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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

High Resolution Model Development to Quantify the Impact of Icebergs on the Stability of the Atlantic Meridional Overturning Circulation

In the present-day North Atlantic Ocean, relatively warm and salty water moves northwards from the tropics to the high latitudes, sinks, and returns southward towards the equator as North Atlantic Deep Water, forming the so called Atlantic Meridional Overturning Circulation (AMOC). It has been found that the stability of the AMOC is non-linearly related to the freshwater budget of the North Atlantic. In this way, additional fresh water can be added to the ocean with little impact, until a tipping point is reached that causes the AMOC to suddenly weaken and the Northern Hemisphere to abruptly cool. A great deal of uncertainty still remains over the sensitivity of the AMOC to changes in freshwater discharge as a result of the unrealistic manner in which freshwater has historically been added to climate models. Frequently, freshwater is discharged in ocean models entirely as liquid water, but in reality a large fraction of freshwater entering the ocean is ice calving from marine glaciers (half for Antarctica and two-thirds for Greenland). To more accurately quantify AMOC sensitivity to past and future changes in freshwater input, this project developed a comprehensive iceberg model to more realistically simulate the interaction between the cryosphere and the oceans at high-latitudes. The iceberg model created is written in Fortran90 and designed to scale efficiently on High Performance Computing (HPC) clusters so that tens-of-thousands of icebergs can be simulated at any time. Experiments performed with our model showed that in the Pleistocene there would have been enormous floods of freshwater released into the North Atlantic that would have transported icebergs and meltwater along the entire east coast of the United States, as far south as Florida Keys. In addition, high-resolution, modern-day, model simulations showed that if the Greenland Ice Sheet continues to melt at its current rate then there will be a 6-fold increase in the number of icebergs drifting in the North Atlantic in the next 30 years, and that the strength of the AMOC could weaken by 3.5%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A bi-level spatiotemporal clustering approach and its application to drought extraction

We present a novel flexible bi-level spatiotemporal clustering algorithm to extract events based on their intensity and spatiotemporal structures. Our algorithm consists of using (i) a novel space-time k-means clustering to obtain spatiotemporally coherent intensity clusters, and (ii) a density-based spatial clustering of applications with noise (DBSCAN) to spatiotemporally section the intensity clusters into individual events. We discuss the development of the algorithm, the selection, tuning and meaning of the parameters within each step, as well as its validation. Finally, we apply the algorithm to a spatiotemporal drought index, standardized vapor pressure deficit drought index (SVDI), over the continental United States (US) from 1980–2021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents.

17 WIND ENERGY↗
DOE OSTI2023

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Analysis of spin frustration in an Fe III 7 cluster using a combination of computational, experimental, and magnetostructural correlation methods

The synthesis, structure, and magnetic properties are reported for [Fe 7 O 3 (O 2 C t Bu) 9 (mda) 3 (H 2 O) 3 ] ( 1 ), where mdaH 2 is N -methyldiethanolamine. 1 was prepared from the reaction of [Fe 3 O(O 2 C t Bu) 6 (H 2 O) 3 ](NO 3 ) with mdaH 2 in a 1:~3 ratio in MeCN. The core of 1 consists of a central octahedral Fe III ion held within a non-planar Fe 6 loop by three μ 3 -O 2- and three μ 2 -RO - arms from the three mda 2- chelates. Variable-temperature dc and ac magnetic susceptibility studies revealed dominant antiferromagnetic coupling, leading to a ground state spin of S = 5 / 2 . The ground state was confirmed by a fit of magnetization data collected in the 0.1–7.0 T and 1.8–10.0 K ranges. The four Fe 2 pairwise exchange parameters ( J 1 - J 4 ) were estimated by independent methods: theoretical calculations using either broken symmetry energy differences (-46.3, -16.2, -3.9, and - 28.1 cm -1 , respectively) or Green’s function approximation methods (-41.4, -14.8, -13.2, and - 24.7 cm -1 ), and a magnetostructural correlation (MSC) previously developed for high nuclearity Fe III /O complexes (-39.5, -13.8, -6.7, and - 23.5 cm -1 ). Additionally, the J 1 - J 4 obtained from the MSC and theoretical methods were used with the program PHI to both simulate χ M T vs T as well as to serve as reasonable input values to fit the experimental data (-41.0, -11.4, -5.0, and - 27.3 cm -1 ). Analysis of the J ij led to identification of the spin frustration effects operative and the resultant spin vector alignments at each Fe III ion, thus allowing for the rationalization of the experimental ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Designing networks: A mixed-integer linear optimization approach

Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network temporal evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this work, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present useful modeling techniques and apply them to mathematically express and constrain a broad class of network properties in the context of an optimization formulation. We derive complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Mining data in a dynamic PRA framework

