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DOE OSTI2023

Stopping to reflect: Asymptotic static moving mirrors as quantum analogs of classical radiation

Radiation from an accelerating charge is a basic process that can serve as an intersection between classical and quantum physics. We present two exactly soluble electron trajectories that permit analysis of the radiation emitted, exploring its time evolution and spectrum by analogy with the moving mirror model of the dynamic Casimir effect. These classical solutions are finite energy, rectilinear (nonperiodic), asymptotically zero velocity worldlines with corresponding quantum analog beta Bogolyubov coefficients. One of them has an interesting connection to uniform acceleration and Leonardo da Vinci's water pitcher experiment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Resilience Analysis of DC Microgrids under Denial of Service Threats

This paper develops a resilience analysis framework to study the fault ride-through capability of direct current (DC) microgrids in unknown denial of service (DoS) cyber incidents. DoS can be a frequent threat to DC microgrids with advanced controllers that hinge on active information exchanges: it can paralyze data communications and cause control ineptness or even system instability. Furthermore, we show that temporal DoS incidents render the DC microgrid cyber-physical topology and parameters time-varying and cause them to jump between faulty conditions. As existing DC microgrid stability analysis results are primarily developed from time-invariant systems, they might not be valid for the DoS interrupted systems. In this paper, we seek to study whether a DC microgrid is resilient against time-varying unknown DoS incidents. The problem is formulated as a stability analysis problem for a system with randomly switching dynamics. Scalable conditions are developed to provide provable resilience guarantees. In addition, we exploit the special structure of the conditions to yield quantified resilience measure by convex optimization techniques. As a result, the measure can be used for the evaluation of the resilience of different DC microgrid design against DoS incidents. We demonstrate the effectiveness of the proposed work using simulation case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Flame Edge Dynamics and Interaction in a Multi-Nozzle Can Combustor with Fuel Staging

The characterization and mitigation of thermoacoustic combustion instabilities in gas turbine engines is necessary to reduce pollutant emissions, premature wear, and component failure associated with unstable flames. Fuel staging, a technique in which the fuel flow to a multi-nozzle combustor is unevenly distributed between the nozzles, has been shown to mitigate the intensity of self-excited combustion instabilities in multiple nozzle combustors. In our previous work, we hypothesized that staging suppresses instability through a phase-cancellation effect in which the heat release rate from the staged nozzle oscillates out of phase with that of the other nozzles, leading to destructive interference that suppresses the instability. This previous theory, however, was based on chemiluminescence imaging, which is a line-of-sight integrated technique. In this work, we use high-speed laser-induced fluorescence to further investigate instability suppression in two staging configurations: center-nozzle and outer-nozzle staging. An edge-tracking algorithm is used to compute local flame edge displacement as a function of time, allowing instability-driven edge oscillation phase coherence and other instantaneous flame dynamics to be spectrally and spatially resolved. Analysis of flame edge oscillations shows the presence of convecting coherent fluctuations of the flame edge caused by periodic vortex shedding. When the system is unstable, these two flame edges oscillate together as a result of high-intensity longitudinal-mode acoustic oscillations in the combustor that drive periodic vortex shedding at each of the nozzle exits. In the stable cases, however, the phase between the oscillations of the center and outer flame edges is greater than 90 degrees (~114 degrees), suggesting that the phase-cancellation hypothesis may be valid. This analysis allows a better understanding of the instantaneous flame dynamics behind flame edge oscillation phase offset and fuel staging-based instability suppression.

Doleiden, Daniel↗

DOE OSTI2020

Cloud Atlas: Unraveling the Vertical Cloud Structure with the Time-series Spectrophotometry of an Unusually Red Brown Dwarf

Rotational modulations of emission spectra in brown dwarf and exoplanet atmospheres show that clouds are often distributed non-uniformly in these ultracool atmospheres. The spatial heterogeneity in cloud distribution demonstrates the impact of atmospheric dynamics on cloud formation and evolution. In this study, we update the Hubble Space Telescope (HST) time-series data analysis of the previously reported rotational modulations of WISEP J004701+680352—an unusually red late-L brown dwarf with a spectrum similar to that of the directly imaged planet HR 8799e. We construct a self-consistent spatially heterogeneous cloud model to explain the HST and the Spitzer time-series observations, as well as the time-averaged spectra of WISE 0047. Additionally, in the heterogeneous cloud model, a cloud thickness variation of around one pressure scale height explains the wavelength dependence in the HST near-IR spectral variability. By including disequilibrium CO/CH 4 chemistry, our models also reproduce the redder $J-{K}_{{\rm{s}}}$ color of WISE 0047 compared to that of field brown dwarfs. We discuss the impact of vertical cloud structure on atmospheric profile and estimate the minimum eddy diffusivity coefficient for other objects with redder colors. Our data analysis and forward modeling results demonstrate that time-series spectrophotometry with a broad wavelength coverage is a powerful tool for constraining heterogeneous atmospheric structure.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Orientational Pair Correlations and Local Structure of Benzonitrile from Molecular Dynamics Simulations with Comparisons to Experiments [plus supplemental information]

