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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Evaluation and Comparison of Machine Learning Techniques for Rapid QSTS Simulations

Rapid and accurate quasi-static time series (QSTS) analysis is becoming increasingly important for distribution system analysis as the complexity of the distribution system intensifies with the addition of new types, and quantities, of distributed energy resources (DER). The expanding need for hosting capacity analysis, control systems analysis, photovoltaic (PV) and DER impact analysis, and maintenance cost estimations are just a few reasons that QSTS is necessary. Historically, QSTS analysis has been prohibitively slow due to the number of computations required for a full-year analysis. Therefore, new techniques are required that allow QSTS analysis to rapidly be performed for many different use cases. This research demonstrates a novel approach to doing rapid QSTS analysis for analyzing the number of voltage regulator tap changes in a distribution system with PV components. A representative portion of a yearlong dataset is selected and QSTS analysis is performed to determine the number of tap changes, and this is used as training data for a machine learning algorithm. The machine learning algorithm is then used to predict the number of tap changes in the remaining portion of the year not analyzed directly with QSTS. The predictions from the machine learning algorithms are combined with the results of the partial year simulation for a final prediction for the entire year, with the goal of maintaining an error <10% on the full-year prediction. Five different machine learning techniques were evaluated and compared with each other; a neural network ensemble, a random forest decision tree ensemble, a boosted decision tree ensemble, support vector machines, and a convolutional neural network deep learning technique. A combination of the neural network ensemble together with the random forest produced the best results. Using 20% of the year as training data, analyzed with QSTS, the average performance of the technique resulted in ~2.5% error in the yearly tap changes, while maintaining a <10% 99.9 th percentile error bound on the results. This is a 5x speedup compared to a standard, full-length QSTS simulation. These results demonstrate the potential for applying machine learning techniques to facilitate modern distribution system analysis and further integration of distributed energy resources into the power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Analysis of the Temporal Response of Coupled Asymmetrical Zero-Power Subcritical Bare Metal Reactor Systems

The behavior of symmetrical coupled-core systems has been extensively studied, yet there is a dearth of research on asymmetrical systems due to the increased complexity of the analysis of such systems. In this research, the multipoint kinetics method is applied to asymmetrical zeropower, subcritical, bare metal reactor systems. Existing research on asymmetrical reactor systems assumes symmetry in the neutronic coupling; however, it will be shown that this cannot always be assumed. Deep subcriticality adds another layer of complexity and requires modification of the multipoint kinetics equations to account for the effect of the external neutron source. A modified set of multipoint kinetics equations is derived with this in mind. Subsequently, the Rossi-alpha equations are derived for a two-region asymmetrical reactor system. The predictive capabilities of the radiation transport code MCNP6 for neutron noise experiments are shown in a comparison to the results of a series of Rossi-alpha measurements performed by J. Mihalczo utilizing a coupled set of symmetrical bare highly-enriched uranium (HEU) cylinders. The ptrac option within MCNP6 can generate time-tagged counts in a cell (list-mode data). The list-mode data can then be processed similarly to measured data to obtain values for system parameters such as the dual prompt neutron decay constants observable in a coupled system. The results from the ptrac simulations agree well with the historical measured values. A series of case studies are conducted to study the effects of geometrical asymmetry in the coupling between two bare metal HEU cylinders. While the coupling behavior of symmetrical systems has been reported on extensively, that of asymmetrical systems remains sparse. In particular, it appears that there has been no previous research in obtaining the coupling time constants for asymmetrically-coupled systems. The difficulty in observing such systems is due in part to the inability to determine the individual coupling coefficients from measurement: unlike the symmetrical cases, only the product of the values can be obtained. A method is proposed utilizing MCNP6 tally ratios to separate the coupling coefficients for such systems. This work provides insight into the behavior of asymmetrically-coupled systems as the separation distance between the two cores is changed and also as the asymmetry is increased. As the asymmetry increases, both the slower and the faster observable prompt neutron decay constants increase in magnitude. The coupling time constants are determined from the measured decay constants. As the separation distance increases, both coupling coefficients decrease as expected. Based on these findings, an effective computational method utilizing MCNP6 and the Rossialpha technique can be applied to the prediction of asymmetrical coupled system measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Impacts of hydrogen bonding interactions with Np(v/vi)O 2 Cl 4 complexes: vibrational spectroscopy, redox behavior, and computational analysis