Computational (also known as Dynamic) Probabilistic Risk Assessment (PRA) methods employs system simulation codes coupled with stochastic analysis tools in order to determine probabilities of certain outcomes such as system failure. In contrast to classical PRA methods (i.e., Event-Tree and Fault-Tree) in which timing and sequencing of events is set by the analyst, accident progression is dictated by the system control logic and its interaction with system temporal evolution. Due to the nature of the problem, Simulation-Based PRA methods require large amount of computationally expensive simulation runs. In addition, these methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). In this paper we investigate and apply several methods and algorithms to analyze these large amounts of time-dependent data. Furthermore, the scope of this article is to present a broad overview of methods and algorithms that can be used to improve data quality and to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Uranyl Carbonate Complexes in Aqueous Solution and Their Ligand NMR Chemical Shifts and 17 O Quadrupolar Relaxation Studied by ab Initio Molecular Dynamics

Dynamic structural effects, NMR ligand chemical shifts, and 17 O NMR quadrupolar relaxation rates are investigated in the series of complexes UO 2 2+ , UO 2 (CO 3 ) 3 4– , and (UO 2 ) 3 (CO 3 ) 6 6– . Car–Parrinello molecular dynamics (CPMD) is used to simulate the dynamics of the complexes in water. NMR properties are computed on clusters extracted from the CPMD trajectories. In the UO 2 2+ complex, coordination at the uranium center by water molecules causes a decrease of around 300 ppm for the uranyl 17 O chemical shift. The final value of this chemical shift is within 40 ppm of the experimental range. The UO 2 (CO 3 ) 3 4– and (UO 2 ) 3 (CO 3 ) 6 6– complexes show a solvent dependence of the terminal carbonate 17 O and 13 C chemical shifts that is less pronounced than that for the uranyl oxygen atom. Corrections to the chemical shift from hybrid functionals and spin–orbit coupling improve the accuracy of chemical shifts if the sensitivity of the uranyl chemical shift to the uranyl bond length (estimated at 140 ppm per 0.1 Å from trajectory data) is taken into consideration. The experimentally reported trend in the two unique 13 C chemical shifts is correctly reproduced for (UO 2 ) 3 (CO 3 ) 6 6– . NMR relaxation rate data support large 17 O peak widths, but remain below those noted in the experimental literature. Furthermore, comparison of relaxation data for solvent-including versus solvent-free models suggest that carbonate ligand motion overshadows explicit solvent effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Immobilization of “Capping Arene” Cobalt(II) Complexes on Ordered Mesoporous Carbon for Electrocatalytic Water Oxidation

We report the synthesis, characterization, and electrocatalytic water oxidation activity of two cobalt complexes, (6-FP)Co(NO 3 ) 2 (1) (6-FP = 8,8'-(1,2-phenylene)diquinoline) and (5-FP)Co(NO 3 ) 2 (2) (5-FP = 1,2-bis(N-7-azaindolyl)benzene), containing "capping arene" bidentate ligands with nitrogen atom donors. The cobalt complexes 1 and 2 were supported on ordered mesoporous carbon (OMC) by π-π stacking, resulting in heterogenized cobalt materials 6-FP-Co-OMC-1 and 5-FP-Co-OMC-2, respectively, and studied for electrocatalytic water oxidation. We find that 6-FP-Co-OMC-1 exhibits an overpotential of 355 mV for a current density of 10 mA cm -2 and a turnover frequency (TOF) of ~0.53 s -1 at an overpotential of 400 mV at pH 14. 6-FP-Co-OMC-1 exhibits activity that is ~1.6 times that of 5-FP-Co-OMC-2, which gives a TOF of 0.32 s -1 at 400 mV overpotential. The structural stability of the single-atom Co site was demonstrated for 6-FP-Co-OMC-1 using X-ray absorption spectroscopy for the molecular complex supported on OMC, but slow degradation in catalyst activity can be attributed to eventual formation of Co oxide clusters. DFT computations of electrocatalytic water oxidation using the molecular complexes as models provide a description of the catalytic mechanism. These studies reveal that the mechanism for O-O bond formation involves an intermediate Co IV oxo complex that undergoes an intramolecular reductive O-O coupling to form a Co II -OOH species. Further, the calculations predict that the molecular 6-FP-Co structure is more active for electrocatalytic water oxidation than 5-FP-Co, which is consistent with experimental studies of 6-FP-Co-OMC-1 and 5-FP-Co-OMC-2, highlighting the possibility that the ligand structure influences the catalytic activity of the supported molecular catalysts.

