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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Experimental Investigation of Fuel Staging Effect on Modal Dynamics of Thermoacoustic Azimuthal Instabilities in a Multi-Nozzle Can Combustor

Abstract This paper analyzes the dynamics of unstable azimuthal thermoacoustic modes in a lean premixed combustor. Azimuthal modes can be decomposed into two counter rotating waves where they can either compete and potentially suppress one of them (spinning) or coexist (standing), depending on the operating conditions. This paper describes experimental results of the dynamical behaviors of these two waves. The experimental data were taken at different mass flow rates as well as different azimuthal fuel staging in a multi-nozzle can combustor. It is shown that at a low flow rate with uniform fuel distribution, the two waves have similar amplitudes, giving rise to a standing wave. However, the two amplitudes are slowly oscillating out of phase to each other, and the phase difference between the two waves also shows oscillatory behavior. For an intermediate flow rate, the dynamics show intermittency between standing and spinning waves, indicating that the system is bistable. In addition, the phase difference dramatically shifts when the mode switches between standing and spinning waves. For a high flow rate, the system stabilizes at a spinning wave most of the time. These experimental observations demonstrate that not only the amplitudes of two waves but also the phase difference plays an important role in the dynamics of azimuthal mode. For non-uniform azimuthal fuel staging, the modal dynamics exhibit only an oscillatory standing wave behavior regardless of the mass flow rate. Compared to the uniform fuel staging, however, the pressure magnitude is considerably reduced, which provides a potential strategy to mitigate and/or suppress the instabilities.

Kim, J.↗
DOE OSTI2018

Review Article: Stress in thin films and coatings: Current status, challenges, and prospects

The issue of stress in thin films and functional coatings is a persistent problem in materials science and technology that has congregated many efforts, both from experimental and fundamental points of view, to get a better understanding on how to deal with, how to tailor, and how to manage stress in many areas of applications. With the miniaturization of device components, the quest for increasingly complex film architectures and multiphase systems and the continuous demands for enhanced performance, there is a need toward the reliable assessment of stress on a submicron scale from spatially resolved techniques. Also, the stress evolution during film and coating synthesis using physical vapor deposition (PVD), chemical vapor deposition, plasma enhanced chemical vapor deposition (PECVD), and related processes is the result of many interrelated factors and competing stress sources so that the task to provide a unified picture and a comprehensive model from the vast amount of stress data remains very challenging. This article summarizes the recent advances, challenges, and prospects of both fundamental and applied aspects of stress in thin films and engineering coatings and systems, based on recent achievements presented during the 2016 Stress Workshop entitled “Stress Evolution in Thin Films and Coatings: from Fundamental Understanding to Control.” Evaluation methods, implying wafer curvature, x-ray diffraction, or focused ion beam removal techniques, are reviewed. Selected examples of stress evolution in elemental and alloyed systems, graded layers, and multilayer-stacks as well as amorphous films deposited using a variety of PVD and PECVD techniques are highlighted. Based on mechanisms uncovered by in situ and real-time diagnostics, a kinetic model is outlined that is capable of reproducing the dependence of intrinsic (growth) stress on the grain size, growth rate, and deposited energy. The problems and solutions related to stress in the context of optical coatings, inorganic coatings on plastic substrates, and tribological coatings for aerospace applications are critically examined. This review also suggests strategies to mitigate excessive stress levels from novel coating synthesis perspectives to microstructural design approaches, including the ability to empower crack-based fabrication processes, pathways leading to stress relaxation and compensation, as well as management of the film and coating growth conditions with respect to energetic ion bombardment. Future opportunities and challenges for stress engineering and stress modeling are considered and outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2014

TU-A-18A-01: Basic Principles of PET/CT, Calibration Methods and Contrast Recovery Across Multiple Cameras

