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DOE OSTI2023

Computational framework for modeling of physical process

Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N. The method includes generating a set of approximated system variables corresponding to the set of measurements based on the numerical model.

Chen, Xiao↗

DOE OSTI2024

Computational framework for modeling of physical process

Chen, Xiao↗

DOE OSTI2024

Geometry-aware training of factorized layers in tensor Tucker format

Reducing parameter redundancies in neural network architectures is crucial for achieving feasible computational and memory requirements during train and inference of large networks. Given its easy implementation and flexibility, one promising approach is layer factorization, which reshapes weight tensors into a matrix format and parameterizes it as the product of two rank-r matrices. However, this family of approaches often requires an initial full-model warm-up phase, prior knowledge of a feasible rank, and it is sensitive to parameter initialization.In this work, we introduce a novel approach to train the factors of a Tucker decomposition of the weight tensors. Our training proposal proves to be optimal in locally approximating the original unfactorized dynamics and stable for the initialization. Furthermore, the rank of each mode is dynamically updated during training.We provide a theoretical analysis of the algorithm, showing convergence, approximation and local descent guarantees. The method's performance is further illustrated through a variety of experiments, showing remarkable training compression rates and comparable or even better performance than the full baseline and alternative layer factorization strategies.

Zangrando, Emanuele [Gran Sasso Science Institute ↗

DOE OSTI2024

Simple and Robust Carrier-Based PWM Technique for Single-Stage Three-phase Rectifier Indirect Matrix Converter

Indirect matrix converters (IMC) can offer high efficiency, high power density, and bidirectional power flow capability with a single-stage three-to single-phase AC-AC power conversion integrating a conventional three-phase active rectifier with a primary side full-bridge inverter of a dual active bridge converter. However, the IMCs generally require space vector modulation techniques, leading to complex sectors and dwell times calculations. A practical implementation of the modulation methods with a commonly used digital signal processor becomes even more challenging when considering power factor correction, harmonics reduction, and deadtime between sector transitions. This paper proposes a simple and robust carrier-based pulse width modulation (PWM) technique determined through a voltage-source inverter (VSI) to current-source inverter (CSI) to IMC conversion. This translation enables the adoption of all conventional VSI control methods with active and reactive power control in the IMCs through simple carrier and reference waveform comparison. The VSI vectors are first one-on-one matched with CSI vectors and translated to IMC modulation signals without calculating sectors and dwell times. Nine different carrier waveforms are proposed, and the converter performance is analyzed. Grid current THD and efficiency are estimated for each modulation method. The symmetric A and B methods had the lowest THD of the grid current, 2.80%, and the efficiency remained at approximately 98.3%, making it the most suitable carrier-based method proposed in this paper. The space vector PWM (SVPWM) modulation method was implemented to the DSP and generated the expected twelve gate signals.

Benson, Mikayla↗

DOE OSTI2016

SU-D-BRB-01: A Comparison of Learning Methods for Knowledge Based Dose Prediction for Coplanar and Non-Coplanar Liver Radiotherapy

Purpose: The predictive power of knowledge based planning (KBP) has considerable potential in the development of automated treatment planning. Here, we examine the predictive capabilities and accuracy of previously reported KBP methods, as well as an artificial neural networks (ANN) method. Furthermore, we compare the predictive accuracy of these methods on coplanar volumetric-modulated arc therapy (VMAT) and non-coplanar 4π radiotherapy. Methods: 30 liver SBRT patients previously treated using coplanar VMAT were selected for this study. The patients were re-planned using 4π radiotherapy, which involves 20 optimally selected non-coplanar IMRT fields. ANNs were used to incorporate enhanced geometric information including liver and PTV size, prescription dose, patient girth, and proximity to beams. The performance of ANN was compared to three methods from statistical voxel dose learning (SVDL), wherein the doses of voxels sharing the same distance to the PTV are approximated by either taking the median of the distribution, non-parametric fitting, or skew-normal fitting. These three methods were shown to be capable of predicting DVH, but only median approximation can predict 3D dose. Prediction methods were tested using leave-one-out cross-validation tests and evaluated using residual sum of squares (RSS) for DVH and 3D dose predictions. Results: DVH prediction using non-parametric fitting had the lowest average RSS with 0.1176(4π) and 0.1633(VMAT), compared to 0.4879(4π) and 1.8744(VMAT) RSS for ANN. 3D dose prediction with median approximation had lower RSS with 12.02(4π) and 29.22(VMAT), compared to 27.95(4π) and 130.9(VMAT) for ANN. Conclusion: Paradoxically, although the ANNs included geometric features in addition to the distances to the PTV, it did not perform better in predicting DVH or 3D dose compared to simpler, faster methods based on the distances alone. The study further confirms that the prediction of 4π non-coplanar plans were more accurate than VMAT. NIH R43CA183390 and R01CA188300.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Gyro-fluid and two-fluid theory and simulations of edge-localized-modes