The neptunyl (Np(V)O 2 + /Np(VI)O 2 2+ ) cation is the dominant form of 237 Np in acidic aqueous solutions and the stability of the Np(V) and Np(VI) species is driven by the specific chemical constituents present in the system. Hydrogen bonding with the oxo group may impact the stability of these species, but there is limited understanding of how these intermolecular interactions influence the behavior of both solution and solid-state species. In the current study, we systematically evaluate the interactions between the neptunyl tetrachloride species and hydrogen donors in coordination complexes and in the related aqueous solutions. Both Np(V) compounds (N 2 C 4 H 12 ) 2 [Np(V)O 2 Cl 4 ]Cl (Np(V)pipz) and (NOC 4 H 10 ) 3 [Np(V)O 2 Cl 4 ] (Np(V)morph) exhibit directional hydrogen bonding to the neptunyl oxo group while Np(VI) compounds (NC 5 H 6 ) 2 [Np(VI)O 2 Cl 4 ] (Np(VI)pyr) and (NOC 4 H 10 ) 4 [Np(VI)O 2 Cl 4 ]·2Cl (Np(VI)morph) assemble via halogen interactions. Here, the Raman spectra of the solid-state phases indicate the activation of vibrational bands when there is asymmetry of the neptunyl bond, while these spectral features are not observed within the related solution phase spectra. Density functional theory calculations of the Np(V)pipz system suggest that activation of the ν 3 asymmetric stretch and other combination modes lead to additional complexity within the solid-state spectra. Electrochemical analyses of complexes in the solution phases are consistent with the results of the crystallization experiments as the voltammetric potentials of Np(V)/Np(VI) complexes in the presence of protonated heterocycles differ from the potentials of pure Np(V) and may correlate with the hydrogen bonding interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A hybrid machine-learning approach for analysis of methane hydrate formation dynamics in porous media with synchrotron CT imaging

Fast multi-phase processes in methane hydrate bearing samples pose a challenge for quantitative micro-computed tomography study and experiment steering due to complex tomographic data analysis involving time-consuming segmentation procedures. This is because of the sample's multi-scale structure, which changes over time, low contrast between solid and fluid materials, and the large amount of data acquired during dynamic processes. Here, a hybrid approach is proposed for the automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media, which includes a deep-learning 3D U-Net model. To prepare a training dataset for the 3D U-Net, a technique to automate data labeling based on sample-specific information about the mineral matrix immobility and occasional fluid movement in pores is proposed. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as incremental flow and redistribution of pore brine. Results of the quantitative analysis showed that for typical gas-hydrate stability parameters (100 bar methane pressure, 7°C temperature) the rate of formation is slow (less than 1% per hour), after which the surface area of contact between brine and gas increases, resulting in faster formation (2.5% per hour). Hydrate growth reaches the saturation point after 11 h of the experiment. Finally, the efficacy of the proposed segmentation scheme in on-the-fly automatic data analysis and experiment steering with zooming to regions of interest is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.

Suchyta, Eric↗
DOE OSTI2024

Structural Trends and Vibrational Analysis of N,N,N′,N′−Tetramethylmalonamide Complexes Across the Lanthanide Series

Fundamental understanding of coordination chemistry across the lanthanide series is essential for explaining chemical behavior of rare-earth metals in complex liquid-liquid extraction processes, which in turn affects the distribution ratios and efficacy of separations as a whole. In this work, we explore the structural trends between the lanthanides and a neutral N,N,N',N'-tetramethylmalonamide (TMMA) ligand within four isolated families of solid-state compounds: Ln(trans-TMMA) 2 (NO 3 ) 3 Ln=La-Nd, Sm; Ln(cis-TMMA) 2 (NO 3 ) 3 Ln=Eu-Tb, Er; [Ln(TMMA) 3 (NO 3 ) 2 ][Ln(TMMA)(NO 3 ) 4 ] Ln=Dy-Tm; Ln(Κ 2 -TMMA)(iPrOH)(NO 3 ) 3 and Ln(Κ 1 -TMMA)(Κ 2 -TMMA)(NO 3 ) 3 Ln=Yb, Lu. Moving across the lanthanide series, we note the formation of both discrete charge-neutral complexes, as well as charged molecular anion-cation pairs, with variations in spatial ligand arrangement, coordination numbers, and ligand denticities. IR and Raman spectroscopy paired with DFT frequency calculations were used for an in-depth investigation of vibrational modes unique to each structural family. The collection of isolated model compounds was also discussed in the context of liquid-liquid separations based on reported distribution ratios from malonamide extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Development of Ambient Mass Spectrometry Rapid Analysis Methods for Trace Inorganics