This continuing education session will discuss the physical principles of PET/CT imaging and characterization of contrast recovery using accreditation phantoms. A detailed overview will be given on the physical principles of PET including positron decay physics, 2D and 3D data acquisition, time-of-flight, scatter correction, CT attenuation correction, and image reconstruction. Instrument quality control and calibration procedures will be discussed. Technical challenges, common image artifacts and strategies to mitigate these issues will also be discussed. Data will be presented on acquisition techniques and reconstruction parameters affecting contrast recovery. The discussion will emphasize the minimization of reconstruction differences in quantification metrics such as SUV and contrast recovery coefficients for the NEMA and ACR clinical trial phantoms. Data from new and older generation scanners will be shown including comparison of contrast recovery measurements to their analytical solutions. The goal of this session is to update attendees on the quality control and calibration of PET/CT scanners, on methods to establish a common calibration for PET/CT scanners to control for instrument variance across multiple sites. Learning Objectives: Review the physical principles of PET/CT, quality control and calibration Gain further understanding on how to apply techniques for improving quantitative agreement across multiple cameras Describe the differences between measured and expected contrast recovery for the NEMA and ACR PET phantoms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

TU-F-17A-05: Calculating Tumor Trajectory and Dose-Of-The-Day for Highly Mobile Tumors Using Cone-Beam CT Projections

Purpose: Cone-beam CT (CBCT) projection images provide anatomical data in real-time over several respiratory cycles, forming a comprehensive picture of tumor movement. We developed a method using these projections to determine the trajectory and dose of highly mobile tumors during each fraction of treatment. Methods: CBCT images of a respiration phantom were acquired, where the trajectory mimicked a lung tumor with high amplitude (2.4 cm) and hysteresis. A template-matching algorithm was used to identify the location of a steel BB in each projection. A Gaussian probability density function for tumor position was calculated which best fit the observed trajectory of the BB in the imager geometry. Two methods to improve the accuracy of tumor track reconstruction were investigated: first, using respiratory phase information to refine the trajectory estimation, and second, using the Monte Carlo method to sample the estimated Gaussian tumor position distribution. 15 clinically-drawn abdominal/lung CTV volumes were used to evaluate the accuracy of the proposed methods by comparing the known and calculated BB trajectories. Results: With all methods, the mean position of the BB was determined with accuracy better than 0.1 mm, and root-mean-square (RMS) trajectory errors were lower than 5% of marker amplitude. Use of respiratory phase information decreased RMS errors by 30%, and decreased the fraction of large errors (>3 mm) by half. Mean dose to the clinical volumes was calculated with an average error of 0.1% and average absolute error of 0.3%. Dosimetric parameters D90/D95 were determined within 0.5% of maximum dose. Monte-Carlo sampling increased RMS trajectory and dosimetric errors slightly, but prevented over-estimation of dose in trajectories with high noise. Conclusions: Tumor trajectory and dose-of-the-day were accurately calculated using CBCT projections. This technique provides a widely-available method to evaluate highly-mobile tumors, and could facilitate better strategies to mitigate or compensate for motion during SBRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Calculating tumor trajectory and dose-of-the-day using cone-beam CT projections

Purpose: Cone-beam CT (CBCT) projection images provide anatomical data in real-time over several respiratory cycles, forming a comprehensive picture of tumor movement. The authors developed and validated a method which uses these projections to determine the trajectory of and dose to highly mobile tumors during each fraction of treatment. Methods: CBCT images of a respiration phantom were acquired, the trajectory of which mimicked a lung tumor with high amplitude (up to 2.5 cm) and hysteresis. A template-matching algorithm was used to identify the location of a steel BB in each CBCT projection, and a Gaussian probability density function for the absolute BB position was calculated which best fit the observed trajectory of the BB in the imager geometry. Two modifications of the trajectory reconstruction were investigated: first, using respiratory phase information to refine the trajectory estimation (Phase), and second, using the Monte Carlo (MC) method to sample the estimated Gaussian tumor position distribution. The accuracies of the proposed methods were evaluated by comparing the known and calculated BB trajectories in phantom-simulated clinical scenarios using abdominal tumor volumes. Results: With all methods, the mean position of the BB was determined with accuracy better than 0.1 mm, and root-mean-square trajectory errors averaged 3.8% ± 1.1% of the marker amplitude. Dosimetric calculations using Phase methods were more accurate, with mean absolute error less than 0.5%, and with error less than 1% in the highest-noise trajectory. MC-based trajectories prevent the overestimation of dose, but when viewed in an absolute sense, add a small amount of dosimetric error (<0.1%). Conclusions: Marker trajectory and target dose-of-the-day were accurately calculated using CBCT projections. This technique provides a method to evaluate highly mobile tumors using ordinary CBCT data, and could facilitate better strategies to mitigate or compensate for motion during stereotactic body radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Systems-level investigation of aqueous batteries for understanding the benefit of water-in-salt electrolyte by synchrotron nanoimaging

