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Results for “Spatial Partitioning”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Spatial and temporal baseline of perfluorooctanesulfonic acid retained in sediment core samples from Puget Sound, Washington, USA

Per- and poly-fluorinated alkyl substances (PFAS) are a group of highly persistent synthetic chemicals utilized in many industrial and consumer products, and — most significantly toward introduction to the marine environment — in fire-fighting foams. Recently, PFAS have been linked to adverse health effects, prompting the need to understand transport and fate. Puget Sound’s main basin, hosting densely populated urban and industrial areas, is known to be contaminated with various persistent organic pollutants and provides a central focus for ecosystem monitoring. Perfluorooctanesulfonic acid, a manufactured PFAS and biodegradation product, partitions to marine sediments and thus can be used as a primary indicator toward regulatory efforts. The current study offers a spatial and temporal analysis of the Puget Sound from cores collected adjacent, Tacoma and Seattle, WA, as well as cores from central Hood Canal and Carr Inlet.

Per- and poly-fluorinated alkyl substances (PFAS),↗
DOE OSTI2023

Laboratory Study of Collisionless Magnetic Reconnection

A concise review is given on the past two decades’ results from laboratory experiments on collisionless magnetic reconnection in direct relation with space measurements, especially by the Magnetospheric Multiscale (MMS) mission. Highlights include spatial structures of electromagnetic fields in ion and electron diffusion regions as a function of upstream symmetry and guide field strength, energy conversion and partitioning from magnetic field to ions and electrons including particle acceleration, electrostatic and electromagnetic kinetic plasma waves with various wavelengths, and plasmoid-mediated multiscale reconnection. Combined with the progress in theoretical, numerical, and observational studies, the physics foundation of fast reconnection in collisionless plasmas has been largely established, at least within the parameter ranges and spatial scales that were studied. Immediate and long-term future opportunities based on multiscale experiments and space missions supported by exascale computation are discussed, including dissipation by kinetic plasma waves, particle heating and acceleration, and multiscale physics across fluid and kinetic scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗
DOE OSTI2021

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Fine scale transitions of the microbiota and metabolome along the gastrointestinal tract of herbivorous fishes

Abstract Background Gut microorganisms aid in the digestion of food by providing exogenous metabolic pathways to break down organic compounds. An integration of longitudinal microbial and chemical data is necessary to illuminate how gut microorganisms supplement the energetic and nutritional requirements of animals. Although mammalian gut systems are well-studied in this capacity, the role of microbes in the breakdown and utilization of recalcitrant marine macroalgae in herbivorous fish is relatively understudied and an emerging priority for bioproduct extraction. Here we use a comprehensive survey of the marine herbivorous fish gut microbial ecosystem via parallel 16S rRNA gene amplicon profiling (microbiota) and untargeted tandem mass spectrometry (metabolomes) to demonstrate consistent transitions among 8 gut subsections across five fish of the genus of Kyphosus . Results Integration of microbial phylogenetic and chemical diversity data reveals that microbial communities and metabolomes covaried and differentiated continuously from stomach to hindgut, with the midgut containing multiple distinct and previously uncharacterized microenvironments and a distinct hindgut community dominated by obligate anaerobes. This differentiation was driven primarily by anaerobic gut endosymbionts of the classes Bacteroidia and Clostridia changing in concert with bile acids, small peptides, and phospholipids: bile acid deconjugation associated with early midgut microbiota, small peptide production associated with midgut microbiota, and phospholipid production associated with hindgut microbiota. Conclusions The combination of microbial and untargeted metabolomic data at high spatial resolution provides a new view of the diverse fish gut microenvironment and serves as a foundation to understand functional partitioning of microbial activities that contribute to the digestion of complex macroalgae in herbivorous marine fish.

