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DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learning methods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with unform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10Gbps connections with 0-366ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss rates but become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Generalization Bounds↗

DOE OSTI2025

Tomographic Sparse View Selection Using the View Covariance Loss

Standard computed tomography (CT) reconstruction algorithms such as filtered back projection (FBP) and Feldkamp-Davis-Kress (FDK) require many views for producing high-quality reconstructions, which can slow image acquisition and increase cost in non-destructive evaluation (NDE) applications. Over the past 20 years, a variety of methods have been developed for computing high-quality CT reconstructions from sparse views. However, the problem of how to select the best views for CT reconstruction remains open. In this paper, we present a novel view covariance loss (VCL) function that measures the joint information of a set of views by approximating the normalized mean squared error (NMSE) of the reconstruction. We present fast algorithms for computing the VCL along with an algorithm for selecting a subset of views that approximately minimizes its value. Our experiments on simulated and measured data indicate that for a fixed number of views our proposed view covariance loss selection (VCLS) algorithm results in reconstructions with lower NRMSE, fewer artifacts, and greater accuracy than current alternative approaches.

Lin, Jingsong [Purdue University]↗

DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learningmethods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with uniform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10 Gbps connections with 0–366 ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss ratesbut become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Rao, Nageswara S.↗

DOE OSTI2020

Beam impedance and heating analysis of the diagnostic stripline

In this work the heat transfer analysis has been performed for the stripline kicker, design of which is used at many accelerator facilities as a part of the transverse bunch-by-bunch feed-back system, including NSLS-II. The experimental data of the electrode temperature have been collected from a special diagnostic stripline designed with six infrared view ports. The temperature analysis is based on the power loss calculations and the loss factor computed by the 3-D electromagnetic simulation code GdfidL. To estimate the power loss, we analyze the real part of the longitudinal impedance and the loss factor for two different regimes. We use the ANSYS finite element code to correlate the temperature with the power loss. Lambertson and Shafer formalisms of the longitudinal and transverse beam impedances are discussed for the simplified stripline geometries. The required characteristic impedances and the geometric factors are determined analytically for the simplified geometries and compared with the results for the designed stripline geometry using the 2-D POISSON code by solving the Laplace’s equation in two dimensions. Lambertson’s equations are compared with numerical results. We introduce the frequency range, within which we can apply the analytical approach.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Fingerprinting Uranium Oxides with Electron Energy Loss Spectroscopy Supported by Theoretical Computations

Uranium oxides occur in a variety of phases that differ in crystal structure and uranium oxidation states. Electron energy loss spectroscopy (EELS) is one of the few techniques that has sufficient spatial resolution and sensitivity to electronic structure to distinguish amongst phases at the nanoscale. However, beam-sensitive materials such as uranium oxides are subject to spectral modification due to interactions with the electron beam. Therefore, theory support is essential to reliably exclude the impact of beam damage and generate true reference datasets. Here we use a comparison of theoretical and experimental spectra to probe the impact of beam damage on O K-edge and U N-edge (N6,7 and N4,5) EELS spectra of various single-valent and mixed-valence uranium oxide bulk phases. Using a low-dose experimental set-up, we show that the O K-edge theoretical spectra are in excellent agreement with experiment for both peak positions and relative intensities of respective peaks. In contrast, U N-edge features are less distinguishing due to the partially localized nature of the U 5f orbitals and overlapping multiplet and spin–orbit coupling effects. This work demonstrates that O K-edge EELS is sufficiently diagnostic to distinguish a wide range of uranium oxides and that the experimental approach used here minimizes beam damage and allows valence state discrimination across the U(IV), U(V) and U(VI) series. When combined with imaging modes available in electron mi-croscopy, the work enables detailed investigation and characterization of uranium redox transformations at the nanoscale.