Water-in-salt (WIS) electrolytes provide a promising path toward aqueous battery systems with enlarged operating voltage windows for better safety and environmental sustainability. In this work, a new electrode couple, LiV 3 O 8 -LiMn 2 O 4 , for aqueous Li-ion batteries is investigated to understand the mechanism by which the WIS electrolyte improves the cycling stability at an extended voltage window. Operando synchrotron transmission x-ray microscopy on the LiMn 2 O 4 cathode reveals that the WIS electrolyte suppresses the mechanical damage to the electrode network and dissolution of the electrode particles, in addition to delaying the water decomposition process. Because the viscosity of WIS is notably higher, the reaction heterogeneity of the electrodes is quantified with x-ray absorption spectroscopic imaging, visualizing the kinetic limitations of the WIS electrolyte. This work furthers the mechanistic understanding of electrode–WIS electrolyte interactions and paves the way to explore the strategy to mitigate their possible kinetic limitations in three-dimensional architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗
DOE OSTI2022

Multiple Mechanisms for Copper Uptake by Methylosinus trichosporium OB3b in the Presence of Heterologous Methanobactin

Methanotrophs play a critical role in the global carbon cycle, as well as in future strategies for mitigating climate change through their consumption of methane, a trace atmospheric gas much more potent than carbon dioxide in global warming potential. Copper uptake is critical for methanotrophic activity, and here, we show different approaches for copper uptake.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

When Labels Fall Short: Property Graph Simulation via Blending of Network Structure and Vertex Attributes

Property graphs can be used to represent heterogeneous networks with attributed vertices and edges. Given one property graph, simulating another graph with same or greater size with identical statistical properties with respect to the attributes and connectivity is critical for privacy preservation and benchmarking purposes. In this work we tackle the problem of capturing the statistical dependence of the edge connectivity on the vertex labels and using the same distribution to regenerate property graphs of the same or expanded size in a scalable manner. However, accurate simulation becomes a challenge when the attributes do not completely explain the network structure. We propose the Property Graph Model (PGM) approach that uses an attribute (or label) augmentation strategy to mitigate the problem and preserve the graph connectivity as measured via degree distribution, vertex label distributions and edge connectivity. Our proposed algorithm is scalable with a linear complexity in the number of edges in the target graph. We illustrate the efficacy of the PGM approach in regenerating and expanding the datasets by leveraging two distinct illustrations.

Visweswara Sathanur, Arun↗
DOE OSTI2024

Performance Losses and Current-Driven Recovery from Cation Contaminants in PEM Water Electrolysis

Water contaminants are a common cause of failure for polymer electrolyte membrane (PEM) electrolyzers in the field as well as a confounding factor in research on cell performance and durability. In this study, we investigated the performance impacts of feed water containing representative tap water cations at concentrations ranging from 0.5–500 μ M, with conductivities spanning from ASTM Type II to tap-water levels. We present multiple diagnostic signatures to help identify the presence of contaminants in PEM electrolysis cells. Through analysis of polarization curves and impedance spectroscopy to understand the origins of performance losses, we found that a switch from the acidic to alkaline hydrogen evolution mechanism is a key factor in contaminated cell behavior. Finally, we demonstrated that this mechanism switching can be harnessed to remove cation contaminants and recover cell performance without the use of an acid wash. We demonstrated near-complete recovery of cells contaminated with sodium and calcium, and partial recovery of a cell contaminated with iron, which was further investigated by post-mortem microscopy. The improved understanding of contaminant impacts from this work can inform development of strategies to mitigate or recover performance losses as well as improve the consistency and rigor of electrolysis research.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Redox Activity Modulation in Extended Fluorenone-Based Flow Battery Electrolytes with π-π Stacking Effect