Ambient mass spectrometry is being investigated as a new method for rapidly characterizing trace inorganic species, including nuclear materials. SRNL is currently developing electrospray ionization (ESI) and paper spray ionization (PSI) methods for mass spectrometry for the detection of trace inorganic compounds JEOL AccuTOF™-DART ® LP 4G mass spectrometer. Sample analysis generates a complex three-dimensional data set with 10 2 -10 3 individual mass spectra spread temporally. To improve the quality and ease of data extraction from this amount of information, a simple data analysis pipeline written in R/R Studio has been improved and expanded upon. Specifically, the software now has header inputs to set base input/output filenames, isotopes of interest, and a list of concentrations analyzed on the instrument. Using list-based structures to enable batch processing of many concentrations at once, it then loads each file, extracts the relevant intensities for masses of interest from each spectrum, and iterates through each concentration to generate graphs of internal standard & analyte correlations, measured isotope ratios, and total ion chromatograms. It then filters the data to remove points at background levels or at the detector saturation limit. Using this filtered data, the pipeline re-creates the graphs to reveal high-quality information from a low-quality raw dataset. All graphs of the R software then output to PowerPoint format. Additionally, faster 3D visualization functionality was added to the pipeline for viewing the entire data file produced by the instrument as an intensity map. With these data analysis tools ready, samples of strontium nitrate/yttrium nitrate as an analyte/internal standard combination were measured on the AccuTOF. From the filtered data, calibration curves were prepared and limits of detection (LOD) of 1 ppb for ESI-MS and 20 ppb for PSI-MS were obtained. The quality available from the calibration curves and the low limits of detection demonstrate the value of the instrument/analysis pipeline system in characterizing trace inorganics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Ultrafast dynamics of CN radical reactions with chloroform solvent under vibrational strong coupling

Polariton chemistry may provide a new means to control molecular reactivity, permitting remote, reversible modification of reaction energetics, kinetics, and product yields. A considerable body of experimental and theoretical work has already demonstrated that strong coupling between a molecular vibrational mode and the confined electromagnetic field of an optical cavity can alter chemical reactivity without external illumination. However, the mechanisms underlying cavity-altered chemistry remain unclear in large part because the experimental systems examined previously are too complex for detailed analysis of their reaction dynamics. Here, we experimentally investigate photolysis-induced reactions of cyanide radicals with strongly-coupled chloroform (CHCl 3 ) solvent molecules and examine the intracavity rates of photofragment recombination, solvent complexation, and hydrogen abstraction. Here we use a microfluidic optical cavity fitted with dichroic mirrors to facilitate vibrational strong coupling (VSC) of the C–H stretching mode of CHCl 3 while simultaneously permitting optical access at visible wavelengths. Ultrafast transient absorption experiments performed with cavities tuned on- and off-resonance reveal that VSC of the CHCl 3 C–H stretching transition does not significantly modify any measured rate constants, including those associated with the hydrogen abstraction reaction. This work represents, to the best of our knowledge, the first experimental study of an elementary bimolecular reaction under VSC. We discuss how the conspicuous absence of cavity-altered effects in this system may provide insights into the mechanisms of modified ground state reactivity under VSC and help bridge the divide between experimental results and theoretical predictions in vibrational polariton chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data

