Search NASA⌕ Search

SEARCH · Search NASA

Results for “expanded analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85

2.3.4.104 - Lignin Conversion to Sustainable Aviation Fuel Blendstocks

The Lignin Conversion to Sustainable Aviation Fuel Blendstocks (LigSAF) project focuses on the conversion of lignin-rich streams to deoxygenated aromatic and cycloalkane blendstocks in the jet fuel range. This work is done in close collaboration with the BETO-funded Lignin-First Biorefinery Development project and industrial scale-up partners, and the work is closely guided by analysis to develop cost-effective and sustainable routes to produce lignin-based SAF blendstocks. To date, we have demonstrated the continuous catalytic conversion of a lignin oil from poplar to deoxygenated aromatic products at -85% C-mol yield. This hydrodeoxygenation process uses a stable, earth-abundant catalyst and requires no solvent. We have also established a baseline process model and associated techno-economic analysis and life cycle assessment that together demonstrate the potential to achieve cost parity with fossil carbon-based jet fuel at -70% reduction in greenhouse gas emissions. Current work is focused on expanding the slate of feedstocks for hydrodeoxygenation to include lignin oils from softwoods, agricultural residues, and grasses as well as from hydrolysis lignin substrates from biochemical conversion and pulp-and-paper processes. We are also undertaking catalyst development efforts to tune the reaction selectivity from aromatic compounds to cycloalkanes. Lastly, we are investigating reaction engineering strategies to slurry solids for hydrodeoxygenation reactions.

aromatics↗

Efficient Modeling of Floating Wind Arrays Including Current Loads and Seabed Bathymetry: Preprint

Capabilities for modeling the effects of seabed bathymetry and current drag loads on a floating wind farm are now available in an open-source model for quasi-static analysis. In this model, mooring lines and dynamic cables are represented by a quasistatic solver that can quickly represent complex mooring/cabling arrangements and arrays of floating bodies. To account for seabed bathymetry, we expand the model to include a surface mesh that captures changes in water depth over a rectangular grid. We formulate modifications to the catenary equations that capture a mooring line's profile and tensions when contacting a slope seabed. To account for current drag loads on mooring lines and dynamic cables, we formulate a novel technique that rotates the reference frame so that the vector sum of the the weight and the current force are used in the catenary equations, while accounting for the seabed orientation. To complete the system, current drag loads on floating substructures are handled by inclusion of strip-theory drag calculations. These new capabilities are verified by comparing with results from the established offshore dynamics models MoorDyn and OrcaFlex in equivalent steady-state scenarios. The results show very good agreement for both sloped seabeds and current loads. With computation times of the quasi-static model typically under one second, the model additions are a useful capability toward rapidly evaluating a floating wind array's response to environmental loads under realistic site conditions.

bathymetry↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Large-scale Structure of the Heliospheric Current Sheets within the Heliosheath Inferred from Voyager 2 Observations

In this paper, we conducted an analysis of the heliospheric current sheets (HCSs) in the heliosheath (HS), utilizing observations by Voyager 2 between 2008 and 2018. Employing rigorous criteria, we identified a total of 34 HCSs that indicate significant changes in magnetic polarity. These occurrences were more prevalent during solar maximum periods when the HCS expanded to higher latitudes, coinciding with the spacecraft positioned at an average latitude of –31° from the solar equator. We determined certain features of the large-scale structures of the identified HCSs. Most importantly, employing two distinct methods indicates that the thickness of the HCSs within the HS ranges from ~0.003 to ~0.4 au with an average thickness of ~0.03 to ~0.1 au, depending on methods of event selection and fitting techniques. This thickness surpasses that known near 1 au or other heliospheric distances. It is also notably thicker than the typical proton inertial length, implying unfavorable conditions for magnetic reconnection. Additionally, our analysis reveals a frequent tilt of HCS planes relative to the solar equatorial plane by a varying angle up to several tens of degrees, likely implying a common occurrence of a warped structure of the HCS within the HS. Longitudinally, the HCS planes closely align with the Parker spiral field direction expected in the HS. Finally, for a large fraction of the identified HCS events, the HCS planes are likely characterized by a rotational discontinuity. These findings are valid within the limits of the 1 hr resolution data used in this study.

