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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Surprising Stability of Cubane under Extreme Pressure

The chemical stability of solid cubane under high-pressure was examined with in situ Raman spectroscopy and synchrotron powder X-ray diffraction (PXRD) in a diamond anvil cell (DAC) up to 60 GPa. The Raman modes associated with solid cubane were assigned by comparing experimental data with calculations based on density functional perturbation theory, and low-frequency lattice modes are reported for the first time. Here, the equation of state of solid cubane derived from the PXRD measurements taken during compression gives a bulk modulus of 14.5(2) GPa. In contrast with previous work and chemical intuition, PXRD and Raman data indicate that solid cubane exhibits anomalously large stability under extreme pressure, despite its immensely strained 90° C–C–C bond angles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

FY2017 status report: Model 9975 O-ring fixture long-term leak performance

A series of experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the Model 9975 shipping package has been ongoing since 2004 at the Savannah River National Laboratory. One approach has been to periodically evaluate the leak performance of O-rings being aged in mock-up 9975 Primary Containment Vessels (PCVs) at elevated temperature. Other methods such as compression-stress relaxation (CSR) tests and field surveillance are also on-going to evaluate O-ring behavior. Seventy tests using PCV mock-ups with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 ºF. They were leak-tested initially and have been tested periodically to determine if they continue to meet the leak-tightness criterion defined in ANSI standard N14.5-97. Due to material substitution, a smaller test matrix with fourteen additional tests was initiated in 2008 with GLT-S O-rings heated to temperatures ranging from 200 to 400 ºF. Leak test failures have been experienced in all of the GLT O-ring fixtures aging at 350 ºF and higher temperatures, and in 8 fixtures aging at 300 ºF. The 300 °F GLT O-ring fixtures failed after 2.8 to 5.7 years at temperature. The remaining GLT O-ring fixtures aging at 300 ºF were retired from testing following more than 5 years at temperature without failure. No failures have yet been observed in GLT O-ring fixtures aging at 200 ºF for 9 to 10.5 years, or in GLT O-ring fixtures aging at 270 ºF for 5.7 years. These aging temperatures bound O-ring temperatures anticipated during normal storage in K-Area Complex (KAC). Leak test failures have been experienced in all of the GLT-S O-ring fixtures aging at 300 ºF and above. No failures have yet been observed in GLT-S O-ring fixtures aging at 200 and 250 ºF for 6.9 to 7.5 years. Data from the O-ring fixtures are generally consistent with results from compression stress relaxation testing, and provide confidence in the predictive models based on those results. However, uncertainty still exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in KAC. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicates margin remains for O-rings still in service. Aging and periodic leak testing will continue for the remaining PCV fixtures.

42 ENGINEERING↗
DOE OSTI2015

Kinetic Alfvén waves and particle response associated with a shock-induced, global ULF perturbation of the terrestrial magnetosphere

On 2 October 2013, the arrival of an interplanetary shock compressed the Earth's magnetosphere and triggered a global ULF (ultra low frequency) oscillation. Furthermore, the Van Allen Probe B spacecraft observed this large-amplitude ULF wave in situ with both magnetic and electric field data. Broadband waves up to approximately 100 Hz were observed in conjunction with, and modulated by, this ULF wave. Detailed analysis of fields and particle data reveals that these broadband waves are Doppler-shifted kinetic Alfvén waves. This event then suggests that magnetospheric compression by interplanetary shocks can induce abrupt generation of kinetic Alfvén waves over large portions of the inner magnetosphere, potentially driving previously unconsidered wave-particle interactions throughout the inner magnetosphere during the initial response of the magnetosphere to shock impacts.

