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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SUNDIALS time integrators for exascale applications with many independent systems of ordinary differential equations

Many complex systems can be accurately modeled as a set of coupled time-dependent partial differential equations (PDEs). However, solving such equations can be prohibitively expensive, easily taxing the world’s largest supercomputers. One pragmatic strategy for attacking such problems is to split the PDEs into components that can more easily be solved in isolation. This operator splitting approach is used ubiquitously across scientific domains, and in many cases leads to a set of ordinary differential equations (ODEs) that need to be solved as part of a larger “outer-loop” time-stepping approach. The SUNDIALS library provides a plethora of robust time integration algorithms for solving ODEs, and the U.S. Department of Energy Exascale Computing Project (ECP) has supported its extension to applications on exascale-capable computing hardware. In this paper, we highlight some SUNDIALS capabilities and its deployment in combustion and cosmology application codes (Pele and Nyx, respectively) where operator splitting gives rise to numerous, small ODE systems that must be solved concurrently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling

PeleLMeX simulates chemically reacting low Mach number flows with block-structured adaptive mesh refinement (AMR). The code is built upon the AMReX library, which provides the underlying data structures and tools to manage and operate on them across massively parallel computing architectures. PeleLMeX algorithmic features are inherited from its predecessor PeleLM but key improvements allow representation of more complex physical processes. Together with its compressible flow counterpart PeleC, the thermo-chemistry library PelePhysics and the multi-physics library PeleMP, it forms the Pele suite of open-source reactive flow simulation codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

TREAT Cask Stand Drawings for Unlimited Use

This report contains drawings of the HFEF-15 Cask stand in the TREAT Reactor Building (MFC-720) and the Cask Stand Tower on the south wall of the TREAT High Bay. Public release is sought so these can be sent to DOD-SCO and their contracted companies looking at options for fueling the PELE reactor prior to demonstration in the DOME or elsewhere at INL.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Low-Dimensional Manifold via Co-Kurtosis PCA in Combustion Modeling

For multi-scale multi-physics applications e.g., the turbulent combustion code Pele, robust and accurate dimensionality reduction is crucial to solving problems at exascale and beyond. A recently developed technique, Co-Kurtosis based Principal Component Analysis (CoK-PCA) which leverages principal vectors of co-kurtosis, is a promising alternative to traditional PCA for complex chemical systems. To improve the effectiveness of this approach, we employ Artificial Neural Networks for reconstructing thermo-chemical scalars, species production rates, and overall heat release rates corresponding to the full state space. Our focus is on bolstering confidence in this deep learning based non-linear reconstruction through Uncertainty Quantification (UQ) and Sensitivity Analysis (SA). UQ involves quantifying uncertainties in inputs and outputs, while SA identifies influential inputs. One of the noteworthy challenges is the computational expense inherent in both endeavors. To address this, we employ the Monte Carlo methods to effectively quantify and propagate uncertainties in our reduced spaces while managing computational demands. Our research carries profound implications not only for the realm of combustion modeling but also for a broader audience in UQ. By showcasing the reliability and robustness of CoK-PCA in dimensionality reduction and deep learning predictions, we empower researchers and decision-makers to navigate complex combustion systems with greater confidence.

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

Plan for the Development and Application of a Risk Assessment Approach for Transportation Package Approval of a Transportable Nuclear Power Plant for Maritime Shipment (Rev. 1)

This plan proposes a strategy for licensing a transportable nuclear power plant, containing its unirradiated and irradiated fuel, as a transportation package for maritime transport using a probabilistic risk assessment framework in order to meet the regulatory requirements of 10 CFR Part 71. It is anticipated that initially, the deterministic transportation package licensing approach will be challenging due to the functional requirements of the transportable nuclear power plant. As such, a partial exemption request from the U.S. Nuclear Regulatory Commission coupled with applied compensatory measures are anticipated in support of providing equivalent safety to the public, worker, and environment. A plan is outlined as to how this would be demonstrated and a pathway is primarily outlined using the accompanying low accident rates which in turn support very low probabilities of release for a maritime application. Wherever possible, the proposed plan is supported by actual accident (casualty) data. Additional supporting information regarding a highway transportation probabilistic risk assessment in support of the Project Pele demonstration reactor that is currently under development is also referenced and discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