This paper reports on the theoretical and simulation results of a gyro-Landau-fluid extension of the BOUT++ code, which contributes to increasing the physics understanding of edge-localized-modes (ELMs). Large ELMs with low-to-intermediate-n peeling-ballooning (P-B) modes are significantly suppressed due to finite Larmor radius (FLR) effects when the ion temperature increases. For type-I ELMs, it is found from linear simulations that retaining complete first order FLR corrections as resulting from the incomplete “gyroviscous cancellation” in Braginskii's two-fluid model is necessary to obtain good agreement with gyro-fluid results for high ion temperature cases (T{sub i}≽3 keV) when the ion density has a strong radial variation, which goes beyond the simple local model of ion diamagnetic stabilization of ideal ballooning modes. The maximum growth rate is inversely proportional to T{sub i} because the FLR effect is proportional to T{sub i}. The FLR effect is also proportional to toroidal mode number n, so for high n cases, the P-B mode is stabilized by FLR effects. Nonlinear gyro-fluid simulations show results that are similar to those from the two-fluid model, namely that the P-B modes trigger magnetic reconnection, which drives the collapse of the pedestal pressure. Due to the additional FLR-corrected nonlinear E × B convection of the ion gyro-center density, for a ballooning-dominated equilibrium the gyro-fluid model further limits the radial spreading of ELMs. In six-field two fluid simulations, the parallel thermal diffusivity is found to prevent the ELM encroachment further into core plasmas and therefore leads to steady state L-mode profiles. The simulation results show that most energy is lost via ion channel during an ELM event, followed by particle loss and electron energy loss. Because edge plasmas have significant spatial inhomogeneities and complicated boundary conditions, we have developed a fast non-Fourier method for the computation of Landau-fluid closure terms based on an accurate and tunable approximation. The accuracy and the fast computational scaling of the method have been demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Rapid simulations of hyperspectral near-field images of three-dimensional heterogeneous surfaces – part II

The modeling of the near-field interaction in the scattering-type scanning near-field optical microscope (s-SNOM) is rapidly advancing, although an accurate yet versatile modeling framework that can be easily adapted to various complex situations is still lacking. In this work, we propose a time-efficient numerical scheme in the quasi-electrostatic limit to capture the tip-sample interaction in the near field. This method considers an extended tip geometry, which is a significant advantage compared to the previously reported method based on the point-dipole approximation. Using this formalism, we investigate, among others, nontrivial questions such as uniaxial and biaxial anisotropy in the near-field interaction, the relationship between various experimental parameters (e.g. tip radius, tapping amplitude, etc.), and the tip-dependent spatial resolution. The demonstrated method further sheds light on the understanding of the contrast mechanism in s-SNOM imaging and spectroscopy, while also representing a valuable platform for future quantitative analysis of the experimental observations.