Carbone, Jacopo↗

DOE OSTI2018

Extending continuum models for atom probe simulation

Highlights: • Demonstration of 3D curvature level set methods for APT simulations • Demonstration of non-rotationally symmetric tip shape simulations • Optimised speed for simulations, calculations achievable on minute timescales This work describes extensions to existing level-set algorithms developed for application within the field of atom probe tomography (APT). We present a new simulation tool for the simulation of 3D tomographic volumes, using advanced level set methods. By combining narrow-band, B-Tree and particle-tracing approaches from level-set methods, we demonstrate a practical tool for simulating shape changes to APT samples under applied electrostatic fields, in three dimensions. This work builds upon our previous studies by allowing for non-axially symmetric solutions, with minimal loss in computational speed, whilst retaining numerical accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Energy loss of a heavy fermion in a collisional QED plasma

We compute the energy loss of heavy fermions moving in a plasma, taking into account the modification of the photon collective modes induced by collisions using a Bhatnagar-Gross–Krook collisional kernel. We include contributions from both hard and soft scatterings of the heavy fermion using a collisionally modified hard-thermal-loop resummed propagator. Using this method, one does not need to introduce a separation scale between hard- and soft-momentum exchanges. To place our calculation in context, we review other theoretical approaches to computing the collisional energy loss of fermions and discuss the systematics and results obtained in each approach compared to using a resummed propagator for both hard and soft momentum exchanges. Our final results indicate that self-consistently including the effect of collisions in the self-energies of the resummed propagator results in an increased energy loss compared to using collisionless hard-thermal-loop propagators. The effect becomes larger as the magnitude of the coupling constant and the velocity of the fermion increase. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

DOE OSTI2024

tLaSDI: Thermodynamics-informed latent space dynamics identification

Here we propose a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Thermodynamics-informed latent space dynamics identification

This software showcases a latent space dynamics identification method, namely tLaSDI, that embeds the first and second principles of thermodynamics. The latent variables are learned through an autoencoder as a nonlinear dimension reduction model. The latent dynamics are constructed by a neural network-based model that precisely preserves certain structures for the thermodynamic laws through the GENERIC formalism. An abstract error estimate is established, which provides a new loss formulation involving the Jacobian computation of autoencoder. The autoencoder and the latent dynamics are simultaneously trained to minimize the new loss. Computational examples demonstrate the effectiveness of tLaSDI, which exhibits robust generalization ability, even in extrapolation. In addition, an intriguing correlation is empirically observed between a quantity from tLaSDI in the latent space and the behaviors of the full-state solution.

Cheung, Siu Wun↗

DOE OSTI2024

Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge

CMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. We developed a filament-free, bulk switching RRAM technology to address these challenges. We systematically engineered a trilayer metal-oxide stack and investigated the switching characteristics of RRAM with varying thicknesses and oxygen vacancy distributions to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching at megaohm regime with high current nonlinearity, up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform and showcased edge computing by implementing a spiking neural network for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Toroidal modeling of runaway electron loss due to 3-D fields in DIII-D and COMPASS

The 3-D field induced relativistic runaway electron (RE) loss has been simulated for DIII-D, COMPASS and ITER plasmas, utilizing the MARS-F code incorporated with the recently developed and updated RE orbit module (REORBIT). Modeling shows effectively 100% loss of a post-disruption, high-current runaway beam in DIII-D, due to the 1 kG level of magnetic field perturbation produced by a fast growing n = 1 resistive kink instability. The RE loss is shown to be independent of the particle energy or the initial location of particles in the configuration space. Applied resonant magnetic perturbation (RMP) fields from in-vessel coils are not effective for RE beam mitigation in DIII-D, but do produce finite (>10%) RE loss in COMPASS, consistent with experimental observations in above two devices. The major reasons for this difference in RE control by RMP between these two devices are (i) the coil proximity to the RE beam and (ii) the effective coil current scaling versus the machine size and the toroidal magnetic field. About 10% RE loss fraction is also predicted for an ITER 15 MA scenario with pre-disruption plasma, highlighting the role of the plasma response. Up to 30% loss is computed, however, by artificially scaling the equilibrium pressure to zero. This is due to the more resistive plasma response and stronger resulting field line stochasticity. Distributions of the lost REs to the limiting surface show poloidally peaked profile near the high-field-side in both DIII-D and COMPASS, covering about 100o poloidal angle. Higher perturbation field level and/or higher particle energy also result in REs being lost to the low-field-side of the limiting surface of these two devices, increasing the effective wetted area. Finally, for the modeled ITER plasmas, the applied RMP field, with optimal poloidal spectrum that maximizes the edge localized mode control, leads to REs being lost to the lower divertor region of the limiting surface within a narrow poloidal band.