The Lomb–Scargle discrete Fourier transform (LSDFT) is a well-known technique for analyzing time series. In this study, a solution for empirical orthogonal functions (EOFs) based on irregularly sampled data is derived from the LSDFT. It is demonstrated that this particular algorithm has no hard limit on its accuracy and yields results comparable to those of complex Hilbert EOF analysis. Two LSDFT algorithms are compared in terms of their performance in evaluating EOFs for precipitation observations from the Tropical Rainfall Measuring Mission satellite. Both are shown to be able to capture the pattern of the diurnal cycle of rainfall over the complex topography and diverse land cover of South America, and both also show other consistent features in the 0–12-day frequency band.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Position Assignment and Oxidation State Recognition of Fe and Co Centers in Heterometallic Mixed-Valent Molecular Precursors for the Low-Temperature Preparation of Target Spinel Oxide Materials

A series of mixed-valent, heterometallic (mixed-transition metal) diketonates that can be utilized as prospective volatile single-source precursors for the low-temperature preparation of M x M' 3–x O 4 spinel oxide materials is reported. Three iron–cobalt complexes with Fe/Co ratios of 1:1, 1:2, and 2:1 were synthesized by several methods using both solid-state and solution reactions. On the basis of nearly quantitative reaction yields, elemental analyses, and comparison of metal–oxygen bonds with those in homometallic analogues, heterometallic compounds were formulated as [Fe III (acac) 3 ][Co II (hfac) 2 ] (1), [Co II (hfac) 2 ][Fe III (acac) 3 ][Co II (hfac) 2 ] (2), and [Fe II (hfac) 2 ][Fe III (acac) 3 ][Co II (hfac) 2 ] (3). In the above heteroleptic complexes, the Lewis acidic, coordinatively unsaturated CoII/FeII centers chelated by two hexafluoroacetylacetonate (hfac) ligands maintain bridging interactions with oxygen atoms of acetylacetonate (acac) groups that chelate the neighboring Fe III metal ion. Preliminary assignment of Fe and Co positions/oxidation states in 1–3 drawn from X-ray structural investigation was corroborated by a number of complementary techniques. Single-crystal resonant synchrotron diffraction and neutron diffraction experiments unambiguously confirmed the location of Fe and Co sites in the molecules of dinuclear (1) and trinuclear (2) complexes, respectively. Direct analysis in real time mass spectrometry revealed the presence of Fe III - and Co II -based fragments in the gas phase upon evaporation of precursors 1 and 2 as well as of Fe III , Fe II , and Co II species for complex 3. Theoretical investigation of two possible “valent isomers”, [Fe II I(acac) 3 ][Co II (hfac) 2 ] (1) and [Co III (acac) 3 ][Fe II (hfac) 2 ] (1'), provided an additional support for the metal site/oxidation state assignment giving a preference of 6.48 kcal/mol for the experimentally observed molecule 1. Magnetic susceptibility measurements data are in agreement with the presence of high-spin FeIII and CoII magnetic centers with weak anti-ferromagnetic coupling between those in molecules of 1 and 2. Highly volatile heterometallic complexes 1–3 were found to act as effective single-source precursors for the low-temperature preparation of iron–cobalt spinel oxides Fe x Co 3–x O 4 known as important materials for diverse energy-related applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

MaDaTS: Managing Data on Tiered Storage for Scientific Workflows

Scientific workflows are processing large amounts of data through complex simulation and analysis tasks. Meanwhile, the need to minimize I/O costs on next generation systems and the evolution of new technologies (NVRAMs, SSDs etc.) is resulting in deeper storage hierarchies on High Performance Computing (HPC) systems. A multi-tiered storage hierarchy introduces complexities in workflow and data management. There is need for simple and flexible data abstractions that can allow users to seamlessly manage workflow data and tasks on HPC systems with multiple storage tiers. MaDaTS (Managing Data on Tiered Storage for Scientific Workflows) provides an API and a command-line tool that allows users to manage their workflows and data on tiered storage (Ghoshal & Ramakrishnan (2017)).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools

