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DOE OSTI2021

Key predictors of soil organic matter vulnerability to mineralization differ with depth at a continental scale

Abstract Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. However, our understanding of the controls on SOM mineralization is still incomplete, and as such, our ability to predict carbon-climate feedbacks is limited. To improve our understanding of controls on SOM decomposition, A and upper B horizon soil samples from 26 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and sample-specific field capacity (−33 kPa) water potential. Cumulative carbon dioxide respired was periodically measured and normalized by soil organic C content to calculate cumulative specific respiration (CSR), a metric of SOM vulnerability to mineralization. The Boruta algorithm, a feature selection algorithm, was used to select important predictors of CSR from 159 variables. A diverse suite of predictors was selected (12 for A horizons, 7 for B horizons) with predictors falling into three categories corresponding to SOM chemistry, reactive Fe and Al phases, and site moisture availability. The relationship between SOM chemistry predictors and CSR was complex, while sites that had greater concentrations of reactive Fe and Al phases or were wetter had lower CSR. Only three predictors were selected for both horizon types, suggesting dominant controls on SOM decomposition differ by horizon. Our findings contribute to the emerging consensus that a broad array of controls regulates SOM decomposition at large scales and highlight the need to consider changing controls with depth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Eigensolver performance comparison on Cray XC systems

Summary Hermitian (symmetric) eigenvalue solvers are the core constituents of electronic structure, quantum‐chemistry, and other HPC applications such as Quantum ESPRESSO, VASP, CP2K, and NWChem to name a few. Our understanding of the performance of symmetric eigenvalue algorithms on various hardware is clearly important to the quantum chemistry or condensed matter physics community but in fact goes beyond that community. For instance, big data analytics is increasingly utilizing eigenvalues solvers, in the study of randomized singular value decomposition (SVD) or principal component analysis (PCA). Noise, vibration, and harshness (NVH) is another field where fast and efficient eigenvalue solvers are required. Most eigenvalue solver packages feature numerous different parameters which can be tuned for performance, eg, the number of nodes, number of total ranks, the decomposition of the matrix, etc. In this paper, we investigate the performance of different packages as well as the influence of these knobs on the solver performance.

Cook, Brandon↗

DOE OSTI2016

Benchmark study of the two-dimensional Hubbard model with auxiliary-field quantum Monte Carlo method

Ground-state properties of the Hubbard model on a two-dimensional square lattice are studied by the auxiliary-field quantum Monte Carlo method. Accurate results for energy, double occupancy, effective hopping, magnetization, and momentum distribution are calculated for interaction strengths of U/t from 2 to 8, for a range of densities including half-filling and n = 0.3,0.5,0.6, 0.75, and 0.875. At half-filling, the results are numerically exact. Away from half-filling, the constrained path Monte Carlo method is employed to control the sign problem. Our results are obtained with several advances in the computational algorithm, which are described in this paper in detail. We discuss the advantages of generalized Hartree-Fock trial wave functions and its connection to pairing wave functions, as well as the interplay with different forms of Hubbard-Stratonovich decompositions. We study the use of different twist angle sets when applying the twist averaged boundary conditions. We propose the use of quasirandom sequences, which improves the convergence to the thermodynamic limit over pseudorandom and other sequences. With it and a careful finite size scaling analysis, we are able to obtain accurate values of ground-state properties in the thermodynamic limit. Detailed results for finite-sized systems up to 16 × 16 are also provided for benchmark purposes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

SPADES (Scalable Parallel Discrete Events Simulation) [SWR-24-99]

SPADES (Solver for PArallel Discrete Event Simulation) is an open-source parallel discrete event simulation (PDES) package built on the AMReX library. Targeted at solving discrete event systems in parallel, this software package aims to be performance portable and scalable on heterogeneous computing architectures, e.g., graphic processing units (GPU). SPADES implements optimistic synchronization with rollback through an implementation of the Time Warp algorithm. An alternative conservative synchronization approach is also implemented using the Lower Bound on Incoming Time Stamp. In our implementation, logical processes are represented as cells in a grid and event messages are represented as particles. SPADES supports various parallel decomposition strategies, including the use of the Message Passing Interface (MPI) and OpenMP threading. All major GPU architectures (e.g., Intel, AMD, NVIDIA) are supported through the use of performance portability functionalities implemented in AMReX. The SPADES software is released in NREL Software Record SWR-24-99 “SPADES (Scalable Parallel Discrete Events Simulation)”.