58 GEOSCIENCES↗
DOE OSTI2025

Modeling a Sodium Heat Pipe Experiment at SPHERE Using Sockeye

The Single Primary Heat Extraction and Rejection Emulator (SPHERE) facility at Idaho Na- tional Laboratory was recently utilized to generate data for the startup and steady operation of a high-performance, sodium heat pipe over the course of 1000 hours, as a test of detrimental, long-term effects of heat pipe operation. The setup consists of a single, sodium heat pipe enclosed in a stainless-steel vacuum chamber, heated radiatively via a cylindrical ceramic fiber heater configuration and cooled via a water-cooled calorimeter. Measurements include temperatures at several axial locations along the outer surface of the heat pipe, the power provided to the heaters, and the heat removal rate of the calorimeter. In this work, this data is utilized to validate heat pipe models in the heat pipe application Sockeye, which is based upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Sockeye provides various heat pipe models at an engineering scale appropriate for the multiphysics simulation of microreactors, which may feature several hundred heat pipes. This work details models of this experiment in SPHERE using various heat pipe models with Sockeye, including heat conduction-based models and compressible flow models of the heat pipe interior. These models are compared to the experimental data to assess the accuracy of several aspects of heat pipe modeling, including frozen startup, the effect of non-condensable gases, and the coupling of the heat pipe to its environment.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
DOE OSTI2017

Nonlinear Feature Extraction and Energy Dissipation of Foam/Metal Interfaces

The physical mechanisms of energy dissipation in foam to metal interfaces must be understood in order to develop predictive models of systems with foam packaging common to many aerospace and aeronautical applications. Experimental data was obtained from hardware termed Ministack, which has large, unbonded interfaces held under compressive preload. This setup has a solid aluminum mass placed into two foam cups which are then inserted into an aluminum can and fastened with a known preload. Ministack was tested on a shaker using upward sine sweep base acceleration excitations to estimate the linearized natural frequency and energy dissipation of the first axial mode. The experimental system was disassembled and reassembled before each series of tests in order to observe the effects of the assembly to assembly variability on the dynamics. Additionally, Ministack was subjected to upward and downward sweeps to gain some understanding of the nonlinearities. Finally, Ministack was tested using a transient input, and the ring down was analyzed to find the effective stiffness and damping. There are some important findings in the measured data: there is significant assembly to assembly variability, the order in which the sine sweeps are performed influence s the dynamic response, and the system exhibits nontrivial damping and stiffness nonlinearities that must be accounted for in modeling efforts .

42 ENGINEERING↗
DOE OSTI2017

An iterative forward analysis technique to determine the equation of state of dynamically compressed materials

Here, we developed an iterative forward analysis (IFA) technique with the ability to use hydrocode simulations as a fitting function for analysis of dynamic compression experiments. The IFA method optimizes over parameterized quantities in the hydrocode simulations, breaking the degeneracy of contributions to the measured material response. Velocity profiles from synthetic data generated using a hydrocode simulation are analyzed as a first-order validation of the technique. We also analyze multiple magnetically driven ramp compression experiments on copper and compare with more conventional techniques. Excellent agreement is obtained in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The Stellar decomposition: A compact representation for simplicial complexes and beyond

Here, we introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex’s vertices and cells such that each region has sufficient information to locally reconstruct the star of its vertices, i.e., the cells incident in the region’s vertices. Stellar decompositions are general in that they can compactly represent and efficiently traverse arbitrary complexes with a manifold or non-manifold domain. They are scalable to complexes in high dimension and of large size, and they enable users to easily construct tailored application-dependent data structures using a fraction of the memory required by a corresponding global topological data structure on the complex. As a concrete realization of this model for spatially embedded complexes, we introduce the Stellar tree, which combines a nested spatial tree with a simple tuning parameter to control the number of vertices in a region. Stellar trees exploit the complex’s spatial locality by reordering vertex and cell indices according to the spatial decomposition and by compressing sequential ranges of indices. Stellar trees are competitive with state-of-the-art topological data structures for manifold simplicial complexes and offer significant improvements for cell complexes and non-manifold simplicial complexes. We conclude with a high-level description of several mesh processing and analysis applications that utilize Stellar trees to process large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
DOE OSTI2024

Shock equation of state experiments in MgO up to 1.5 TPa and the effects of optical depth on temperature determination