79 ASTRONOMY AND ASTROPHYSICS↗

Multidimensional effective field theory analysis for direct detection of dark matter

The scattering of dark matter particles off nuclei in direct detection experiments can be described in terms of a multidimensional effective field theory (EFT). Here a new systematic analysis technique is developed using the EFT approach and Bayesian inference methods to exploit, when possible, the energy-dependent information of the detected events, experimental efficiencies, and backgrounds. Highly dimensional likelihoods are calculated over the mass of the weakly interacting massive particle (WIMP) and multiple EFT coupling coefficients, which can then be used to set limits on these parameters and choose models (EFT operators) that best fit the direct detection data. Expanding the parameter space beyond the standard spin-independent isoscalar cross section and WIMP mass reduces tensions between previously published experiments. Combining these experiments to form a single joint likelihood leads to stronger limits than when each experiment is considered on its own. Simulations using two nonstandard operators ($\mathscr{O}$ 3 and $\mathscr{O}$ 8 ) are used to test the proposed analysis technique in up to five dimensions and demonstrate the importance of using multiple likelihood projections when determining constraints on WIMP mass and EFT coupling coefficients. In particular, this shows that an explicit momentum dependence in dark matter scattering can be identified.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Application of two-dimensional unsteady aerodynamic to a free-tip rotor response analysis

The free-tip rotor utilizes a rotor blade tip which is structurally decoupled from the blade inboard section. The tip is free to pitch about its own pitch axis to respond to the local flow angularity changes. The tip also experiences the heaving motion due to the flapping of the rotor blade. For an airfoil in any pitching and heaving motion which can be expanded into a Fourier series, the lift and moment calculated by Theodoren's theory is simply the linear combination of the lift and moment calculated for each harmonic. These lift and moment are then used to determine the response of the free-tip rotor. A parametric study is performed to determine the effect of mechanical damping, mechanical spring, sweep, friction, and a constant control moment on the free-tip rotor response characteristics and the resulting azimuthal lift distributions. The results showed that the free-tip has the capability to suppress the oscillatory lift distribution around the azimuth and to eliminate a significant negative life peak on the advancing tip. This result agrees with the result of the previous analysis based on the steady aerodynamics.

Yates, L.↗

Assessing Fossil Fuel and Feedstock Use in the U.S. Plastics and Rubber Sector: A Supply Chain Analysis

In plastics and rubber manufacturing, fossil fuels are consumed both as an energy source and as feedstocks that are converted to higher-value products. For example, in the manufacture of polyethylene, natural gas is consumed both as a fuel and as a feedstock during ethylene production. In this work, we expand on the U.S. Department of Energy's Bandwidth Study on Energy Use and Potential Energy Savings Opportunities in U.S. Plastics and Rubber Manufacturing, which quantified onsite fuel consumption and the potential for reducing fuel consumption by increasing energy efficiency in the plastics and rubber sector. The bandwidth study did not quantify fuel consumed upstream in the supply chain or as a feedstock; however, both contribute significantly to a plastic's total fossil fuel requirements. The U.S. Energy Information Administration's 2014 Manufacturing Energy Consumption Survey (MECS) estimates that fossil fuels consumed as feedstocks account for approximately 74% of total fossil fuel consumption in the U.S. plastic resin manufacturing sector (NAICS 325211). We employ the Materials Flows through Industry (MFI) supply chain modeling tool, developed at the National Renewable Energy Laboratory (NREL), to quantify process fuel and feedstock requirements within the supply chains of the same 10 categories of plastics and rubber commodities covered in the DOE bandwidth report. From these results, we identify supply chains that will have a high feedstock requirement even when energy efficiency is increased. We then use MFI to analyze several alternative plastics supply chains, including those utilizing biomass feedstocks and/or polyethylene terephthalate (PET) waste upcycling, to determine if these alternatives can potentially reduce both process fuel and feedstock requirements within the supply chains of interest. This presentation will include a case study comparison of supply chain energy consumption for petroleum-derived and bio-derived fiberglass reinforced plastic involving a novel waste PET upcycling technique recently discovered by NREL researchers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Survey of Galileo Plasma Observations in Jupiter's Plasma Sheet