3-D field↗

DOE OSTI2024

Reductive Elimination From Tetra‐Alkyl Cuprates [Me n Cu(CF 3 ) 4− n ] − ( n =0–4): Beyond Simple Oxidation States

Abstract In recent years, the electronic structures of organocuprates in general and the complex [Cu(CF 3 ) 4 ] − in particular have attracted significant interest. A possible key indicator in this context is the reactivity of these species. Nonetheless, this aspect has received only limited attention. Here, we systematically study the series of tetra‐alkyl cuprates [Me n Cu(CF 3 ) 4− n ] − and their unimolecular reactivity in the gas phase, which includes concerted formal reductive eliminations as well as radical losses. Through computational studies, we characterize the electronic structures of the complexes and show how these are connected to their reactivity. We find that all [Me n Cu(CF 3 ) 4− n ] − ions feature inverted ligand fields and that the distinct reactivity patterns of the individual complexes arise from the interplay of different effects.

Zimmer, Bastian↗

DOE OSTI2020

Computational analysis of ion orbital loss in diverted positive- and negative-triangularity tokamaks

The mechanism of ion orbital loss in diverted negative-triangularity (NT) tokamaks is significantly different from that of positive-triangularity (PT) tokamaks. The orbital loss from the edge of NT tokamaks can be quite large, because the separatrix X-point is located on the outboard side, meaning that trapped ions crossing the separatrix are lost to the inboard divertor plate after a mirror reflection on the side of the strong magnetic field. NT tokamaks have difficulties in building up steep pressure gradients in the edge regions. However, the majority of trapped ions crossing the separatrix in PT tokamaks survive (through complete banana motions) without reaching the X-point region. For NT tokamaks, topological changes in the trapped ion trajectories can be achieved in the presence of the radial electric field, thus reducing the orbital loss, whereas for PT tokamaks, the orbital loss is relatively insensitive to the radial electric field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Radiation-damage investigation of a DNA 16-mer

In macromolecular crystallography, a great deal of effort has been invested in understanding radiation-damage progression. While the sensitivity of protein crystals has been well characterized, crystals of DNA and of DNA–protein complexes have not thus far been studied as thoroughly. Here, a systematic investigation of radiation damage to a crystal of a DNA 16-mer diffracting to 1.8 Å resolution and held at 100 K, up to an absorbed dose of 45 MGy, is reported. The RIDL ( Radiation-Induced Density Loss ) automated computational tool was used for electron-density analysis. Both the global and specific damage to the DNA crystal as a function of dose were monitored, following careful calibration of the X-ray flux and beam profile. The DNA crystal was found to be fairly radiation insensitive to both global and specific damage, with half of the initial diffraction intensity being lost at an absorbed average diffraction-weighted dose, D 1/2 , of 19 MGy, compared with 9 MGy for chicken egg-white lysozyme crystals under the same beam conditions but at the higher resolution of 1.4 Å. The coefficient of sensitivity of the DNA crystal was 0.014 Å 2 MGy -1 , which is similar to that observed for proteins. These results imply that the significantly greater radiation hardness of DNA and RNA compared with protein observed in a DNA–protein complex and an RNA–protein complex could be due to scavenging action by the protein, thereby protecting the DNA and RNA in these studies. In terms of specific damage, the regions of DNA that were found to be sensitive were those associated with some of the bound calcium ions sequestered from the crystallization buffer. In contrast, moieties farther from these sites showed only small changes even at higher doses.