25 ENERGY STORAGE↗
DOE OSTI2018

Tomographic analysis of tangential viewing cameras (invited)

Many tokamaks now use visible light cameras to observe plasma-wall interactions and integrated line emission. The DIII-D coherence imaging spectroscopy diagnostic cameras image interferograms that encode line integrated velocity. By modeling the 2D camera image pixels as line of sight integrals through an axisymmetric discrete grid, it is possible to do tomographic analysis to determine the local plasma line emissivity and parallel velocity. Approaches to solve the inverse problem posed by these tangential viewing cameras are presented. The inversion begins with calculation of the sparse response matrix that encompasses all the geometry and diagnostic information and reduces the process of image formation to a sparse matrix-vector multiply. Our report includes techniques for determining the detailed geometry of the camera views and methods for handling physical quantities that vary spatially. Additionally, the size of the response matrix has driven the development of capability to distribute the coarse parallel calculation across a heterogeneous cluster of computers on the Energy Sciences Network. Iterative techniques are then used to solve the sparse matrix-vector linear system

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Non-dilute helium-related defect interactions in the near-surface region of plasma-exposed tungsten

We report a systematic energetic analysis of helium-related defect interactions that mediate helium (He) segregation on surfaces of plasma-exposed tungsten at different levels of He ion implantation. We focus on high He fluences that increase the He content in the plasma-exposed material well beyond the dilute limit of He concentration and employ atomic configurations generated by large-scale molecular dynamics simulations of He-implanted tungsten. We perform systematic molecular statics computations of cluster– defect interaction energetics in the highly defect-rich near-surface region of plasma-exposed tungsten for small mobile helium clusters as a function of the cluster distance from the surface. In this region, mobile clusters are also subjected to the stress fields generated by defects such as helium bubbles and other clusters, which govern cluster–defect interactions in addition to the cluster–surface interaction. Based on systematic investigation of individual cluster–defect interactions, we develop a mathematical framework to describe the interaction energy landscapes consisting of elastic interaction potential perturbations to finite-width square-well potentials, where the potential well accounts for cluster trapping by the defect at close range and subsequent coalescence and the perturbation potential is parameterized according to elastic inclusion theory. Superposition of all the relevant interaction potentials provides a comprehensive description of the interaction energy landscape that would be experienced by a small mobile cluster along its migration path toward the plasma-exposed surface at high He fluence. Such descriptions are particularly important for developing atomistically-informed, hierarchical multi-scale models of helium cluster dynamics in plasma-facing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coarse-grain cluster analysis of tensors with application to climate biome identification

A tensor provides a concise way to codify the interdependence of complex data. Treating a tensor as a d-way array, each entry records the interaction between the different indices. Clustering provides a way to parse the complexity of the data into more readily understandable information. Clustering methods are heavily dependent on the algorithm of choice, as well as the chosen hyperparameters of the algorithm. However, their sensitivity to data scales is largely unknown. In this work, we apply the discrete wavelet transform to analyze the effects of coarse-graining on clustering tensor data. We are particularly interested in understanding how scale affects clustering of the Earth's climate system. The discrete wavelet transform allows classification of the Earth's climate across a multitude of spatial-temporal scales. The discrete wavelet transform is used to produce an ensemble of classification estimates, as opposed to a single classification. Each element of the ensemble is a clustering at a different spatial-temporal scale. Information theoretic approaches are used to identify important scale lengths in clustering the L15 Climate Datset. We also discover a sub-collection of the ensemble that spans the majority of the variance observed, allowing for efficient consensus clustering techniques that can be used to identify climate biomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Microscopic origin of temperature-dependent magnetism in spin-orbit-coupled transition metal compounds

A few 4 d and 5 d transition metal compounds with various electron fillings were recently found to exhibit magnetic susceptibilities χ and magnetic moments that deviate from the well-established Kotani model. This model has been considered for decades to be the canonical expression for descriing the temperature dependence of magnetism in systems with nonnegligible spin-orbit coupling effects. In this paper, we uncover the origin of such discrepancies and determine the applicability and limitations of the Kotani model by calculating the temperature dependence of the magnetic moments of a series of 4 d (Ru-based) and 5 d (W-based) systems at different electron fillings. For this purpose, we perform exact diagonalization of -derived relativistic multiorbital Hubbard models on finite clusters and compute their magnetic susceptibilities. Comparison with experimentally measured magnetic properties indicates that contributions such as a temperature-independent χ 0 background, crystal field effects, Coulomb and Hund's couplings, and intersite interactions—not included in the Kotani model—are especially crucial for correctly describing the temperature dependence of χ and magnetic moments at various electron fillings in these systems. Based on our results, we propose a generalized approach beyond the Kotani model to accurately describe their magnetism. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

WfBench: Automated Generation of Scientific Workflow Benchmarks

The prevalence of scientific workflows with high computational demands calls for their execution on various distributed computing platforms, including large-scale leadership-class high-performance computing (HPC) clusters. To handle the deployment, monitoring, and optimization of workflow executions, many workflow systems have been developed over the past decade. There is a need for workflow benchmarks that can be used to evaluate the performance of workflow systems on current and future software stacks and hardware platforms.We present a generator of realistic workflow benchmark specifications that can be translated into benchmark code to be executed with current workflow systems. Our approach generates workflow tasks with arbitrary performance characteristics (CPU, memory, and I/O usage) and with realistic task dependency structures based on those seen in production workflows. We present experimental results that show that our approach generates benchmarks that are representative of production workflows, and conduct a case study to demonstrate the use and usefulness of our generated benchmarks to evaluate the performance of workflow systems under different configuration scenarios.

Coleman, Taina↗