Here, we present an experimentally parametrized molecular dynamics study of single-molecule and collective orientational relaxation in neat benzonitrile through the analysis of the reorientational anisotropy and polarizability anisotropy time-correlation function (PA-TCF). The simulations show that the PA-TCF is dominated by collective reorientation after 20 ps. Collective reorientation is found to be slower than single-molecule reorientation by a factor of 1.67, consistent with recent experiments. The simulations provide direct evidence of local antiparallel benzonitrile configurations. These structures, which have been the center of some debate, are responsible for the slower rate of collective vs. single-molecule reorientation in the liquid. Further structural analysis indicates that significant Coulombic interactions between the nitrile group and hydrogen atoms on adjacent molecules play a role in the formation of the antiparallel structures. The single-molecule dynamics reflected in the anisotropy are complex and consist of a ballistic regime, restricted angular diffusion, and spatially anisotropic free diffusion. The principal components of the rotational diffusion tensor are independently obtained and shown to reproduce the free diffusion regime of the anisotropy for each principal axis according to the predictions of a previous theory.

14 SOLAR ENERGY↗

DOE OSTI2017

Quantitative proteome analysis of bovine mammary gland reveals protein dynamic changes involved in peak and late lactation stages

Highlights: • Revealed dynamic protein changes between two lactation stages in bovine mammary by TMT-based proteomics (first time). • Longitudinal design avoided the influence of different genetic backgrounds on the DEP detection. • 179 differentially expressed proteins (DEPs) identified. • Identified novel DEPs: AACS, DHCR7, GSTM3, SFRP1 and SFRP4. • Major pathways: PI3K-Akt, localization, lipid metabolic, amino acid transport immune system and apoptotic signaling. Mammary gland is an important organ for milk synthesis and secretion. It undergoes dramatic physiological changes to adapt the shift from peak to late lactation stage. Protein plays a final very vital role in many life functions, and the protein changes during different lactation stages potentially reflect the biology of lactation and the functions of mammary gland in cows. In current study, we adopted tandem mass tags label-based quantitative analysis technique and to investigate proteome changes occurring in bovine mammary gland from peak to late lactation stages. A total of 3753 proteins from mammary tissues taken at two lactation points from four individual cows by biopsy were quantified, out of which 179 proteins were expressed differentially between two stages. We observed five new DEPs (AACS, DHCR7, GSTM3, SFRP1 and SFRP4) and nine functional well-studies known proteins (PLIN2, LPIN1, PLIN3, GSN, CD74, MMP2, SOD1, SOD3 and GPX3) related to milk performance and mammary morphology. Bioinformatics analyses of the DEPs showed a majority of the up-regulated proteins during late lactation stage were related to apoptosis and immune process, while the downregulated proteins were mainly involved in localization, lipid metabolic and transport process. This suggests that the mammary gland can adapt to different molecular functions according to the biological need of the animal. From the integrated analysis of the differentially expressed proteins with known quantitative trait loci and genome-wide association study data, we identified 95 proteins may potentially affect milking performance. We expect findings in this study could be a valuable resource for future studies investigating the bovine proteome and functional studies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Visualizing degradation mechanisms in a gas-fed CO 2 reduction cell via operando X-ray tomography

We utilize operando X-ray computed tomography, coupled with real-time electrochemical analysis, to reveal the underlying failure mechanisms of membrane electrode assemblies (MEAs) for electrochemical CO 2 reduction (eCO 2 R). Through operando imaging, we can obtain unprecedented insights into the dynamic behavior of the MEA under different operating conditions, revealing critical changes in interface interactions, phase distribution, and structural integrity over time. Our findings identify phenomena giving rise to the transition from CO 2 R to the hydrogen evolution reaction (HER), as evidenced by shifts in cathode potential and CO 2 R selectivity. The formation of inhomogeneous precipitates at the gas diffusion electrode disrupts the CO 2 supply and reduces the active sites for eCO 2 R, resulting in a shift toward H2 production during low current density operation. Additionally, under high current density conditions, rapid water crossover up to the microporous layer/gas diffusion layer promotes the transition from CO 2 R to HER, further shifting cell potential toward anodic direction. Oscillating voltage conditions reveal the dissolution and regrowth of precipitates, providing direct visualization of the competing selectivity of CO 2 R and HER. This work offers new insight into the degradation mechanisms of MEAs, with implications for the design of more durable CO 2 R systems.