Sparagon, Wesley J. (ORCID:0000000296274174)↗
DOE OSTI2023

Multiscale architecture for fast optical addressing and control of large-scale qubit arrays

This paper presents a technique for rapid site-selective control of the quantum state of particles in a large array using the combination of a fast deflector (e.g., an acousto-optic deflector) and a relatively slow spatial light modulator (SLM). The use of SLMs for site-selective quantum state manipulation has been limited due to slow transition times that prevent rapid, consecutive quantum gates. By partitioning the SLM into multiple segments and using a fast deflector to transition between them, it is possible to substantially reduce the average time increment between scanner transitions by increasing the number of gates that can be performed for a single SLM full-frame setting. We analyzed the performance of this device in two different configurations: In configuration 1, each SLM segment addresses the full qubit array; in configuration 2, each SLM segment addresses a subarray and an additional fast deflector positions that subarray with respect to the full qubit array. With these hybrid scanners, we calculated qubit addressing rates that are tens to hundreds of times faster than using an SLM alone.

Graham, T. M.↗
DOE OSTI2022

Spatially Averaged Ice Contents of Ice-Wedge Polygon Cross-Sections to 3-m Depth, July 2013, Utqiagvik, Alaska

This dataset contains spatially averaged estimates of ice content (volume percent) for two-dimensional cross-sectional profiles (from trough center to trough center to a depth of 3 meters) of low- and flat-centered ice-wedge polygons (three of each type) located near Utqiagvik, Alaska. A combination of soil pits, trenches, and cores were used to describe, sample, and map the cross-section stratigraphy of soil horizons and ice wedges for each polygon at 6 depth intervals. Observed soil horizons were assigned to four types with increasing amounts of organic components (mineral, mineral/organic, organic/mineral, and organic). The average ice contents of each soil horizon type below the permafrost boundary and wedge ice were weighted by their cross-sectional area fractions to calculate spatially averaged estimates of ice content for each polygon. In the active layer, spatially averaged estimates of volumetric water contents were similarly determined and reported here as “ice” content to enable estimates of the soil’s structurally competent porosity and excess ice in permafrost layers. In this dataset, the file AK13_ice_contents.csv includes cross-sectional area fractions and spatially averaged ice contents for soil layers and horizon types at the six depth intervals. The file AK13_permafrost_ice_fractions.csv contains the calculated partitioning of ice contents into pore ice and excess ice fractions for the three permafrost-dominated depth intervals. In addition, there is a data dictionary file for each of these data files and a file-level metadata file. These data were generated by the Department of Energy’s Soil Carbon Response to Environmental Change Scientific Focus Area and were used as inputs to model simulations examining the consequences of thaw-affected subsidence and microtopography change on active layer thickness of low-relief polygonal tundra landscapes in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Anion Selectivities in Zwitterion Grafted Nanopores: Effect of Zwitterion Architecture

The separation of ions of similar charge is a crucial challenge in many applications, from water treatment to precious metal recovery. Membranes with cross-linked zwitterionic amphiphilic copolymer (ZAC-X) selective layers, which feature self-assembled, zwitterion-lined nanodomains for permeation, offer unique permselectivity between monovalent anions (e.g. $\mathrm{Cl^-}$/$\mathrm{F^-}$). This has motivated studies on the mechanisms of transport and selectivity in this family of materials. In this study, we conducted molecular dynamics simulations of aqueous salt solutions within zwitterion-functionalized nanopores to elucidate the influence of dipole orientation of the ZI ligands on anion diffusivities, partitioning, and permeabilities. Here, our model compares systems with contrasting ZI organization: surface-cation-anion ($\mathrm{S\text{-}ZI^{+}\text{-}ZI^{-}}$, Motif A) and surface-anion-cation ($\mathrm{S\text{-}ZI^{-}\text{-}ZI^{+}}$, Motif B). Our results reveal that Motif A exhibits less pronounced ion pairing due to a spatial separation in the radial profiles of cations and anions. Motif B demonstrates prominent ion pairing for smaller anions owing to their overlap with cation distributions. Further, our potential of mean force profiles reveal that anion partitioning increases with anion size in both ligand motifs, whereas Motif B exhibits significantly higher partitioning selectivity towards larger anions compared to Motif A. Our results for ion diffusivities show that the self-diffusivities of both anions and cations are lower for Motif B compared to Motif A. Such trends in anion partitioning and diffusivities can be explained by differences in the interactions and steric hindrance experienced by the anionic species in Motifs A and B. Finally, our results for anion permselectivity, obtained by combining partitioning and diffusivity, indicate that partitioning trends dominate over diffusivity trends. Consequently, anion permeability increases with anion size, and ligand Motif B yields much higher permselectivity towards larger anions compared to ligand Motif A.

