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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrochemically Determined and Structurally Justified Thermochemistry of H atom Transfer on Ti-Oxo Nodes of the Colloidal Metal–Organic Framework Ti-MIL-125

Titanium dioxide (TiO 2 ) has long been employed as (photo)electrodes for reactions relevant to energy storage and renewable energy synthesis. Proton-coupled electron transfer (PCET) reactions with equimolar amounts of protons and electrons at the TiO 2 surface or within the bulk structure lie at the center of these reactions. Because a proton and an electron are thermochemically equivalent to an H-atom, these reactions are essentially H-atom transfer reactions. Thermodynamics of H-atom transfer has a complex dependence on the synthetic protocol and chemical history of the electrode, the reaction medium, and many others; together, these complications preclude the understanding of the H-atom transfer thermochemistry with atomic-level structural knowledge. Herein, we report our success in employing open-circuit potential (E OCP ) measurements to quantitatively determine the H-atom transfer thermochemistry at structurally well-defined Ti-oxo clusters within a colloidally stabilized metal–organic framework (MOFs), Ti-MIL-125. The free energy to transfer H-atom, Ti 3+ O–H bond dissociation free energy (BDFE), was measured to be 68(2) kcal mol -1 . To the best of our understanding, this is the first report on using E OCP measurements to quantify thermochemistry on any MOFs. The proton topology, the structural change upon the redox reaction, and BDFE values were further quantitatively corroborated using computational simulations. Furthermore, comparisons of the E OCP -derived BDFEs of Ti-MIL-125 to similar parameters in the literature suggest that E OCP should be the preferred method for quantitatively accurate BDFE calculations. Here, the reported success in employing E OCP for nanosized Ti- MIL-125 should lay the ground for thermochemical measurements of other colloidal systems, which are otherwise challenging. Implications of these measurements on Ti-MIL-125 as an H-atom acceptor in chemical reactions and comparisons with other MOFs/metal oxides are discussed.

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

Iron transformation mediates phosphate retention across a permafrost thaw gradient

Phosphorus limits primary productivity in many (Sub-)Arctic ecosystems and may constrain biological carbon sequestration. Iron (III) oxides strongly bind phosphate in soils but can dissolve under flooded, reducing conditions induced by permafrost thaw and ground collapse. The ability for iron to regulate phosphate storage and solubility in thawing permafrost landscapes remains unclear. Here, iron-rich sediments containing iron oxides and organic-bound iron were incubated with or without added phosphate in soils along a permafrost thaw gradient to evaluate how iron-phosphate associations respond to thaw-induced redox shifts. Iron oxides partially dissolved and released sorbed phosphate when incubated in soils underlain by degraded permafrost. Iron complexed by organic matter remained stable but provided no phosphate binding capacity. Phosphate addition enhanced iron oxide dissolution and phosphorus concentrations in associated microbial biomass. Our study demonstrates that the capacity for iron oxides to immobilize and retain phosphate in permafrost peatlands decreases with permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Organic carbon content and turnover time in relation to pedogenic iron and aluminum in four temperate forest soils sampled in 2007

Soil organic carbon (SOC) can be stabilized via association with iron (Fe) and aluminum (Al) minerals. Fe and Al can be strong predictors of SOC storage and turnover in soils with relatively high extractable metals content and moderately acidic to circumneutral pH. Here we test whether pedogenic Fe and Al influence SOC content and turnover in soils with low Fe and Al content and acidic pH. In soils from four sites spanning three soil orders, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon. We evaluated the correlations of Fe and Al concentrations, mean annual precipitation (MAP), mean annual temperature (MAT), and pH with SOC content and 14C-based turnover times. We found that poorly crystalline Fe and Al content predicted SOC turnover times (p < 0.0001) consistent with findings of previous studies, while organically-complexed Fe and Al content was a better predictor of SOC concentration (p < 0.0001). Greater site-level MAP (p < 0.0001) and colder site-level MAT (p < 0.0001) were correlated with longer SOC turnover times but were not correlated with SOC content. Our results suggest that poorly crystalline Fe and Al effectively slow the turnover of SOC in these acidic soils, even when their combined content in the soil is less than 2% by mass. However, in the strongly acidic Spodosol, organo-metal complexes tended to be less stable resulting in a more actively cycling mineral-associated SOC pool. We characterized mineralogy and carbon content in soils from four forested sites in the eastern deciduous forest zone that span three soil orders. Using selective chemical dissolution applied to the soil fraction containing mineral-associated carbon, we quantified the amount of Fe and Al in operationally-defined poorly crystalline and organically-complexed phases, and correlated these with previously published SOC content and 14C-based turnover times (McFarlane et al. 2013). This dataset comprises site characterization undertaken in 2007 (.png) and subsequent soil analyses (.csv containing C, Fe, Al, 14C-derived TurnoverTime) concluded in 2010.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Unmanned surface traverses of Mars and Moon: Science objectives, payloads, operations

Science objectives and properties to be measured are outlined for long surface traverse missions on Mars and the Moon, with remotely-controlled roving vehicles. A series of candidate rover payloads is proposed for each planet, varying in weight, cost, purpose, and development needed. The smallest weighs 35 kg; the largest almost 300 kg. A high degree of internal control will be needed on the Mars rover, including the ability to carry out complex science sequences. Decision-making by humans in the Mars mission includes supervisory control of rover operations and selection of features and samples of geological and biological interest. For the lunar mission, less control on the rover and more on earth is appropriate. Science portions of the rover mission profile are outlined, with timelines and mileage breakdowns. Operational problem areas for Mars include control, communications, data storage, night operations, and the mission operations system. For the moon, science data storage on the rover would be unnecessary and control much simpler.