The plasma science (PLS) Instrument on the Galileo spacecraft (orbiting Jupiter from December 1995 to September 2003) measured properties of the ions that were trapped in the magnetic field. The PLS data provide a survey of the plasma properties between approx. 5 and 30 Jupiter radii [R(sub J)] in the equatorial region. We present plasma properties derived via two analysis methods: numerical moments and forward modeling. We find that the density decreases with radial distance by nearly 5 orders of magnitude from approx. 2 to 3000 cm(exp.-3) at 6R(sub j) to approx. 0.05cm(sub -3) at 30 R(sub j). The density profile did not show major changes from orbit to orbit, suggesting that the plasma production and transport remained constant within about a factor of 2. The radial profile of ion temperature increased with distance which implied that contrary to the concept of adiabatic cooling on expansion, the plasma heats up as it expands out from Io's orbit (where TI is approx.60-80 eV) at approx. 6R(sub j) to a few keV at 30R(sub j).There does not seem to be a long-term, systematic variation in ion temperature with either local time or longitude. This latter finding differs from earlier analysis of Galileo PLS data from a selection of orbits. Further examination of all data from all Galileo orbits suggests that System Ill variations are transitory on timescales of weeks, consistent with the modeling of Cassini Ultraviolet Imaging Spectrograph observations. The plasma flow is dominated by azimuthal flow that is between 80% and 100% of corotation out to 25 R(sub j).

Bagenal, Fran↗

Unconventional Spintronics from Chiral Perovskites

Spintronic devices typically employ heterostructures with ferromagnets which break time-reversal symmetry and have non-vanishing magnetization. With the growing class of materials that support spin-polarized carriers, current, and excitations, it is possible to envision emerging spintronic applications that are not limited to magnetoresistance. Here, chiral perovskites with no net magnetization are considered, where the space-inversion and mirror symmetries are broken to induce chiral structure. The known importance of these perovskites is further expanded by the demonstration of the chiral-induced spin selectivity (CISS). However, the generation of the spin-polarized carriers across the interface with these chiral perovskites remains to be fully understood. These first-principles studies for 2D PbBr4-based chiral perovskites provide their electronic structure and an orbital-based symmetry analysis, which allows to establish an effective Hamiltonian to elucidate the underlying origin of their chirality. The same analysis is used for the Edelstein effect, responsible for electrical generation of the nonequilibrium spin polarization in many materials, which in chiral perovskites can be a mechanism contributing to CISS. Furthermore, by examining optical properties of chiral perovskites and the opportunity to use them to realize tunable altermagnets, another class of zero-magnetization spintronic materials, a versatile materials platform is put forth for unconventional spintronics.

14 SOLAR ENERGY↗

Summary of Expansions and Updates in R&D GREET ® 2023

The Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model was developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. R&D GREET is a life cycle analysis (LCA) model, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail), other end-use sectors, and energy systems. Argonne has expanded and updated the model in various areas in R&D GREET 2023. This report provides a summary of the expansions and updates.

33 ADVANCED PROPULSION SYSTEMS↗

Summary of Expansions and Updates in GREET ® 2022

The GREET ® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE) and other federal agencies. GREET is a life cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2022, and this report provides a summary of the release.

25 ENERGY STORAGE↗

Plastic deformation in nanoindentation of tantalum: A new mechanism for prismatic loop formation