Lee, Sol A [California Institute of Technology (Ca↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

Optimal Execution of Co-analysis for Large-scale Molecular Dynamics Simulations

The analysis of scientific simulation data enables scientists to derive insights from their simulations. This analysis of the simulation output can be performed at the same execution site as the simulation using the same resources or can be done at a different site. The optimal output frequency is challenging to decide and is often chosen empirically. We propose a mathematical formulation for choosing the optimal frequency of data transfer for analysis and the feasibility of performing the analysis, under the given resource constraints such as network bandwidth, disk space, available memory, and computation time. We propose formulations for two cases of co-analysis -- local and remote. We consider various analyses features such as computation time, input data and memory requirement, importance of the analysis and minimum frequency required for performing the analysis. We demonstrate the effectiveness of our approach using molecular dynamics applications on the Mira and Edison supercomputers.

analysis↗

DOE OSTI2021

Atomic understanding of structural deformations upon ablation of graphene

We investigate the atomic rearrangement in graphene under femtosecond pulse illumination with reactive molecular dynamics simulations and compare with ultra-fast laser ablation experiments. To model the impact of the laser pulse irradiation, heat is locally applied to a selected area of the graphene layer and the resulting structural deformation is simulated as a function of time, providing a detailed understanding of the bond breaking process under laser illumination and subsequent re-equilibration afterAQ3 the pulse is turned off. Analysis of the atomic dynamics indicates that the types of defects formed depend on the pulse energy and exposure duration. By varying the exposed area, we determine that the shape of the ablated area is not only a function of the pulse energy, but also of the beam spot size and pulse repetition. Furthermore, we apply a machine learning approach to extrapolate our simulated data to experimental length scales and reproduce the trends in ablated area as a function of temperature. Furthermore, our study provides a first step towards understanding the design parameters for graphene nano-patterning.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Harnessing stratospheric diffusion barriers for enhanced climate geoengineering

Stratospheric sulfate aerosol geoengineering is a proposed method to temporarily intervene in the climate system to increase the reflectance of shortwave radiation and reduce mean global temperature. In previous climate modeling studies, choosing injection locations for geoengineering aerosols has, thus far, only utilized the average dynamics of stratospheric wind fields instead of accounting for the essential role of time-varying material transport barriers in turbulent atmospheric flows. Here we conduct the first analysis of sulfate aerosol dispersion in the stratosphere, comparing what is now a standard fixed-injection scheme with time-varying injection locations that harness short-term stratospheric diffusion barriers. We show how diffusive transport barriers can quickly be identified, and we provide an automated injection location selection algorithm using short forecast and reanalysis data. Within the first 7 d days of transport, the dynamics-based approach is able to produce particle distributions with greater global coverage than fixed-site methods with fewer injections. Additionally, this enhanced dispersion slows aerosol microphysical growth and can reduce the effective radii of aerosols up to 200–300 d after injection. While the long-term dynamics of aerosol dispersion are accurately predicted with transport barriers calculated from short forecasts, the long-term influence on radiative forcing is more difficult to predict and warrants deeper investigation. Statistically significant changes in radiative forcing at timescales beyond the forecasting window showed mixed results, potentially increasing or decreasing forcing after 1 year when compared to fixed injections. We conclude that future feasibility studies of geoengineering should consider the cooling benefits possible by strategically injecting sulfate aerosols at optimized time-varying locations. Our method of utilizing time-varying attracting and repelling structures shows great promise for identifying optimal dispersion locations, and radiative forcing impacts can be improved by considering additional meteorological variables.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

ESTABLISHING ROCK OUTCROP TIME SERIES AT VARIOUS DEPTHS IN A NONLINEAR SOIL COLUMN

Nonlinear soil-structure interaction (NLSSI) analysis methods are currently being developed at Idaho National Laboratory (INL). Appendix B in ASCE 4 (2016) includes a framework for performing NLSSI analysis. For NLSSI analysis to be widely implemented in industry, it is important to demonstrate that accurate response in a dynamically loaded, nonlinear soil column can be produced. In performing NLSSI analysis, one approach is to consider vertically propagating shear and compressive waves that pass through a nonlinear soil column and into a structure. Using finite element techniques, the structure can be placed in a finite volume of nonlinear soil with a rock outcrop seismic time series applied to the bottom of the nonlinear soil. The necessary depth of the nonlinear soil mesh is dependent on the vertical soil stiffness when the model is in static and dynamic equilibrium. Run time, and therefore size of the meshed soil domain, is an important consideration when developing the NLSSI model. An approach is presented in this paper that establishes compatible rock outcrop seismic time series for reduced nonlinear soil mesh depths. To apply the approach, an example is developed using a reasonable soil column with a reasonable top-of-soil response spectrum. The approach is an iterative method which is applied in two steps. The first step is used to establish a reasonable rock outcrop time series at the highest depth considered. The second step is used to establish compatible rock outcrop time series at shallower depths.