Laser-driven shock compression enables an experimental study of phase transitions at unprecedented pressures and temperatures. One example is the shock Hugoniot of magnesium oxide (MgO), which crosses the B1–B2-liquid triple point at 400–600 GPa, 10 000–13 000 K (0.86–1.12 eV). MgO is a major component within the mantles of terrestrial planets and has long been a focus of high-pressure research. Here, we combine time-resolved velocimetry and pyrometry measurements with a decaying shock platform to obtain pressure–temperature data on MgO from 300 to 1500 GPa and 9000 to 50 000 K. Pressure–temperature–density Hugoniot data are reported at 1500 GPa. These data represent the near-instantaneous response of an MgO [100] single crystal to shock compression. We report on a prominent temperature anomaly between 400 and 460 GPa, in general agreement with previous shock studies, and draw comparison with equation-of-state models. We provide a detailed analysis of the decaying shock compression platform, including a treatment of a pressure-dependent optical depth near the shock front. We show that if the optical depth of the shocked material is larger than 1 μm, treating the shock front as an optically thick gray body will lead to a noticeable overestimation of the shock temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High temperature irradiation induced creep in Ag nanopillars measured via in situ transmission electron microscopy

Irradiation induced creep (IIC) rates are measured in compression on Ag nanopillar (square) beams in the sink-limited regime. The IIC rate increases linearly with stress at lower stresses, i.e. below ≈2/3 the high temperature yield stress and parabolically with pillar width, L, for L less than ≈300 nm. Here, the data are obtained by combining in situ transmission electron imaging with simultaneous ion irradiation, laser heating, and nanopillar compression. Results in the larger width regime are consistent with prior literature.

36 MATERIALS SCIENCE↗
DOE OSTI2015

High-pressure crystallography and compression behavior of the alkali-scandium-germanate end-members LiScGe{sub 2}O{sub 6} and NaScGe{sub 2}O{sub 6}

Synthetic single-crystal samples of the monoclinic pyroxene-type compounds LiScGe{sub 2}O{sub 6} and NaScGe{sub 2}O{sub 6} have been investigated by means of in-situ high-pressure Raman spectroscopy and X-ray diffraction techniques. Crystal-structure investigations at hydrostatic high-pressure conditions were carried out in addition to 10{sup −4} GPa measurements using the diamond-anvil cell technique up to ∼9.5 GPa. Both samples, LiScGe{sub 2}O{sub 6} (space group P2{sub 1}/c, a=9.9999(8) Å, b=9.1040(2) Å, c=5.4610(2) Å, β=109.240(2)° at 10{sup −4} GPa) and NaScGe{sub 2}O{sub 6} (space group C2/c, a=10.1678(5) Å, b=9.1583(5) Å, c=5.5672(3) Å, β=107.257(3)° at 10{sup −4} GPa), did not undergo any compression-induced change of symmetry as confirmed by single-crystal diffraction patterns. Series of high-pressure Raman spectra confirm the absence of any symmetry-related structural phase transition with band positions shifting in a smooth fashion on increasing pressure. High-precision lattice parameters, as determined from X-ray diffraction profile analyzes, were used to monitor both the compressibilities of lattice directions and the evolution of the unit-cell volume with pressure. The experimental data was fitted using a third-order Birch–Murnaghan equation-of-state approach and parameterized fits yield V{sub 0}=469.60(11) Å{sup 3}, K{sub 0}=85.6(1.3) GPa and K′=5.9(4) for LiScGe{sub 2}O{sub 6} and V{sub 0}=495.95(19) Å{sup 3}, K{sub 0}=79(3) GPa and K′=3.9(1.1) for NaScGe{sub 2}O{sub 6}. The systematic comparison of volume properties and compression behavior shows that both pyroxene-type compounds follow established trend lines with similar slopes in comparing volumes versus bulk moduli, and confirm that the position of trend lines in this systematics describing variations with M1 critically depend on the type of M2 and T cations, independent on the space-group symmetry. - Graphical abstract: Polyhedral model of the LiScGe{sub 2}O{sub 6} crystal structure at 9.51 GPa. Red and blue: crystallographic distinctive germanium-tetrahedral chains; Green: scandium-octahedral chains; Purple: lithium atoms. - Highlights: • High-quality high-pressure data of previously uninvestigated germanate compounds. • Results confirmed through complementing sXRD with Raman spectroscopy. • Comparison and relation of high-pressure pyroxene-type compounds.