Here, the mechanisms of deformation under a nanoindentation in tantalum, chosen as a model body-centered cubic (bcc) metal, are identified and quantified. Molecular dynamics (MD) simulations and indentation experiments are conducted for [1 0 0], [1 1 0] and [1 1 1] normals to surface orientations. The simulated plastic deformation proceeds by the formation of nanotwins, which rapidly evolve into shear dislocation loops. It is shown through a dislocation analysis that an elementary twin (three layers) is energetically favorable for a diameter below ~7 nm, at which point a shear loop comprising a perfect dislocation is formed. MD simulations show that shear loops expand into the material by the advancement of their edge components. Simultaneously with this advancement, screw components of the loop cross-slip and generate a cylindrical surface. When opposite segments approach, they eventually cancel by virtue of the attraction between them, forming a quasi-circular prismatic loop composed of edge dislocation segments. This “lasso”-like mechanism by which a shear loop transitions to a prismatic loop is identified for both [0 0 1] and [1 1 1] indentations. The prismatic loops advance into the material along $\langle$1 1 1$\rangle$ directions, transporting material away from the nucleation site. Analytical calculations supplement MD and experimental observations, and provide a framework for the improved understanding of the evolution of plastic deformation under a nanoindenter. Dislocation densities under the indenter are estimated experimentally (~1.2 × 10 15 m -2 ), by MD (~7 × 10 15 m -2 ) and through an analytical calculation (2.6–19 × 10 15 m -2 ). Considering the assumptions and simplifications, this agreement is considered satisfactory. MD simulations also show expected changes in pile-up symmetry after unloading, compatible with crystal plasticity.

36 MATERIALS SCIENCE↗

Ancestral archaea expanded the genetic code with pyrrolysine

The pyrrolysyl-tRNA synthetase (PylRS) facilitates the cotranslational installation of the 22nd amino acid pyrrolysine. Owing to its tolerance for diverse amino acid substrates, and its orthogonality in multiple organisms, PylRS has emerged as a major route to install noncanonical amino acids into proteins in living cells. Recently, a novel class of PylRS enzymes was identified in a subset of methanogenic archaea. Enzymes within this class (ΔPylSn) lack the N-terminal tRNA-binding domain that is widely conserved amongst PylRS enzymes, yet remain active and orthogonal in bacteria and eukaryotes. In this study, we use biochemical and in vivo UAG-readthrough assays to characterize the aminoacylation efficiency and substrate spectrum of a ΔPylSn class PylRS from the archaeon Candidatus Methanomethylophilus alvus. We show that, compared with the full-length enzyme from Methanosarcina mazei, the Ca. M. alvus PylRS displays reduced aminoacylation efficiency but an expanded amino acid substrate spectrum. To gain insight into the evolution of ΔPylSn enzymes, we performed molecular phylogeny using 156 PylRS and 105 pyrrolysine tRNA (tRNA Pyl ) sequences from diverse archaea and bacteria. This analysis suggests that the PylRS•tRNA Pyl pair diverged before the evolution of the three domains of life, placing an early limit on the evolution of the Pyl-decoding trait. Furthermore, our results document the coevolutionary history of PylRS and tRNA Pyl and reveal the emergence of tRNA Pyl sequences with unique A73 and U73 discriminator bases. The orthogonality of these tRNA Pyl species with the more common G73-containing tRNA Pyl will enable future efforts to engineer PylRS systems for further genetic code expansion.

59 BASIC BIOLOGICAL SCIENCES↗

Transition between protein-like and polymer-like dynamic behavior: Internal friction in unfolded apomyoglobin depends on denaturing conditions

Equilibrium dynamics of different folding intermediates and denatured states is strongly connected to the exploration of the conformational space on the nanosecond time scale and might have implications in understanding protein folding. For the first time, the same protein system apomyoglobin has been investigated using neutron spin-echo spectroscopy in different states: native-like, partially folded (molten globule) and completely unfolded, following two different unfolding paths: using acid or guanidinium chloride (GdmCl). While the internal dynamics of the native-like state can be understood using normal mode analysis based on high resolution structural information of myoglobin, for the unfolded and even for the molten globule states, models from polymer science are employed. The Zimm model accurately describes the slowly-relaxing, expanded GdmCl-denaturated state, ignoring the individuality of the different aminoacid side chain. The dynamics of the acid unfolded and molten globule state are similar in the framework of the Zimm model with internal friction, where the chains still interact and hinder each other: the first Zimm relaxation time is as large as the internal friction time. Transient formation of secondary structure elements in the acid unfolded and presence of α-helices in the molten globule state lead to internal friction to a similar extent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature distribution in a laser-heated diamond anvil cell as described by finite element analysis