Instruments & Instrumentation↗

DOE OSTI2019

Photovoltaic Inverter Reliability Assessment

As the price of PV modules drops, the price of power electronics become more important. Power electronics now constitute 8%-12% of the total lifetime PV cost. As of 2010, the inverter and associated power conditioning components accounted for $\$0.25$/W, well above the DOE benchmark of $\$0.12$/W by 2020. As efforts to reduce PV module costs yield diminishing returns, the importance of understanding and reducing inverter costs becomes an increasingly critical and cost-effective investment toward achieving the DOE SunShot goals. With this in view, this report showcases and describes an approach to help assess and predict the reliability of photovoltaic (PV) inverters. To predict the reliability, thermal cycling is considered as a prominent stressor in the inverter system. To evaluate the impacts of thermal cycling, a detailed linearized model of the PV inverter is developed along with controllers. This research also develops models and methods to compute the losses of the power electronics switches and other components in a PV inverter. The losses are then used to estimate the junction and heat sink temperature. The model is verified by developing an in-house inverter. Additionally, to assess the scalability of the research, the hardware inverter is placed inside a thermal chamber to verify the losses for different ambient temperatures. After the verification of the model, a reduced-order model of the inverter is implemented to translate the profile of ambient temperature and solar irradiance into the profile of junction temperatures of the switches. The estimated junction temperature data are used to identify inverter reliability indices and predict the useful lifetime of the inverter system. After developing the models to predict the useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The first chapter involves the motivation behind the research on assessing the reliability of PV inverters. The inverter power stage and controller design of the power converter used in this research is also explained in detail in this chapter. The second chapter presents the various losses of the power converter system and the translation of power loss into temperature increase with thermal modeling. The results of the loss modeling and the thermal modeling are also explained in detail in this chapter. The third chapter involves implementing the reduced-order model to translate the mission profile of ambient temperature and solar irradiance into profile of the junction temperatures of the switches. The final chapter involves identifying reliability indices, which are of interest for this system to predict the remaining useful life of the system, and concludes with the impact of reactive power on the overall reliability of the inverter system.

14 SOLAR ENERGY↗

DOE OSTI2021

Transport of Protostellar Cosmic Rays in Turbulent Dense Cores

We report recent studies have suggested that low-energy cosmic rays (CRs) may be accelerated inside molecular clouds by the shocks associated with star formation. We use a Monte Carlo transport code to model the propagation of CRs accelerated by protostellar accretion shocks through protostellar cores. We calculate the CR attenuation and energy losses and compute the resulting flux and ionization rate as a function of both radial distance from the protostar and angular position. We show that protostellar cores have nonuniform CR fluxes that produce a broad range of CR ionization rates, with the maximum value being up to two orders of magnitude higher than the radial average at a given distance. In particular, the CR flux is focused in the direction of the outflow cavity, creating a "flashlight" effect and allowing CRs to leak out of the core. The radially averaged ionization rates are less than the measured value for the Milky Way of ζ ≈ 10 -16 s -1 ; however, within r ≈ 0.03 pc from the protostar, the maximum ionization rates exceed this value. We show that variation in the protostellar parameters, particularly in the accretion rate, may produce ionization rates that are a couple of orders of magnitude higher or lower than our fiducial values. Finally, we use a statistical method to model unresolved subgrid magnetic turbulence in the core. We show that turbulence modifies the CR spectrum and increases the uniformity of the CR distribution but does not significantly affect the resulting ionization rates.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Comparison of AC Losses of YBCO Circular Pancake Coils and Infinitely Long Stack Approximation

High-temperature superconducting (HTS) coils are key parts of many large-scale AC applications, such as transformers, superconducting magnetic energy storage, and motors. The estimation of AC losses of pancake coils is necessary for optimizing the design of HTS devices and cryogenic systems. To speed up the computation of AC losses, the numerical model of an infinitely long HTS stack is often utilized. An HTS stack is a good approximation of the circular coil only if the coil radius is sufficiently large, since AC losses will exhibit a stronger asymmetry along the radial direction for small values of coil radii. To assess the validation of an infinitely long stack approximation, the comparisons of AC losses between infinitely long stacks and circular coils with different radii are presented. The turn number varies from 10 to 80. We find that the AC losses of HTS circular coils will gradually increase to the same value as an infinitely long stack with increasing coil radii. A new parameter is proposed to quantitatively describe the correctness of infinitely long stack approximation. Finally, a method of AC loss estimation of HTS pancake coils is proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