anions↗
DOE OSTI2024

Processes Associated with Boundary Layer Cloud Ice Phase Precipitation in the High Southern Latitudes (Final Technical Report)

This is a final technical report for DOE Award No. DE-SC0018995. Using data collected during the MARCUS deployment of the 2nd ARM mobile facility, this project sought to address the following scientific questions: 1. What are the conditions that govern phase partitioning in supercooled boundary layer clouds over the high latitude Southern Oceans? 2. To what extent are supercooled mixed phase clouds responsible for the high cloud fractions over the Southern Ocean and do these mixed phase clouds contribute to the model biases in absorbed shortwave radiation? 3. Can the cloud properties and phase partitioning over the Southern Ocean be linked to the underlying aerosol environment? 4. How do the aerosol properties at the surface vary spatially and seasonally over the high latitude Southern Ocean and what processes control these features? 5. How well defined are the atmospheric compositional boundaries between Southern Ocean marine, Antarctic free tropospheric, and Antarctic surface airmasses, and how does this influence the chemistry and physics of the Southern Ocean atmosphere? In this project we published three peer review journal articles that address these questions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Observationally constrained analysis on the distribution of fine- and coarse-mode nitrate in global models

Nitrate plays an important role in the Earth system and air quality. A key challenge in simulating the life cycle of nitrate aerosol in global models is to accurately represent mass size distribution of nitrate aerosol. In this study, we evaluate the performance of the Energy Exascale Earth System Model version 2 (E3SMv2) and the Community Earth System Model version 2 (CESM2), along with Aerosol Comparisons between Observations and Models (AeroCom) phase III models, in simulating spatial distribution of fine-mode nitrate, the mass size distribution of fine- and coarse-mode nitrate, and the gas–aerosol partitioning between nitric acid gas and nitrate, using long-term ground-based observations and measurements from multiple aircraft campaigns. We find that most models underestimate the annual mean PM 2.5 (particulate matter with diameter less than 2.5 µm) nitrate surface concentration averaged over all sites. The observed nitrate PM 2.5 / PM 10 and PM 1 / PM 4 ratios are influenced by the relative contribution of fine sulfate or organic particles and coarse dust or sea salt particles. Overall, the ground-based observations give an annual mean surface nitrate PM 2.5 / PM 10 ratio of 0.7. Most models underestimate the annual mean PM 2.5 / PM 10 ratio in all regions. There are large spreads in the modeled nitrate PM 1 / PM 4 ratios, which span the full range from 0 to 1. Most models underestimate the surface molar ratio of nitrate to total inorganic nitrate averaged across all sites. Our study indicates the importance of gas–aerosol partition parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.

Nitrate↗
DOE OSTI2025

Galerkin formulation of path integrals in lattice field theory

We present a mathematical framework for Galerkin formulations of path integrals in lattice field theory. The framework is based on using the degrees of freedom (DOFs) associated to a Galerkin discretization as the fundamental lattice variables. We formulate standard concepts in lattice field theory, such as the partition function and correlation functions, in terms of the DOFs. For example, using continuous finite element spaces, we show that the two-point spatial correlation function can be defined between any two points on the domain (as opposed to at just lattice sites) and furthermore, this two-point function satisfies a weak propagator (or Green’s function) identity, in analogy to the continuum case, as well as a convergence estimate obtained from the standard finite element techniques. Furthermore, this framework leads naturally to higher-order formulations of lattice field theories by considering higher-order finite element spaces for the Galerkin discretization. We consider analytical and numerical examples of scalar field theory to investigate how increasing the order of piecewise polynomial finite element spaces affect the approximation of lattice observables. Finally, we sketch an outline of this Galerkin framework in the context of gauge field theories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fracture Network Prediction Using Physics-based Machine Learning Algorithms

