregion-appearance based approach with graph cuts to delineate the liver surface. For livers with multiple subregions, a geodesic distance based appearance selection scheme is introduced to utilize proper appearance constraint for each subregion. A special case of the proposed method, which uses only one appearance constraint to segment the liver, is also presented. The segmentation process is modeled with energy functions incorporating both boundary and region information. Rather than a simple fixed combination, an adaptive balancing weight is introduced and learned from training sets. The proposed method only calls initialization inside the liver surface. No additional constraints from user interaction are utilized. Results: The proposed method was validated on 50 3D CT images from three datasets, i.e., Medical Image Computing and Computer Assisted Intervention (MICCAI) training and testing set, and local dataset. On MICCAI testing set, the proposed method achieved a total score of 83.4 ± 3.1, outperforming nonexpert manual segmentation (average score of 75.0). When applying their method to MICCAI training set and local dataset, it yielded a mean Dice similarity coefficient (DSC) of 97.7% ± 0.5% and 97.5% ± 0.4%, respectively. These results demonstrated the accuracy of the method when applied to different computed tomography (CT) datasets. In addition, user operator variability experiments showed its good reproducibility. Conclusions: A multiregion-appearance based method is proposed and evaluated to segment liver. This approach does not require prior model construction and so eliminates the burdens associated with model construction and matching. The proposed method provides comparable results with state-of-the-art methods. Validation results suggest that it may be suitable for the clinical use.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗
DOE OSTI2016

Summary of Fe opacity measurement platform

This powerpoint presentation goes over the Fe opacity measurement platform, including how the experiment works, what can be gathered from the measurements, what can be gathered from the simulations, and the limitations of the experiment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Energy Frontier Research With ATLAS: Final Report

The Boston University (BU) group is playing key roles across the ATLAS experiment: in detector operations, the online trigger, the upgrade, computing, and physics analysis. Our team has been critical to the maintenance and operations of the muon system since its installation. During Run 1 we led the muon trigger group and that responsibility continues into Run 2. BU maintains and operates the ATLAS Northeast Tier 2 computing center. We are actively engaged in the analysis of ATLAS data from Run 1 and Run 2. Physics analyses we have contributed to include Standard Model measurements (W and Z cross sections, t\bar{t} differential cross sections, WWW^* production), evidence for the Higgs decaying to \tau^+\tau^-, and searches for new phenomena (technicolor, Z' and W', vector-like quarks, dark matter).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Novel methods for the time-dependent Maxwell's equations and their applications

This dissertation investigates three different mathematical models based on the time-domain Maxwell's equations using three different numerical methods: a Yee scheme using a non-uniform grid, a nodal discontinuous Galerkin (nDG) method, and a newly developed discontinuous Galerkin method named the weak Galerkin (WG) method. The non-uniform Yee scheme is first applied to an electromagnetic metamaterial model. Stability and superconvergence error results are proved for the method, which are then confirmed through numerical results. Additionally, a numerical simulation of backwards wave propagation through a negative-index metamaterial is given using the presented method. Next, the nDG method is used to simulate signal propagation through a corrugated coaxial cable through the use of axisymmetric Maxwell's equations. Stability and error analysis are performed for the semi-discrete method, and are verified through numerical results. The nDG method is then used to simulate signal propagation through coaxial cables with a number of different corrugations. Finally, the WG method is developed for the standard time-domain Maxwell's equations. Similar to the other methods, stability and error analysis are performed on the method and are verified through a number of numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

CTF (Subchannel) Calculations and Validation L3:VVI.H2L.P15.01

The goal of the Verification and Validation Implementation (VVI) High to Low (Hi2Lo) process is utilizing a validated model in a high resolution code to generate synthetic data for improvement of the same model in a lower resolution code. This process is useful in circumstances where experimental data does not exist or it is not sufficient in quantity or resolution. Data from the high-fidelity code is treated as calibration data (with appropriate uncertainties and error bounds) which can be used to train parameters that affect solution accuracy in the lower-fidelity code model, thereby reducing uncertainty. This milestone presents a demonstration of the Hi2Lo process derived in the VVI focus area. The majority of the work performed herein describes the steps of the low-fidelity code used in the process with references to the work detailed in the companion high-fidelity code milestone (Reference 1). The CASL low-fidelity code used to perform this work was Cobra Thermal Fluid (CTF) and the high-fidelity code was STAR-CCM+ (STAR). The master branch version of CTF (pulled May 5, 2017 – Reference 2) was utilized for all CTF analyses performed as part of this milestone. The statistical and VVUQ components of the Hi2Lo framework were performed using Dakota version 6.6 (release date May 15, 2017 – Reference 3). Experimental data from Westinghouse Electric Company (WEC – Reference 4) was used throughout the demonstrated process to compare with the high-fidelity STAR results. A CTF parameter called Beta was chosen as the calibration parameter for this work. By default, Beta is defined as a constant mixing coefficient in CTF and is essentially a tuning parameter for mixing between subchannels. Since CTF does not have turbulence models like STAR, Beta is the parameter that performs the most similar function to the turbulence models in STAR. The purpose of the work performed in this milestone is to tune Beta to an optimal value that brings the CTF results closer to those measured in the WEC experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Critical Experiment Benchmark Results using MCNP6.2 Unstructured Mesh

The purpose of this report is to document the results of five critical experiment benchmarks modeled using the unstructured mesh (UM) geometry capability in MCNP®1 code, version 6.2. LANL currently has a vast critical experiment benchmark library with over 1100 cases, modeled using constructive solid geometry (CSG) and packaged with Whisper-1.1. Validation efforts for the purposes of nuclear criticality safety typically focus on benchmark libraries built using CSG models. Results of UM geometry models are compared with CSG results and the critical experiment k-effective from the ICSBEP handbook. All computed k-effective results in this study are well within 1% of the experimental result.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

U.S. Industry Opportunities for Advanced Nuclear Technology Development Phase II (Final Report)

This limited scope study aims at preserving the results of experimental programs for the safety of light water cooled and advanced reactors by locating and documenting, to the extent possible, where the experimental test information for these programs has been archived. The Light Water Reactor Data Preservation Activity Team initially identified seven (7) experimental programs, exceeding the required five (5) in the scope of work, which were determined to be “at risk” of potentially losing valuable data. The seven (7) experimental programs/subject areas identified are (descriptions of each experiment/experience are provided in Section 3.0): 1. FERMI-1 Reactor Accident 2. Fission Product Behavior During the In-Pile Severe Fuel Damage Test SFD I-4 3. Containment Iodine Computer Code Exercise Based on Radioiodine Test Facility (RTF) Experiment 4. Wide Range Piping Integrity Demonstration (WIND) Project 5. Iodine Chemical Research in Canada 6. High Temperature Fission Product Chemistry and Transport in Steam 7. Anything related to radioactive Methyl Iodide.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