Chen, Xinzhong (ORCID:0000000261033848)↗

DOE OSTI2024

Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems

Herein this paper focuses on developing a reduction-based algebraic multigrid (AMG) method that is suitable for solving general (non)symmetric linear systems and is naturally robust from pure advection to pure diffusion. Initial motivation comes from a new reduction-based AMG approach, $\ell \text{AIR}$ (local approximate ideal restriction), that was developed for solving advection-dominated problems. Though this new solver is very effective in the advection-dominated regime, its performance degrades in cases where diffusion becomes dominant. This is consistent with the fact that in general, reduction-based AMG methods tend to suffer from growth in complexity and/or convergence rates as the problem size is increased, especially for diffusion-dominated problems in two or three dimensions. Motivated by the success of $\ell \text{AIR}$ in the advective regime, our aim in this paper is to generalize the AIR framework with the goal of improving the performance of the solver in diffusion-dominated regimes. To do so, we propose a novel way to combine mode constraints as used commonly in energy-minimization AMG methods with the local approximation of ideal operators used in $\ell \text{AIR}$. The resulting constrained $\ell \text{AIR}$ algorithm is able to achieve fast scalable convergence on advective and diffusive problems. In addition, it is able to achieve standard low complexity hierarchies in the diffusive regime through aggressive coarsening, something that was previously difficult for reduction-based methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Uniform-in-phase-space data selection with iterative normalizing flows

Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Multirate linearly-implicit GARK schemes

Many complex applications require the solution of initial-value problems where some components change fast, while others vary slowly. Multirate schemes apply different step sizes to resolve different components of the system, according to their dynamics, in order to achieve increased computational efficiency. The stiff components of the system, fast or slow, are best discretized with implicit base methods in order to ensure numerical stability. To this end, linearly implicit methods are particularly attractive as they solve only linear systems of equations at each step. This paper develops the Multirate GARK-ROS/ROW (MR-GARK-ROS/ROW) framework for linearly-implicit multirate time integration. The order conditions theory considers both exact and approximative Jacobians. The effectiveness of implicit multirate methods depends on the coupling between the slow and fast computations; an array of efficient coupling strategies and the resulting numerical schemes are analyzed. Multirate infinitesimal step linearly-implicit methods, that allow arbitrarily small micro-steps and offer extreme computational flexibility, are constructed. The new unifying framework includes existing multirate Rosenbrock(-W) methods as particular cases, and opens the possibility to develop new classes of highly effective linearly implicit multirate integrators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

In situ observation on hydrogenation of Mg-Ni films using environmental transmission electron microscope with aberration correction

In situ transmission electron microscopy (TEM) was performed to observe the hydrogenation of Mg-Ni films in a hydrogen atmosphere of 80–100 Pa. An aberration-corrected environmental TEM with a differential pumping system allows us to reveal the Angstrom-scale structure of the films in the initial stage of hydrogenation: first, nucleation and growth of Mg{sub 2}NiH{sub 4} crystals with a lattice spacing of 0.22 nm in an Mg-rich amorphous matrix of the film occurs within 20 s after the start of the high-resolution observation, then crystallization of MgH{sub 2} with a smaller spacing of 0.15 nm happens after approximately 1 min. Our in situ TEM method is also applicable to the analysis of other hydrogen-related materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Semiautomatic segmentation of liver metastases on volumetric CT images

Purpose: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. Methods: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1–10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the “gold standard” for validation of the method’s accuracy. Results: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. Conclusions: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation method.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Explicit Integration of Extremely Stiff Reaction Networks: Partial Equilibrium Methods

In two preceding papers [1,2] we have shown that, when reaction networks are well removed from equilibrium, explicit asymptotic and quasi-steady-state approximations can give algebraically stabilized integration schemes that rival standard implicit methods in accuracy and speed for extremely stiff systems. However, we also showed that these explicit methods remain accurate but are no longer competitive in speed as the network approaches equilibrium. In this paper we analyze this failure and show that it is associated with the presence of fast equilibration timescales that neither asymptotic nor quasi-steady-state approximations are able to remove efficiently from the numerical integration. Based on this understanding, we develop a partial equilibrium method to deal effectively with the new partial equilibrium methods, give an integration scheme that plausibly can deal with the stiffest networks, even in the approach to equilibrium, with accuracy and speed competitive with that of implicit methods. Thus we demonstrate that algebraically stabilized explicit methods may offer alternatives to implicit integration of even extremely stiff systems, and that these methods may permit integration of much larger networks than have been feasible previously in a variety of fields.