Redox flow battery shows promise for grid-scale energy storage. Aqueous organic redox flow batteries are particularly popular due to their potentially low material cost and safe water-based electrolyte. Commonly, redox active molecules used in this field feature aromatic rings, and increasing π-aromatic conjugation has been a popular strategy to achieve high energy density, high power density, and reduced crossover in new material design. However, this approach can inadvertently hinder redox activity depending on redox mechanism. This study reveals the underlying π-π stacking effect in extended aromatic redox active compounds, where aromatic radical intermediates are involved in the redox process. We report a molecular design strategy to mitigate the negative effect of π-π stacking by altering solvation dynamics and introducing molecular steric hindrance.

25 ENERGY STORAGE↗
DOE OSTI2025

Building High-Energy Silicon-Containing Batteries Using Off-The-Shelf Materials

The technology of silicon anodes appears to be reaching maturity, with high-energy Si cells already in pilot-scale production. However, the performance of these systems can be difficult to replicate in academic settings, making it challenging to translate research findings into solutions that can be implemented by the battery industry. Part of this difficulty arises from the lack of access to engineered Si particles and anodes, as electrode formulations and the materials themselves have become valuable intellectual property for emerging companies. Here, we summarize the efforts by Argonne’s Cell Analysis, Modeling, and Prototyping (CAMP) Facility in developing Si-based prototypes made entirely from commercially available materials. We describe the many challenges we encountered when testing high-loading electrodes (>5 mAh cm −2 ) and discuss strategies to mitigate them. With the right electrode and electrolyte design, we show that our pouch cells containing ≥ 70 wt% SiO x can achieve 600–1,000 cycles at C/3 and meet projected energy targets of 700 Wh L −1 and 350 Wh kg −1 . These results provide a practical reference for research teams seeking to advance silicon-anode development using accessible materials.

25 ENERGY STORAGE↗
DOE OSTI2016

Resonance in Fast-Wave Amplitude in the Periphery of Cylindrical Plasmas and Application to Edge Losses of Wave Heating Power in Tokamaks

Heating magnetically confined plasmas using waves in the ion-cyclotron range of frequencies typically requires coupling these waves over a steep density gradient. This process has produced an unexpected and deleterious phenomenon on the National Spherical Torus eXperiment (NSTX): a prompt loss of wave power along magnetic field lines in front of the antenna to the divertor. Understanding this loss may be key to achieving effective heating and expanding the operational space of NSTX-Upgrade. Here, we propose that a new type of mode, which conducts a significant fraction of the total wave power in the low-density peripheral plasma, is driving these losses. We demonstrate the existence of such modes, which are distinct from surface modes and coaxial modes, in a cylindrical cold-plasma model when a half wavelength structure fits into the region outside the core plasma. The latter condition generalizes the previous hypothesis regarding the occurence of the edge losses and may explain why full-wave simulations predict these losses in some cases but not others. If valid, this condition implies that outer gap control is a potential strategy for mitigating the losses in NSTX-Upgrade in addition to raising the magnetic field or influencing the edge density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗
DOE OSTI2024