42 ENGINEERING↗

DOE OSTI2016

Investigation of phonon transport and thermal boundary conductance at the interface of functionalized SWCNT and poly (ether-ketone)

Carbon nanostructures such as carbon nanotube (CNT), graphene, and carbon fibers can be used as fillers in amorphous polymers to improve their thermal properties. In this study, the effect of covalent bonding of CNT with poly(ether ketone) (PEK) on interfacial thermal interactions is investigated using non-equilibrium molecular dynamics simulations. The number of covalent bonds between (20, 20) CNT and PEK is varied in the range of 0–80 (0%–6.25%), and the thermal boundary conductance is computed. The analysis reveals that covalent functionalization of CNT atoms can enhance the thermal boundary conductance by an order of magnitude compared to the non-functionalized CNT-PEK interface at a high degree of CNT functionalization. Besides strengthening the thermal coupling, covalent functionalization is also shown to modify the phonon spectra of CNT. The transient spectral energy analysis shows that the crosslinks cause faster energy exchange from CNT to PEK in different frequency bands. The oxygen atom of hydroxyl group of PEK contributes energy transfer in the low frequency band, while aromatic and carbonyl carbon atoms play a more significant role in high frequency bands. In addition, by analyzing the relaxation time of the spectral temperature of different frequency bands of CNT, it is revealed that with increasing number of bonds, both lower frequency vibrational modes and higher frequency modes efficiently couple across the CNT-PEK interface and contribute in thermal energy transfer from CNT to the matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

On the measurement of shape: With applications to lunar regolith

With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.

2D shape↗

DOE OSTI2023

Electrochemical Response of Alkaline Batteries Subject to Quasi-Static and Dynamic Loading

We report electrochemical changes were successfully monitored through the coupling of external loading, electrochemical impedance spectroscopy (EIS), and distribution of relaxation times (DRT) analysis. The development of the testing methods allows for detailed observation of changes due to mechanical loading and distinguishes responses between different cell geometries. Comparison of the force vs displacement, voltage vs displacement, and distribution of relaxation times plots to the different cell geometries display failure modes specific to geometry as well as the impact of different loading profiles. Numerical modeling confirmed the movement within individual cells and predicted locations with the most deformation based on the external loading condition applied. The results gathered from combining mechanical loading, electrochemical response, and numerical modeling, yield a viable approach to establishing an improved understanding of the effects of mechanical loading on the electrochemical response of multiple battery geometries and the methods herein may be extensible to additional battery chemistries.

25 ENERGY STORAGE↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Volumetric Rendering on Wavelet-Based Adaptive Grid

Numerical modeling of physical phenomena frequently involves processes across a wide range of spatial and temporal scales. In the last two decades, the advancements in wavelet-based numerical methodologies to solve partial differential equations, combined with the unique properties of wavelet analysis to resolve localized structures of the solution on dynamically adaptive computational meshes, make it feasible to perform large-scale numerical simulations of a variety of physical systems on a dynamically adaptive computational mesh that changes both in space and time. Volumetric visualization of the solution is an essential part of scientific computing, yet the existing volumetric visualization techniques do not take full advantage of multi-resolution wavelet analysis and are not fully tailored for visualization of a compressed solution on the wavelet-based adaptive computational mesh. Our objective is to explore the alternatives for the visualization of time-dependent data on space-time varying adaptive mesh using volume rendering while capitalizing on the available sparse data representation. Two alternative formulations are explored. The first one is based on volumetric ray casting of multi-scale datasets in wavelet space. Rather than working with the wavelets at the finest possible resolution, a partial inverse wavelet transform is performed as a preprocessing step to obtain scaling functions on a uniform grid at a user-prescribed resolution. As a result, a solution in physical space is represented by a superposition of scaling functions on a coarse regular grid and wavelets on an adaptive mesh. An efficient and accurate ray casting algorithm is based just on these coarse scaling functions. Additional details are added during the ray tracing by taking an appropriate number of wavelets into account based on support overlap with the interpolation point, wavelet coefficient magnitude, and other characteristics, such as opacity accumulation (front to back ordering) and deviation from frontal viewing direction. The second approach is based on complementing of wavelet-based adaptive mesh to the traditional Adaptive Mesh Refinement (AMR) mesh. Both algorithms are illustrated and compared to the existing volume visualization software for Rayleigh-Benard thermal convection and electron density data sets in terms of rendering time and visual quality for different data compression of both wavelet-based and AMR adaptive meshes.

Vezolainen, Alexei V.↗