Guidry, Mike W↗

DOE OSTI2015

Electronic and optical properties of titanium nitride bulk and surfaces from first principles calculations

Prediction of the frequency-dependent dielectric function of thin films poses computational challenges, and at the same time experimental characterization by spectroscopic ellipsometry remains difficult to interpret because of changes in stoichiometry and surface morphology, temperature, thickness of the film, or substrate. In this work, we report calculations for titanium nitride (TiN), a promising material for plasmonic applications because of less loss and other practical advantages compared to noble metals. We investigated structural, electronic, and optical properties of stoichiometric bulk TiN, as well as of the TiN(100), TiN(110), and TiN(111) outermost surfaces. Density functional theory (DFT) and many-body GW methods (Green's (G) function-based approximation with screened Coulomb interaction (W)) were used, ranging from G{sub 0}W{sub 0}, GW{sub 0} to partially self-consistent sc-GW{sub 0}, as well as the GW-BSE (Bethe-Salpeter equation) and time-dependent DFT (TDDFT) methods for prediction of the optical properties. Structural parameters and the band structure for bulk TiN were shown to be consistent with previous work. Calculated dielectric functions, plasma frequencies, reflectivity, and the electron energy loss spectrum demonstrated consistency with experiment at the GW{sub 0}-BSE level. Deviations from experimental data are expected due to varying experimental conditions. Comparison of our results to spectroscopic ellipsometry data for realistic nanostructures has shown that although TDDFT may provide a computationally feasible level of theory in evaluation of the dielectric function, application is subject to validation with GW-BSE calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Generation and Fragmentation of Phthalide Derivative Negative Ions

Molecules of diphenylphthalide and 3,3-diphenylphthalide-4′,4′-dicarbonic acid have been studied using the method of dissociative electron capture negative ion mass spectrometry. The mean lifetimes of negative molecular ions relative to the electron detachment have been measured. The electron affinity has been estimated in the Arrhenius approximation and calculated by the DFT B3LYP/6-31G+(d) method.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Advanced Methods for Immersed Domain Multi-physics Computations

This is the final report on the project, and describes the main accomplishments in the development of the Shifted Boundary Method (SBM), a new computational framework for embedded/immersed computational mechanics applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Synthetic methods for crystallite size control of bimetallic polyanionic battery compositions

Bimetallic polyanionic materials, such as silver vanadium phosphorus oxide (Ag 2 VO 2 PO 4 , SVOP), are promising cathode materials for Li batteries due in part to their large capacity and high current capability. A new synthesis of Ag 2 VO 2 PO 4 based on microwave heating is disclosed, where the reaction time is reduced by approximately 100 times relative to other reported methods, and the crystallite size is controlled via synthesis temperature, showing a linear positive correlation of crystallite size with temperature. Reaction times of an hour or less are sufficient to render phase-pure material after reaction at 50° C. to 180° C., significantly lower than the temperatures reported for other methods. Crystallite sizes between 42 nm and 60 nm are achieved by the novel method, smaller than by other methods. Silver/vanadium atomic ratios of 1.96 to 2.04 in the as-synthesized SVOP result and appear temperature-dependent. Notably, under galvanostatic reduction, the Ag 2 VO 2 PO 4 sample with the smallest crystallite size delivers the highest capacity and shows the highest loaded voltage.

Takeuchi, Kenneth J.↗

DOE OSTI2014

A coherent method for the detection and parameter estimation of continuous gravitational wave signals using a pulsar timing array

The use of a high precision pulsar timing array is a promising approach to detecting gravitational waves in the very low frequency regime (10{sup –6}-10{sup –9} Hz) that is complementary to ground-based efforts (e.g., LIGO, Virgo) at high frequencies (∼10-10{sup 3} Hz) and space-based ones (e.g., LISA) at low frequencies (10{sup –4}-10{sup –1} Hz). One of the target sources for pulsar timing arrays is individual supermassive black hole binaries which are expected to form in galactic mergers. In this paper, a likelihood-based method for detection and parameter estimation is presented for a monochromatic continuous gravitational wave signal emitted by such a source. The so-called pulsar terms in the signal that arise due to the breakdown of the long-wavelength approximation are explicitly taken into account in this method. In addition, the method accounts for equality and inequality constraints involved in the semi-analytical maximization of the likelihood over a subset of the parameters. The remaining parameters are maximized over numerically using Particle Swarm Optimization. Thus, the method presented here solves the monochromatic continuous wave detection and parameter estimation problem without invoking some of the approximations that have been used in earlier studies.

79 ASTRONOMY AND ASTROPHYSICS↗