In recent years, systematic CO2 injection into geological reservoirs across the U.S. has gained traction as a strategy to mitigate greenhouse gas emissions. This approach necessitates precise monitoring to ensure secure containment, minimize risks, and optimize storage management. Our study leverages machine learning (ML) techniques to advance the understanding of CO2 injection processes, focusing on the Illinois Basin. Over a three-year injection period, we analyzed microseismic data, identifying 19 temporal intervals with significant bottom-hole pressure changes. By partitioning microseismic events into these intervals and estimating b-values, we revealed over 100 clusters of events related to fracture initiation or reactivation. Advanced spatial analysis highlighted horizontally-oriented fractures along the NNW-SSE axis. This quantification of fracture networks informs dynamic injection scheduling, work-over strategies, and risk assessments, enhancing carbon capture, utilization, and storage (CCUS) operations. Additionally, our methodology offers valuable insights for oil and gas operations and geothermal development, supporting fracture-based monitoring and risk mitigation.

Kumar, Abhash↗
DOE OSTI2023

Systems and methods for modeling water quality

A system, method, device and computer-readable medium for creating an ensemble model of water quality. The ensemble model is generated by determining a set of optimal component models for spectral regions of a body of water, and combining the optimal models. The optimal models can be based on remote sensing data, including satellite imagery. A K-fold partition approach or a global approach can be used to determine the optimal component models, and the optimal component models can be combined through spectral space partition rules to generate an ensemble model of water quality. The ensemble model not only has improved water quality prediction ability, but also has strong spatial and temporal extensibility. The spatial and temporal extensibility of the ensemble model is fundamentally important and desirable for long-term and large-scale remote sensing monitoring and assessment of water quality.

Liu, Hongxing↗
DOE OSTI2025

Global Simulations of Phase State and Equilibration Time Scales of Secondary Organic Aerosols with GEOS-Chem

The phase state of secondary organic aerosols (SOA) can range from liquid through amorphous semisolid to glassy solid, which is important to consider as it influences various multiphase processes including SOA formation and partitioning, multiphase chemistry, and cloud activation. In this study, we simulate the glass transition temperature and viscosity of SOA over the globe using the global chemical transport model, GEOS-Chem. The simulated spatial distributions show that SOA at the surface exist as liquid over equatorial regions and oceans, semisolid in the midlatitude continental regions, and glassy solid over lands with low relative humidity. The predicted SOA viscosities are mostly consistent with the available measurements. In the free troposphere, SOA particles are mostly predicted to be semisolid at 850 hPa and glassy solid at 500 hPa, except over tropical regions including Amazonia, where SOA are predicted to be low viscous. Phase state also exhibits seasonal variation with a higher frequency of semisolid and solid particles in winter compared to warmer seasons. We calculate equilibration time scales of SOA partitioning (τ eq ) and effective mass accommodation coefficient (α eff ), indicating that τ eq is shorter than the chemical time step of GEOS-Chem of 20 min and αeff is close to unity for most locations at the surface level, supporting the application of equilibrium SOA partitioning. However, τ eq is prolonged and α eff is lowered over drylands and most regions in the upper troposphere, suggesting that kinetically limited growth would need to be considered for these regions in future large-scale model studies.