Henry de Frahan, Marc [National Renewable Energy L↗

DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Chiral rank-$k$ truncations for the multigrid preconditioner of Wilson fermions in lattice QCD

We present a modification to the setup algorithm for the multigrid preconditioner of Wilson fermions in lattice QCD. A larger number of test vectors than that used in conventional multigrid is generated by the smoother. This set of test vectors is then truncated by a singular value decomposition on the chiral components of the test vectors, which are subsequently used to form the prolongation and restriction matrices of the multigrid hierarchy. This modification is demonstrated to improve the convergence of linear equations on an anisotropic lattice with 𝑚𝜋 ≈ 280 MeV from the Hadron Spectrum Collaboration and an isotropic lattice with 𝑚𝜋 ≈ 220 MeV from the MILC Collaboration. The lattice volume dependence of the method is also examined.

Whyte, Travis [Jülich Supercomputing Center, Jülic↗

NASA NTRS1982

Operator split methods in the numerical solution of the finite deformation elastoplastic dynamic problem

The spatial formulation of the elastoplastic dynamic problem for finite deformations is considered. A thermodynamic argument leads to an additive decomposition of the spatial rate of deformation tensor and allows an operator split of the evolutionary equations of the problem into elastic and plastic parts. This operator split is taken as the basis for the definition of a global product algorithm. In the context of finite element discretization the product algorithm entails, for every time step, the solution of a nonlinear elastodynamic problem followed by the application of plastic algorithms that operate on the stresses and internal variables at the integration points and bring in the plastic constitutive equations. Suitable plastic algorithms are discussed for the cases of perfect and hardening plasticity and viscoplasticity. The proposed formalism does not depend on any notion of smoothness of the yield surface and is applicable to arbitrary convex elastic regions, with or without corners. The stabiity properties of the global product algorithm are shown to be identical to those of the algorithm used for the integration of the nonlinear elastodynamic problem. Numerical examples illustrate the accuracy of the method.

Pinsky, P. M.↗

DOE OSTI2020

Localized Exponential Time Differencing Method for Shallow Water Equations: Algorithms and Numerical Study

Here, we explore the performance of the exponential time differencing (ETD) method applied to the rotating shallow water equations. Comparing with explicit time stepping of the same order accuracy in time, the ETD algorithms could reduce the computational time in many cases by allowing the use of large time step sizes while still maintaining numerical stability. To accelerate the ETD simulations, we propose a localized approach that synthesizes the ETD method and overlapping domain decomposition. By dividing the original problem into many subdomain problems of smaller sizes and solving them locally, the proposed approach could speed up the calculation of matrix exponential vector products. Several standard test cases for shallow water equations of one or multiple layers are considered. The results show great potential of the localized ETD method for high-performance computing because each subdomain problem can be naturally solved in parallel at every time step.

58 GEOSCIENCES↗

NASA NTRS1979

Data reduction and performance determination

Definitions, algorithms, and procedures for the reduction of monopropellant thruster measurements to performance parameters are provided. A brief discussion of acquisition and recording systems is also included. Emphasis is placed upon monopropellant hydrazine engines, and some parameters relate specifically to the catalytic decomposition of hydrazine (e.g., percent ammonia dissociation). Performance of other types of monopropellant thrusters may, however, be determined by using procedures similar to those discussed. Two appendixes are included: (1) theoretical performance of monopropellant hydrazine; and (2) calculation of rotational performance.

Source record↗

NASA NTRS2010

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Kiely, Aaron↗

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

Path-Integrated Stereo X-Ray Digital Image Correlation: Resolving the Violation of Conservation of Intensity

In this study, x-ray imaging addresses many challenges with visible light imaging in extreme environments, where optical diagnostics such as digital image correlation (DIC) and particle image velocimetry (PIV) suffer biases from index of refraction changes and/or cannot penetrate visibly occluded objects. However, conservation of intensity—the fundamental principle of optical image correlation algorithms—may be violated if ancillary components in the X-ray path besides the surface or fluid of interest move during the test. The test series treated in this work sought to characterize the safe use of fiber-epoxy composites in aerospace and aviation industries during fire accident scenarios. Stereo X-ray DIC was employed to measure test unit deformation in an extreme thermal environment involving a visibly occluded test unit, incident surface heating to temperatures above 600°C, and flames and soot from combusting epoxy decomposition gasses. The objective of the current work is to evaluate two solutions to resolve the violation of conservation of intensity that resulted from both the test unit and the thermal chamber deforming during the test. The first solution recovered conservation of intensity by pre-processing the path-integrated X-ray images to isolate the DIC pattern of the test unit from the thermal chamber components. These images were then correlated with standard, optical DIC software. The second solution, called Path-Integrated Digital Image Correlation (PI-DIC), modified the fundamental matching criterion of DIC to account for multiple, independently-moving components contributing to the final image intensity. The PI-DIC algorithm was extended from a 2D framework to a stereo framework and implemented in a custom DIC software. Both solutions accurately measured the cylindrical shape of the undeformed test unit, recovering radii values of R = 76.20±0.12 mm compared to the theoretical radius of R theor = 76.20 mm. During the test, the test unit bulged asymmetrically as decomposition gasses pressurized the interior and eventually burned in a localized jet. Both solutions measured the heterogeneous radius of this bulge, which reached a maximum of approximately R = 91 mm, with a discrepancy of 2–3% between the two solutions. Two solutions that resolve the violation of conservation of intensity for path-integrated X-ray images were developed. Both were successfully employed in a stereo X-ray DIC configuration to measure deformation of an aluminum-skinned, fiber-epoxy composite test unit in a fire accident scenario.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