Finite element analysis (FEA) is a powerful tool for numerically solving partial differential equations over complex geometries and is thus useful for analyzing heat transport in laser-heated diamond anvil cell (LHDAC) experiments. Our models expand on previously published simulations by calculating the volume-averaged temperatures of both the sample and insulation/pressure media under steady-state heating to determine the thermal pressure of the hot sample. Our goal is to produce an accurate relationship between the measured surface temperature of the absorbing sample and the temperature of the transparent insulating media, which is used to determine thermal pressure but susceptible to steep temperature gradients. We find that in doing so, our FEA models of temperature within the pressure/insulation media can differ from simplified estimates of temperature gradients by more than a factor of 2. We also explore temperature-dependent and temperature-independent thermal conductivity models and find that the volume-averaged temperatures differ by up to a factor of 1.3, forcing the predicted thermal pressures determined to also differ by up to a factor of 1.5 at a temperature of 2000 K at 50 GPa for neon. Higher temperatures exacerbate this difference. We also find that unintentional asymmetric sample insertion and sample heating, which are common in LHDAC experiments, do not have a first-order effect on volume-averaged temperatures. The FEA models, available in both Python and FlexPDE, are versatile across different sample geometries, materials, and heat source laser shapes.

Farah, Frederick↗

CORONAL MAGNETOGRAPHY OF A SIMULATED SOLAR ACTIVE REGION FROM MICROWAVE IMAGING SPECTROPOLARIMETRY

We have simulated the Expanded Owens Valley Solar Array (EOVSA) radio images generated at multiple frequencies from a model solar active region, embedded in a realistic solar disk model, and explored the resulting data cube for different spectral analysis schemes to evaluate the potential for realizing one of EOVSA’s most important scientific goals—coronal magnetography. In this paper, we focus on modeling the gyroresonance and free–free emission from an on-disk solar active region model with realistic complexities in electron density, temperature and magnetic field distribution. We compare the magnetic field parameters extrapolated from the image data cube along each line of sight after folding through the EOVSA instrumental profile with the original (unfolded) parameters used in the model. We find that even the most easily automated, image-based analysis approach (Level-0) provides reasonable quantitative results, although they are affected by systematic effects due to finite sampling in the Fourier (UV) plane. Finally, we note the potential for errors due to misidentified harmonics of the gyrofrequency, and discuss the prospects for applying a more sophisticated spectrally based analysis scheme (Level-1) to resolve the issue in cases where improved UV coverage and spatial resolution are available.

79 ASTRONOMY AND ASTROPHYSICS↗

Striped Data Server for Scalable Parallel Data Analysis

A columnar data representation is known to be an efficient way for data storage, specifically in cases when the analysis is often done based only on a small fragment of the available data structures. A data representation like Apache Parquet is a step forward from a columnar representation, which splits data horizontally to allow for easy parallelization of data analysis. Based on the general idea of columnar data storage, working on the [LDRD Project], we have developed a striped data representation, which, we believe, is better suited to the needs of High Energy Physics data analysis. A traditional columnar approach allows for efficient data analysis of complex structures. While keeping all the benefits of columnar data representations, the striped mechanism goes further by enabling easy parallelization of computations without requiring special hardware. We will present an implementation and some performance characteristics of such a data representation mechanism using a distributed no-SQL database or a local file system, unified under the same API and data representation model. The representation is efficient and at the same time simple so that it allows for a common data model and APIs for wide range of underlying storage mechanisms such as distributed no-SQL databases and local file systems. Striped storage adopts Numpy arrays as its basic data representation format, which makes it easy and efficient to use in Python applications. The Striped Data Server is a web service, which allows to hide the server implementation details from the end user, easily exposes data to WAN users, and allows to utilize well known and developed data caching solutions to further increase data access efficiency. We are considering the Striped Data Server as the core of an enterprise scale data analysis platform for High Energy Physics and similar areas of data processing. As a result, we have been testing this architecture with a 2TB dataset from a CMS dark matter search and plan to expand it to multiple 100 TB or even PB scale. We will present the striped format, Striped Data Server architecture and performance test results.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