DNS of Flame Stabilization Dynamics of a Swirl-Stabilized Spray Burner Using Sustainable Aviation Fuels

Concern for emission reduction has motivated the development of new cost-effective alternative sustainable aviation fuels (SAFs). Drop-in SAFs with blends of the certified and the alternative fuels are beneficial because they do not require engine modifications for use in current aviation engines. Combustion characteristics are of particular concern when comparing a new fuel with Jet-A. Lean blow-off and flame stabilization have been identified to be governed by the fuel propensity to autoignition, i.e. derived cetane number. However, fundamental investigation is required to identify the impact of derived cetane number on the combustion mode of flame stabilization in a realistic combustor. The combustion mode has also a direct impact on turbulent combustion modeling closures. DNS simulations are performed in the low-Mach solver of the Pele Suite called PeleLMeX. Lagrangian multi-phase modeling is used to capture the liquid spray injection of Jet-A (reference fuel) and C1 as a representative of a low cetane number SAF. Adaptive Mesh Refinement (AMR) is used to enable a more efficient simulation of a more realistic domain size and embedded boundary treatment is used to model a bluff-body geometry. Local extinction and edge flame propagation were observed for both fuels. The edge flame propagation mode was quantified in terms of a Damkohler number defined as the ratio between progress variable reaction rate and its diffusive flux. Initial analysis suggests that a mixed mode combustion occurs for the edge flame propagation, with flame propagation assisted by ignition and autoignition co-existing for both Jet-A and C1 flames. The analysis of the extinction region shows a larger progress variable for Jet-A which can further increase the local displacement speed and present a faster reignition of the stoichiometric mixture fraction.

adaptive mesh refinement↗
DOE OSTI2024

Förster Resonance Energy Transfer and Enhanced Emission in Cs 4 PbBr 6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications

Encapsulating Cs 4 PbBr 6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs 4 PbBr 6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs 4 PbBr 6 pseudo-spherical quantum dots is quenched and is dominated with Pb 2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs 4 PbBr 6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb 2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs 4 PbBr 6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Global color and albedo variations on Io

The present Voyager imaging data multispectral mosaics of Io include global mosaics from each of the Voyager 1 and 2 data sets and a high-resolution mosaic of the region centered on the Ra Patera volcano. The constancy of the disk-integrated color and albedo of Io over recent decades despite volcanic activity may be due to the regular occurrence of large Pele-type plumes with relatively dark, red deposits. Io's intrinsic spectral variability involves continuous variation among three major spectral end members. Attention is given to the mapping of the data into five spectral units for the purposes of comparison with laboratory measurements of Io surface material candidates.

Mcewen, Alfred S.↗
NASA NTRS1988

The global distribution, abundance, and stability of SO2 on Io

Voyager multispectral mosaics, earth-observed spectra, and photometric characterizations have been used to model and globally map the SO2 distribution and abundances, the bolometric hemispheric albedos, and the passive surface temperatures on Io. The SO2 is noted to be concentrated in the bright equatorial band, while being deficient in the region defined by Pele-type volcanic eruptions and the polar regions. The brightest, locally coldest areas correspond to SO2-rich regions, although many small patches occur elsewhere. These results are found to support the regional cold-trapping model for the surface and atmospheric SO2 of Fanale et al. (1982).