TU-G-204-02: Automatic Sclerotic Bone Metastases Detection in the Pelvic Region From Dual Energy CT

Purpose: To automatically detect sclerotic bone metastases in the pelvic region using dual energy computed tomography (DECT). Methods: We developed a two stage algorithm to automatically detect sclerotic bone metastases in the pelvis from DECT for patients with multiple bone metastatic lesions and with hip implants. The first stage consists of extracting the bone and marrow regions by using a support vector machine (SVM) classifier. We employed a novel representation of the DECT images using multi-material decomposition, which represents each voxel as a mixture of different physical materials (e.g. bone+water+fat). Following the extraction of bone and marrow, in the second stage, a bi -histogram equalization method was employed to enhance the contrast to reveal the bone metastases. Next, meanshift segmentation was performed to separate the voxels by their intensity levels. Finally, shape-based filtering was performed to extract the possible locations of the metastatic lesions using multiple shape criteria. We used the following shape parameters: area, eccentricity, major and minor axis, perimeter and skeleton. Results: A radiologist with several years of experience with DECT manually labeled 64 regions consisting of metastatic lesions from 10 different patients. However, the patients had many more metastasic lesions throughout the pelvis. Our method correctly identified 46 of the marked 64 regions (72%). In addition, our method also identified several other lesions, which can then be validated by the radiologist. The missed lesions were typically very large elongated regions consisting of several islands of very small (<4mm) lesions. Conclusion: We developed an algorithm to automatically detect sclerotic lesions in the pelvic region from DECT. Preliminary assessment shows that our algorithm generated lesions agreeing with the radiologist generated candidate regions. Furthermore, our method reveals additional lesions that can be inspected by the radiologist, thereby, reducing radiologist effort in identifying all the lesions with poor contrast from the DECT images.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Analysis of MHD stability and active mode control on KSTAR for high confinement, disruption-free plasma

Long-pulse plasma operation at high normalized beta, $β_N$, above the $\textit{n}$= 1 ideal MHD no-wall stability limit in KSTAR is presently limited by tearing instabilities rather than resistive wall modes. H-mode plasma operation during the recent KSTAR device campaign produced discharges having strong $\textit{m/n}$= 2/1 tearing instabilities at $β_N$ lower than the ideal MHD no-wall beta limit. The unstable tearing mode consequently reduced plasma confinement and toroidal plasma rotation significantly. We report the experiment confirmed that an extended duration of electron cyclotron heating (ECH) at the initial phase of the discharge plays a critical role in mode destabilization. To study destabilizing mechanisms that affect the mode growth, the stability of the observed tearing modes from plasmas with significantly different $β_N$ is computed by using the resistive DCON code and the M3D-C 1 code. Equilibrium reconstructions that include constraints from internal profile diagnostics, and computed fast particle pressure are used as input for reliable computation of stability. The classical tearing stability index, Δ', from resistive DCON is computed to be unstable when the island is fully saturated with large amplitude, while the unstable mode is not computed by M3D-C 1 . The modified Rutherford equation (MRE) describing the evolution of the island width has been constructed for KSTAR plasmas by using plasma parameters computed by the TRANSP code. The MRE model estimates a saturated island width corresponding to ~10% of the plasma minor radius for equilibrium at high $β_N$ 3 having a stable Δ' from the resistive DCON. In preparation for long-pulse plasma operation at higher beta utilizing increased plasma heating power, a resistive wall mode (RWM) active feedback control algorithm has been completed and enabled on KSTAR. To accurately determine the $\textit{n}$= 1component produced by RWMs, an algorithm has been developed that includes magnetic sensor compensation of the prompt applied field and the field from the induced current on the passive conductors. Use of multiple toroidal sensor arrays is enabled by modifying the sensor toroidal angles assumed in mode decomposition to include the effect of varied mode helicities in the outboard region where the mode measurement is made. This analysis on stability, transport, and control provides the required foundation for disruption prediction and avoidance research on KSTAR.