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

Physicochemical properties of the Portland cement-based mortar exposed to deep seafloor conditions at a depth of 1680 m

Achieving breakthroughs in marine technologies requires the development of infrastructures submerged in deep-sea environments, whose physicochemical effects on cement-based materials considerably differ from those of shallow seas. However, very few studies focused on the cement-based materials subjected to deep-sea conditions. This work investigates the changes in the compressive strength and phase composition of the cement mortar kept on the seafloor with a depth of 1680 m for 608 d. The mortar specimens salvaged from the seafloor exhibited severe visible damages, including softened mashy structures and significantly decreased compressive strengths. The obtained X-ray diffraction, scanning electron microscopy, and nuclear magnetic resonance data revealed that the dissolution of portlandite, decalcification of calcium (alumino) silicate hydrate, and formation of brucite, magnesium (alumino) silicate hydrate, a hydrotalcite-like phase, thaumasite, and ettringite likely contributed to the disintegration of mortar, which could be further accelerated by the low temperature of the deep-sea environment.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Measurements of continuous mix evolution in a high energy density shear flow

We report on the novel integration of streaked radiography into a counter-flowing High Energy Density (HED) shear environment that continually measures a growing mix layer of Al separating two low-density CH foams. Measurements of the mix width allow us to validate compressible turbulence models and with streaked imaging, make this possible with a minimal number of experiments on large laser facilities. In this paper, we describe how the HED counter-flowing shear layer is created and diagnosed with streaked radiography. We then compare the streaked data to previous two-dimensional, single frame radiography and radiation hydrodynamic simulations of the experiment with inline compressible turbulent mix models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Abstract For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to explain relationships in data. Powerful new algorithms can enable computers to learn physics by observing images and videos. Inspired by this idea, instead of training machine learning models using physical quantities, we used images, that is, pixel information. For this work, and as a proof of concept, the physics of interest are wind-driven spatial patterns. These phenomena include features in Aeolian dunes and volcanic ash deposition, wildfire smoke, and air pollution plumes. We use computer model simulations of spatial deposition patterns to approximate images from a hypothetical imaging device whose outputs are red, green, and blue (RGB) color images with channel values ranging from 0 to 255. In this paper, we explore deep convolutional neural network-based autoencoders to exploit relationships in wind-driven spatial patterns, which commonly occur in geosciences, and reduce their dimensionality. Reducing the data dimension size with an encoder enables training deep, fully connected neural network models linking geographic and meteorological scalar input quantities to the encoded space. Once this is achieved, full spatial patterns are reconstructed using the decoder. We demonstrate this approach on images of spatial deposition from a pollution source, where the encoder compresses the dimensionality to 0.02% of the original size, and the full predictive model performance on test data achieves a normalized root mean squared error of 8%, a figure of merit in space of 94% and a precision-recall area under the curve of 0.93.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

Scientific data analytics in high-performance computing environments has been evolving along with the advancement of computing capabilities. With the onset of exascale computing, the increasing gap between compute performance and I/O bandwidth has rendered the traditional post-simulation processing a tedious process. Despite the challenges due to increased data production, there exists an opportunity to benefit from "cheap" computing power to perform query-driven exploration and visualization during simulation time. To accelerate such analyses, applications traditionally augment, post-simulation, raw data with large indexes, which are then repeatedly utilized for data exploration. However, the generation of current state-of-the-art indexes involves a compute- and memory-intensive processing, thus rendering them inapplicable in an in situ context. In this paper we propose DIRAQ, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. DIRAQ's effective core-local, precision-based encoding approach incorporates an embedded compressed index that is 3---6 $$\times $$ ? smaller than current state-of-the-art indexing schemes. Its data-aware index adjustmentation improves performance of group-level index layout creation by up to 35 % and reduces the size of the generated index by up to 27 %. Moreover, DIRAQ's in network index merging strategy enables the creation of aggregated indexes that speed up spatial-context query responses by up to $$10\times $$ 10 ? versus alternative techniques. DIRAQ's topology-, data-, and memory-aware aggregation strategy results in efficient I/O and yields overall end-to-end encoding and I/O time that is less than that required to write the raw data with MPI collective I/O.