Mcewen, Alfred S.↗
NASA NTRS1994

Detection of the SO2 atmosphere on Io with the Hubble Space Telescope

Observations of the trailing hemisphere of Io made with the Faint Object Spectrograph of the Hubble Space Telescope (HST) in March 1992 have resulted in the first detection of atmospheric SO2 absorption bands in the ultraviolet. These observations represent only the third positive means of detection of what is widely believed to be Io's primary atmospheric constituent. Below approximately 2130 A the geometric albedo of the satellite is dominated by SO2 gas absorption band signatures, which have been analyzed using models that include the effects of optical thickness, temperature, and spatial distribution. The disk-intergrated HST data cannot resolve the spatial distribution, but it is possible to define basic properties and set constraints on the atmosphere at the time of the observations. Hemispheric atmospheres with average column density N = 6 - 10 x 10(exp 15)/sq sm and T(gas) = 110 - 500 K fit the data, with preference for temperatures of approximately 200 - 250 K. Better fits are found as the atmosphere is spatially confined, with a limit of approximately 8% hemispheric areal coverage and N approximately equal to 3 x 10(exp 17)/sq cm with colder 110 - 250 K temepratures. A dense (N greater than or equal to 10(exp 16)/sq cm), localized component of SO2 gas, such as that possibly associated with active volcanoes, can generate the observed spectral constrast only when the atmosphere is cold (110 K) and an extended component such as Pele is included. The combination of a dense, localized atmosphere with a tenuous component (N less than 10(exp 16)/sq cm, either patchy or extended) also fits the data. In all cases the best fit models imply a disk-averaged column density larger than exospheric but approximately 10 - 30 times less than the previous upper limit from near-UV observations.

Ballester, G. E.↗
NASA NTRS2003

Galileo PPR at Io: High Resolution Scans Taken in Conjunction with SSA and NIMS Data

The Galileo Photopolarimeter-Radiometer (PPR), when used in the radiometry mode which is most often used at Io, is a long-wavelength infrared single-aperture photometer. It is sensitive to temperatures from about 60 to several hundred K, and is thus useful for studying the volcanoes and background temperatures on Io. PPR can take raster scan images when it is the primary instrument being used (these data were discussed last year, see Rathbun et al., 2002). It can also take data in ride-along mode in conjunction with another remote sensing instrument (either SSI or NIMS) producing one-dimensional temperature scans. The best data of this type were taken during the close approach flybys during orbits I24, I25, I27, I31, I32, and I33 and include measurements of the volcanoes Pele, Prometheus, Pillan, Zamama, Tvashtar, Daedalus, Amarani, Gish Bar, Isum, Emakong, Tupan, and Tohil.

Rathbun, J. A.↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Io, with a Dash of Titan

The session "Io, with a Dash of Titan" contained the following reports:A Deep Lava Channel on Io ; Volcanic Activity at Tvashtar Catena, Io; Characterization of Activity at Loki from Galileo and Ground-based Observations; Active and Passive Lava Resurfacing Processes on Io: A Comparative Study of Loki Patera and Prometheus; Loki Patera as the Surface of a Magma Sea; Lava Lakes on Io: New Perspectives from Modeling; Global Distribution of Active Volcanism on Io as Known at the End of the Galileo Mission Relationships Between Paterae, Mountains, and Hotspots on Io from a Global Database; Lithospheric Recycling on Io: The Role of Delamination; Building Mountains on Io: Implications for Io s Lithosphere ; The Effect of Large Melt Fraction on the Deformation Behavior of Peridotite: Implications for the Rheology of Io s Mantle; Matching Various Observations of Io with DSMC Modeling: Plume, Plume Shadow, Sodium Field Around Pele; and How Does Titan Retain a Finite Orbital Eccentricity?