resistive wall mode (RWM)↗

DOE OSTI2019

Reactions of concerted decomposition of cyclic molecules, as studied by the quantum chemistry methods and parabolic model

Reactions of concerted decomposition of cyclic molecules (Diels—Alder retro-reactions) were studied using quantum chemical modeling and the method of intersecting parabolas (M3IP model). According to results of quantum chemical calculations and topological analysis of transition states (TSs) of five concerted decomposition reactions of cyclic molecules, all TSs represent six-membered rings in which the bonds being cleaved are weak covalent ones. The presence of ring heteroatoms (N, O, or S) has a strong impact on the TS geometry and on the energy characteristics of the reactions. The M3IP model was used to process the experimental results to develop an algorithm for calculating the activation energies (E) of the reactions in question and the classical potential barriers to thermally neutral reaction (E{sub e}{sup 0}). Factors influencing the energies E were determined and assessed. These include the enthalpy of reaction, substituents, ring heteroatoms, the force constants of bonds, and the bond dissociation energies. A comparison of the activation energies E and the enthalpies of reaction ΔH obtained from the M3IP and density functional B3LYP/6-311++G** calculations revealed good agreement between them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Multivariate Empirical Mode Decomposition Based Signal Analysis and Efficient-Storage in Smart Grid

Wide-area-measurement systems (WAMSs) are used in smart grid systems to enable the efficient monitoring of grid dynamics. However, the overwhelming amount of data and the severe contamination from noise often impede the effective and efficient data analysis and storage of WAMS generated measurements. To solve this problem, we propose a novel framework that takes advantage of Multivariate Empirical Mode Decomposition (MEMD), a fully data-driven approach to analyzing non-stationary signals, dubbed MEMD based Signal Analysis (MSA). The frequency measurements are considered as a linear superposition of different oscillatory components and noise. The low-frequency components, corresponding to the long-term trend and inter-area oscillations, are grouped and compressed by MSA using the mean shift clustering algorithm. Whereas, higher-frequency components, mostly noise and potentially part of high-frequency inter-area oscillations, are analyzed using Hilbert spectral analysis and they are delineated by statistical behavior. By conducting experiments on both synthetic and real-world data, we show that the proposed framework can capture the characteristics, such as trends and inter-area oscillation, while reducing the data storage requirements

Big Data↗

DOE OSTI2017

The Approximability of Partial Vertex Covers in Trees.

Motivated by applications in risk management of computational systems, we focus our attention on a special case of the partial vertex cover problem, where the underlying graph is assumed to be a tree. Here, we consider four possible versions of this setting, depending on whether vertices and edges are weighted or not. Two of these versions, where edges are assumed to be unweighted, are known to be polynomial-time solvable (Gandhi, Khuller, and Srinivasan, 2004). However, the computational complexity of this problem with weighted edges, and possibly with weighted vertices, has not been determined yet. The main contribution of this paper is to resolve these questions, by fully characterizing which variants of partial vertex cover remain intractable in trees, and which can be efficiently solved. In particular, we propose a pseudo-polynomial DP-based algorithm for the most general case of having weights on both edges and vertices, which is proven to be NPhard. This algorithm provides a polynomial-time solution method when weights are limited to edges, and combined with additional scaling ideas, leads to an FPTAS for the general case. A secondary contribution of this work is to propose a novel way of using centroid decompositions in trees, which could be useful in other settings as well.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Prediction of new thermodynamically stable aluminum oxides

Recently, it has been shown that under pressure, unexpected and counterintuitive chemical compounds become stable. Laser shock experiments (A. Rode, unpublished) on alumina (Al 2 O 3 ) have shown non-equilibrium decomposition of alumina with the formation of free Al and a mysterious transparent phase. Inspired by these observations, we have explored the possibility of the formation of new chemical compounds in the system Al-O. Using the variable-composition structure prediction algorithm USPEX, in addition to the well-known Al 2 O 3 , we have found two extraordinary compounds Al 4 O 7 and AlO 2 to be thermodynamically stable in the pressure ranges 330-443 GPa and above 332 GPa, respectively. Both of these compounds at the same time contain oxide O 2- and peroxide O 2 2- ions and both are insulating. Peroxo-groups are responsible for gap states, which significantly reduce the electronic band gap of both Al 4 O 7 and AlO 2 .

Science & Technology - Other Topics↗