Binary Quantum Control Optimization with Uncertain Hamiltonians

Optimizing the controls of quantum systems plays a crucial role in advancing quantum technologies. The time-varying noises in quantum systems and the widespread use of inhomogeneous quantum ensembles raise the need for high-quality quantum controls under uncertainties. In this paper, we consider a stochastic discrete optimization formulation of a discretized binary optimal quantum control problem involving Hamiltonians with predictable uncertainties. We propose a sample-based reformulation that optimizes both risk-neutral and risk-averse measurements of control policies, and solve these with two gradient-based algorithms using sum-up-rounding approaches. Furthermore, we discuss the differentiability of the objective function and prove upper bounds of the gaps between the optimal solutions to binary control problems and their continuous relaxations. We conduct numerical simulations on various sized problem instances based on two applications of quantum pulse optimization; we evaluate different strategies to mitigate the impact of uncertainties in quantum systems. In conclusion, we demonstrate that the controls of our stochastic optimization model achieve significantly higher quality and robustness compared with the controls of a deterministic model.

conditional value-at-risk (CVaR)↗
DOE OSTI2023

Solar Farm Development Impacts on Eastern Box Turtle ( Terrapene carolina ) Home Ranges

Eastern Box Turtle (Terrapene carolina) populations have declined drastically since 1970 because of continued destruction and fragmentation of their habitat. Although they are known to shift their home ranges because of environmental degradation, it is unknown how solar arrays impact Eastern Box Turtles. From 2011–2018, we collected data on Eastern Box Turtle movement and occupancy in a 79-ha solar farm. The solar farm is divided into six fenced areas, each containing wildlife openings for movement of terrestrial fauna every 23 m around the fenced solar arrays. For this work, we hypothesized that the solar arrays changed the home range sizes of turtles that interacted with the field. We fitted 41 Eastern Box Turtles with radio transmitters and tracked their locations twice per week in June–August from 2011–2018. Seventeen turtles had home ranges that overlapped with the solar arrays whereas 24 turtles had home ranges that never interacted with the solar arrays. We calculated home range sizes and tested for differences between overlapping and nonoverlapping groups. We further considered if the number of observations within the solar farm impacted home range size and displacement. We found that Eastern Box Turtles that used the solar farm exhibited 55–83% larger home ranges on average than turtles in natural habitats, but there was no significant association of home range size with the amount of time observed within the solar farm. Finally, we discuss strategies to mitigate negative impacts of solar farm development on turtles.

Radio telemetry↗
DOE OSTI2013

The Effect of Grit on Frictional Heating During Oblique Impacts with PBX 9501

Technicians working at the Pantex Plant routinely perform assembly/disassembly operations on weapons containing plastic-bonded explosives (PBXs). With high explosives (HE) operations comes the potential for high consequence accidents. As a result, a process for hazard analysis has been developed within the DOE-NNSA complex to identify and prevent HE-related accidents. Part of this process is to perform research to support or reject the safety basis upon which plant operations are authorized. Understanding the physics of HE response to a variety of mechanical and thermal insults is valuable to this process to: 1) assess risk probability to rank scenarios for the purpose of focusing resources to maximize benefit; 2) define screening thresholds to minimize risk for when an accident does occur; and 3) to develop engineered controls and administrative strategies to mitigate consequences when an accident occurs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Detecting Humanity's Imprint on Rainfall Patterns: An S&TR Preprint

It's the perfect storm. At a time when global demand for water is rising rapidly due to population growth, urbanization, industrial activities, and expanded use of crop irrigation systems, climate change may be altering the timing, location, and amount of rain and snow that fall on large swaths of the planet. Computational models indicate that increases in global surface temperatures will redistribute rainfall in two ways. First, warmer air, which holds more water vapor, will intensify existing precipitation and drought conditions. That is, more rain will fall in wet areas, and evaporation will increase in drier areas. Second, shifts in atmospheric circulation patterns will push storm paths and subtropical dry zones toward the poles. Worldwide changes to rainfall patterns could magnify existing problems with water scarcity, food shortage, and possibly even political instabilities, thereby transforming an environmental concern into a global security issue. Confirming that the predicted changes are occurring and determining whether human-induced (anthropogenic) forces, such as greenhouse-gas emissions and ozone depletion, or naturally occurring fluctuations are causing the pattern shifts may help policy makers develop strategies for mitigating or adapting to the changes. However, extracting this information from global precipitation data can be challenging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