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

Localization of proteins involved in the biogenesis and repair of the photosynthetic apparatus to thylakoid subdomains in Arabidopsis

Abstract Thylakoid membranes in chloroplasts and cyanobacteria harbor the multisubunit protein complexes that catalyze the light reactions of photosynthesis. In plant chloroplasts, the thylakoid membrane system comprises a highly organized network with several subcompartments that differ in composition and morphology: grana stacks, unstacked stromal lamellae, and grana margins at the interface between stacked and unstacked regions. The localization of components of the photosynthetic apparatus among these subcompartments has been well characterized. However, less is known about the localization of proteins involved in the biogenesis and repair of the photosynthetic apparatus, the partitioning of proteins between two recently resolved components of the traditional margin fraction (refined margins and curvature), and the effects of light on these features. In this study, we analyzed the partitioning of numerous thylakoid biogenesis and repair factors among grana, curvature, refined margin, and stromal lamellae fractions of Arabidopsis thylakoid membranes, comparing the results from illuminated and dark‐adapted plants. Several proteins previously shown to localize to a margin fraction partitioned in varying ways among the resolved curvature and refined margin fractions. For example, the ALB3 insertase and FtsH protease involved in photosystem II (PSII) repair were concentrated in the refined margin fraction, whereas TAT translocon subunits and proteins involved in early steps in photosystem assembly were concentrated in the curvature fraction. By contrast, two photosystem assembly factors that facilitate late assembly steps were depleted from the curvature fraction. The enrichment of the PSII subunit OE23/PsbP in the curvature fraction set it apart from other PSII subunits, supporting the previous conjecture that OE23/PsbP assists in PSII biogenesis and/or repair. The PSII assembly factor PAM68 partitioned differently among thylakoid fractions from dark‐adapted plants and illuminated plants and was the only analyzed protein to convincingly do so. These results demonstrate an unanticipated spatial heterogeneity of photosystem biogenesis and repair functions in thylakoid membranes and reveal the curvature fraction to be a focal point of early photosystem biogenesis.

Chotewutmontri, Prakitchai↗
DOE OSTI2023

Application of a Distributed Element Roughness Model to Additively Manufactured Internal Cooling Channels

Abstract Design for cooling effectiveness in turbine blades relies on accurate models for dynamic losses and heat transfer of internal cooling passages. Metal additive manufacturing (AM) has expanded the design space for these configurations, but can give rise to large-scale roughness features. The range of roughness length scales in these systems makes morphology resolved computational fluid dynamics (CFD) impractical. However, volumetric roughness models can be leveraged, as they have computational costs orders of magnitude lower. In this work, a discrete element roughness model (DERM), based on the double-averaged Navier–Stokes equations, is presented and applied to additively manufactured rough channels, representative of gas turbine blade cooling passages. Unique to this formulation of DERM is a generalized sheltering-based treatment of drag, a two-layer model for spatially averaged Reynolds stresses, and explicit treatment of dispersion. Six different AM rough surface channel configurations are studied, with roughness trough to peak sizes ranging from 15% to 60% nominal channel passage half-width, and the roughness Reynolds number ranges from Rek = 60 to 300. DERM predictions for spatially and temporally averaged mean flow quantities are compared to previously reported direct numerical simulation results. Good agreement in the mean velocity profiles, stress balances, and drag partitions are observed. While DERM models are typically calibrated to specific deterministic roughness morphologies at comparatively small roughness Reynolds numbers, the present more generalized DERM formulation has wider applicability. Here, it is demonstrated that the model can accommodate random roughness of large scale, typical of AM.

Engineering↗
DOE OSTI2021

Illuminating the North Korean nuclear explosion test in 2017 using remote infrasound observations

North Korea conducted its sixth underground nuclear explosion test (mb 6.3) on 2017 September 3. The underground explosion produced substantial low-frequency atmospheric waves, which were detected by infrasound arrays located up to a distance of 566 km. These infrasound waves are formed by the conversion of seismic energy to acoustic energy across the lithosphere–atmosphere interface. While infrasound records at regional distances produce estimates of ground motion amplitude over spatially extended regions covering about 26 500 km 2 , 3-D full seismo-acoustic simulations within the lithosphere and atmosphere provide quantitative information about seismo-acoustic energy partitioning. Our results demonstrate the capability of remote infrasound observations combined with 3-D propagation modelling to further develop discrimination methods for underground sources. These results contribute to enhance the confidence of source identification and characterization in nuclear test monitoring research, which is essential for the enforcement of the Comprehensive Nuclear-Test-Ban Treaty.

58 GEOSCIENCES↗