The rapid development of computational approaches for predicting the structures of T cell receptors (TCRs) and TCR-peptide-major histocompatibility (TCR-pMHC) complexes, accelerated by AI breakthroughs such as AlphaFold, has made it feasible to calculate these structures with increasing accuracy. Although these tools show great potential, their relative accuracy and limitations remain unclear due to the lack of standardized benchmarks. Here, we systematically evaluate seven tools for predicting isolated TCR structures together with six tools for predicting TCR-pMHC complex structures. The methods include homology-based approaches, general prediction tools using AlphaFold, TCR-specific tools derived from AlphaFold2, and the newly developed tFold-TCR model. The evaluation uses a post-training data set comprising 40 αβ TCRs and 27 TCR-pMHC complexes (21 Class I and 6 Class II). Model accuracy is assessed at global, local, and interface levels using a variety of metrics. We find that each tool offers distinct advantages in various aspects of its predictions. AlphaFold2, AlphaFold3, and tFold-TCR excel in overall accuracy of TCR structure prediction, and TCRmodel2 and AlphaFold2 perform well in overall accuracy of TCR-pMHC structure prediction. However, TCR-specific tools derived from AlphaFold2 show lower accuracy in the framework region than both homology-based methods and general-purpose tools such as AlphaFold, and challenges remain for all in modeling CDR3 loops, docking orientations, TCR-peptide interfaces, and Class II MHC-peptide interfaces. Furthermore, these findings will guide researchers in selecting appropriate tools, emphasize the importance of using multiple evaluation metrics to assess model performance, and offer suggestions for improving TCR and TCR-pMHC structure prediction tools.

Chemical structure↗
DOE OSTI2016

A multiscale asymptotic analysis of time evolution equations on the complex plane

Using an appropriate norm on the space of entire functions, we extend to the complex plane the renormalization group method as developed by Bricmont et al. The method is based upon a multiscale approach that allows for a detailed description of the long time asymptotics of solutions to initial value problems. The time evolution equation considered here arises in the study of iterations of the block spin renormalization group transformation for the hierarchical N-vector model. We show that, for initial conditions belonging to a certain Fréchet space of entire functions of exponential type, the asymptotics is universal in the sense that it is dictated by the fixed point of a certain operator acting on the space of initial conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Vibrational analysis of methyl cation—Rare gas atom complexes: CH + 3 —Rg (Rg = He, Ne, Ar, Kr)

The vibrational spectra of simple CH + 3 —Rg (Rg = He, Ne, Ar, Kr) complexes have been studied by vibrational configuration interaction theory relying on multidimensional potential energy surfaces (PESs) obtained from explicitly correlated coupled cluster calculations, CCSD(T)-F12a. In agreement with experimental results, the series of rare gas atoms leads to rather unsystematic results and indicates huge zero point vibrational energy effects for the helium complex. In order to study these sensitive complexes more consistently, we also introduce configuration averaged vibrational self-consistent field theory, which is a generalization of standard vibrational self-consistent field theory to several configurations. The vibrational spectra of the complexes are compared to that of the methyl cation, for which corrections due to scalar-relativistic effects, high-order coupled-cluster terms, e.g., quadruple excitations, and core-valence correlation have explicitly been accounted for. The occurrence of tunneling splittings for the vibrational ground-state of CH + 3 —He has been investigated on the basis of semiclassical instanton theory. Furthermore these calculations and a direct comparison of the energy profiles along the intrinsic reaction coordinates with that of the hydronium cation, H 3 O + , suggest that tunneling effects for vibrationally excited states should be very small.

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

Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm

GPU performance of the lattice Boltzmann method (LBM) depends heavily on memory access patterns. When implemented with GPUs on complex domains, typically, geometric data is accessed indirectly and lattice data is accessed lexicographically. Although there are a variety of other options, no study has examined the relative efficacy between them. Here, we examine a suite of memory access schemes via empirical testing and performance modeling. We find strong evidence that semi-direct is often better suited than the more common indirect addressing, providing increased computational speed and reducing memory consumption. For the layout, we find that the Collected Structure of Arrays (CSoA) and bundling layouts outperform the common Structure of Array layout; on V100 and P100 devices, CSoA consistently outperforms bundling, however the relationship is more complicated on K40 devices. When compared to state-of-the-art practices, our recommendations lead to speedups of 10–40 percent and reduce memory consumption up to 17 percent. Using performance modeling and computational experimentation, we determine the mechanisms behind the accelerations. We demonstrate that our results hold across multiple GPUs on two leadership class systems, and present the first near-optimal strong results for LBM with arterial geometries run on GPUs.

42 ENGINEERING↗