Computer Science↗
DOE OSTI2022

Squeezing Out Interfacial Solvation: The Role of Hydrogen-Bonding in the Structural and Orientational Freedom of Molecular Self-Assembly

We report bioinspired membrane molecules with improved physical properties and enhanced stability can serve as functional models for conventional lipid or amphiphilic species. Importantly, these molecules can also provide new insights into emergent phenomena that manifest during self-assembly at interfaces. Here, we elucidate the structural response and mechanistic steps underlying the self-assembly of the amphiphilic, charged oligodimethylsiloxane imidazolium cation (ODMS-MIM+) at the air–aqueous interface using Langmuir trough methods with coincident surface-specific vibrational sum-frequency generation (SFG) spectroscopy. We find evidence for a new compression-induced desolvation step that precedes commonly known disordered-to-ordered phase transitions to form nanoscopic assemblies. The experimental data was supported by atomistic molecular dynamics (MD) simulations to provide a detailed mechanistic picture underlying the assembly and the role of water in these phase transitions. The sensitivity of the hydrophobic ODMS tail conformations to compression-owing to distinct water–ODMS interactions and tail–tail solvation properties-offers new strategies for the design of interfaces that can be further used to develop soft-matter electronics and low-dimensional materials using physical and chemical controls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modeling Framework for the Assessment of a Sustainable Hydrogen Production and Supply Chain Network in California

The cost-effective and sustainable deployment of hydrogen supply and demand networks, especially in large economic regions like California, can be challenging considering the spatial-temporal availability and variability of the different actors across the network such as production processes, distribution modes, and end-users. In this presentation, we will provide an overview and demonstration of a modeling framework used to assess the environmental, economic, and human health impacts of plausible hydrogen production and supply chain networks in California. Scenarios focus on green hydrogen production pathways using water electrolysis and biomass gasification. End-use applications included in the model are transit, medium and heavy-duty trucking, port authorities, and power and aviation companies that currently consume natural gas, diesel, and aviation fuel for their day-to-day operation. Representative locations for hydrogen production and end-use are based on recent projections of the hydrogen economy in California. All mass and energy flows, as well as estimated emissions, are based on H2A process model designs and projections of technology performance, literature review, and LBNL process, economic and life cycle modeling, and not on company data for the sake of this presentation. Human health impacts are included following methodologies developed for the University of California Irvine HyDeal project. Life cycle phases associated with hydrogen production include feedstock preparation (water and biomass), energy production and consumption (renewable, grid, and combination of renewable and grid electricity), maintenance (chemical utilization in electrolysis and natural gas combustion in gasification), carbon sequestration, hydrogen storage (compression and liquefaction), and distribution (truck and pipeline). We apply the framework utilizing California specific emission factors, financial data, and human health damages and explore the impact of network characteristics on results. Example variations include: the inclusion of policy incentives or not, different representations of the electricity grid and source, electrolysis versus gasification versus combinations of both for production, liquefaction versus compression based on producer capacity cutoffs, transportation truck versus pipeline based on existing infrastructure, and ultimate end use. Comparison of these different scenarios can help inform future projects by demonstrating the trade-offs among environmental, economic, and human health impacts. This model, automated in R, is a starting platform upon which new analysis, modeling capabilities, locations, and emission factors can be rapidly tested and integrated.

Zaki, Mohammed Tamim↗