Source record↗
NASA NTRS2004

Volcanic Activity at Tvashtar Catena, Io

Tvashtar Catena (63 N, 120 W) is one of the most interesting features on Io. This chain of large paterae (caldera-like depressions) has exhibited highly variable volcanic activity in a series of observations. Tvashtar is the type example of a style of volcanism seen only at high latitudes, with short-lived Pele-type plumes and short-lived by intense thermal events. Evidence for a hot spot at Tvashtar was first detected in an eclipse observation in April 1997 (orbit G7) by the Solid State Imager (SSI) on the Galileo Spacecraft. Tvashtar was originally targeted for observation at higher resolution in the close flyby in November 1999 (I25) because of its interesting large-scale topography. There are relatively few but generally larger paterae at high latitudes on Io. I25 images revealed a 25 km long, 1-2 km high lava curtain via a pattern of saturation and bleeding in the CCD image, which requires very high temperatures.

Milazzo, M. P.↗
NASA NTRS2005

Classification of Volcanic Eruptions on Io and Earth Using Low-Resolution Remote Sensing Data

Two bodies in the Solar System exhibit high-temperature active volcanism: Earth and Io. While there are important differences in the eruptions on Earth and Io, in low-spatial-resolution data (corresponding to the bulk of available and foreseeable data of Io), similar styles of effusive and explosive volcanism yield similar thermal flux densities. For example, a square metre of an active pahoehoe flow on Io looks very similar to a square metre of an active pahoehoe flow on Earth. If, from observed thermal emission as a function of wavelength and change in thermal emission with time, the eruption style of an ionian volcano can be constrained, estimates of volumetric fluxes can be made and compared with terrestrial volcanoes using techniques derived for analysing terrestrial remotely-sensed data. In this way we find that ionian volcanoes fundamentally differ from their terrestrial counterparts only in areal extent, with Io volcanoes covering larger areas, with higher volumetric flux. Io outbursts eruptions have enormous implied volumetric fluxes, and may scale with terrestrial flood basalt eruptions. Even with the low-spatial resolution data available it is possible to sometimes constrain and classify eruption style both on Io and Earth from the integrated thermal emission spectrum. Plotting 2 and 5 m fluxes reveals the evolution of individual eruptions of different styles, as well as the relative intensity of eruptions, allowing comparison to be made from individual eruptions on both planets. Analyses like this can be used for interpretation of low-resolution data until the next mission to the jovian system. For a number of Io volcanoes (including Pele, Prometheus, Amirani, Zamama, Culann, Tohil and Tvashtar) we do have high/moderate resolution imagery to aid determination of eruption mode from analyses based only on low spatial-resolution data.

Davies, A. G.↗
DOE OSTI2024

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗
DOE OSTI2023

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.

Power grid analysis, GPU↗
DOE OSTI2025

Breaking the Linear Scaling Relations for the Oxygen Reduction Reaction with a Dual‐Atom Catalyst Composed of a MnFe‐Porphyrrole Aerogel

Bimetallic catalysts offer enhanced catalytic performance through synergistic interactions between the two metals, allowing them to break the linear scaling relations and reach high electrocatalytic activity. This study presents bimetallic aerogel-based catalyst synthesized as a covalent, three-dimensional framework containing neighboring iron and manganese sites. The aerogel structure provides a high surface area and porosity, facilitating an ultra-high active site density and efficient mass transport. The MnFe porphyrrole's unique structure is obtained by alternately linking Mn-porphyrin and Fe-corrole complexes. It exhibited outstanding performance with an onset potential of 0.99 V RHE . Comparative studies with a free-base Fe porphyrrole catalyst (E onset 0.97 V RHE ) revealed that while Mn incorporation led to only a slight improvement in half-cell performance, it resulted in significantly enhanced performance in anion exchange membrane fuel cell. The MnFe catalyst achieved an OCV of 0.97 V and a peak power density of 0.27 W cm −2 , outperforming the free-base Fe counterpart. Using density functional theory calculations, we show that the higher ORR activity of MnFe-porphyrrole is due to charge transfer between Mn and Fe atoms, which is absent in the reference free-base Fe-porphyrrole. These findings underscore the advantages of bimetallic catalysts in improving ORR activity and fuel cell efficiency by leveraging synergistic effects.

Aerogel↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