Jaffe, L. D.↗
NASA NTRS1975

Subjective evaluation with FAA criteria: A multidimensional scaling approach

Perceived orderliness in the ground tracks of five A/C during their simulated flights was studied. Dynamically developing ground tracks for five A/C from 21 separate runs were reproduced from computer storage and displayed on CRTS to professional pilots and controllers for their evaluations and preferences under several criteria. The ground tracks were developed in 20 seconds as opposed to the 5 minutes of simulated flight using speedup techniques for display. Metric and nonmetric multidimensional scaling techniques are being used to analyze the subjective responses in an effort to: (1) determine the meaningfulness of basing decisions on such complex subjective criteria; (2) compare pilot/controller perceptual spaces; (3) determine the dimensionality of the subjects' perceptual spaces; and thereby (4) determine objective measures suitable for comparing alternative traffic management simulations.

Kreifeldt, J. G.↗
NASA NTRS1995

Nanosatellite Power System Considerations

The capability to build complex electronic functions into compact packages is opening the path to miniature satellites on the order of 1 kg mass, 10 cm across, packed with the computing processors, motion controllers, measurement sensors, and communications hardware necessary for operation. Power generation will be from short strings of silicon or gallium arsenide-based solar photovoltaic cells with the array power maximized by a peak power tracker (PPT). Energy storage will utilize a low voltage battery with nickel cadmium or lithium ion cells as the most likely selections for rechargeables and lithium (MnO2-Li) primary batteries for one shot short missions.

Robyn, M.↗
NASA NTRS2000

Airbreathing Propulsion System Analysis Using Multithreaded Parallel Processing

In this paper, parallel processing is used to analyze the mixing, and combustion behavior of hypersonic flow. Preliminary work for a sonic transverse hydrogen jet injected from a slot into a Mach 4 airstream in a two-dimensional duct combustor has been completed [Moon and Chung, 1996]. Our aim is to extend this work to three-dimensional domain using multithreaded domain decomposition parallel processing based on the flowfield-dependent variation theory. Numerical simulations of chemically reacting flows are difficult because of the strong interactions between the turbulent hydrodynamic and chemical processes. The algorithm must provide an accurate representation of the flowfield, since unphysical flowfield calculations will lead to the faulty loss or creation of species mass fraction, or even premature ignition, which in turn alters the flowfield information. Another difficulty arises from the disparity in time scales between the flowfield and chemical reactions, which may require the use of finite rate chemistry. The situations are more complex when there is a disparity in length scales involved in turbulence. In order to cope with these complicated physical phenomena, it is our plan to utilize the flowfield-dependent variation theory mentioned above, facilitated by large eddy simulation. Undoubtedly, the proposed computation requires the most sophisticated computational strategies. The multithreaded domain decomposition parallel processing will be necessary in order to reduce both computational time and storage. Without special treatments involved in computer engineering, our attempt to analyze the airbreathing combustion appears to be difficult, if not impossible.

Schunk, Richard Gregory↗
DOE OSTI2023

EDX Spatial: Leveraging cloud and hybrid data management resources for spatial data

In the last few years, the National Energy Technology Laboratory has started leveraging cloud-hosted services for hosting spatial data collections published on the Energy Data eXchange (EDX). Using cloud-hosted storage and compute options offers multiple benefits for visualization and tool development through utilization of spatial data resources. The transition from on-premises services to cloud-hosted services has enabled a few key features: increased accessibility of large derivative datasets, dynamic integration of external authoritative data resources directly from outside entities through representational state transfer application programming interfaces (REST API), and the ability to produce complex mapping applications, dashboards, and online maps. As a result of the shift, NETL has launched EDX Spatial, a platform that leverages on-premises resources combined with cloud compute capabilities to enable enhanced online mapping interfaces and optimize data access. In addition, a unified workflow for handling the public release of spatial data products through EDX has been developed, including standardization of data hosting practices, metadata, symbology, and application elements. This poster reviews the opportunity of leveraging cloud-hosted and hybrid data management solutions for spatial data, and discusses the benefits and lessons learned while leveraging these services through the data repository EDX.

Morkner, Paige↗
DOE OSTI2023

Knowledge-driven design of solid-electrolyte interphases on lithium metal via multiscale modelling

Abstract Due to its high energy density, lithium metal is a promising electrode for future energy storage. However, its practical capacity, cyclability and safety heavily depend on controlling its reactivity in contact with liquid electrolytes, which leads to the formation of a solid electrolyte interphase (SEI). In particular, there is a lack of fundamental mechanistic understanding of how the electrolyte composition impacts the SEI formation and its governing processes. Here, we present an in-depth model-based analysis of the initial SEI formation on lithium metal in a carbonate-based electrolyte. Thereby we reach for significantly larger length and time scales than comparable molecular dynamic studies. Our multiscale kinetic Monte Carlo/continuum model shows a layered, mostly inorganic SEI consisting of LiF on top of Li 2 CO 3 and Li after 1 µs. Its formation is traced back to a complex interplay of various electrolyte and salt decomposition processes. We further reveal that low local Li + concentrations result in a more mosaic-like, partly organic SEI and that a faster passivation of the lithium metal surface can be achieved by increasing the salt concentration. Based on this we suggest design strategies for SEI on lithium metal and make an important step towards knowledge-driven SEI engineering.

25 ENERGY STORAGE↗
DOE OSTI2020

Expanding the potential of redox carriers for flow battery applications

Here, using theoretical modeling to guide our approach, substituents were selected to improve the negative and positive potentials associated with a representative metal-based redox carrier, a phenyl spaced nickel bispicolinamide complex, [Ni(bpb)], 1. To broaden the cell potential, electron donating groups were selected and installed on the pyridyl moieties, [Ni(bpb-(NMe 2 ) 2 )], 2, while electron withdrawing groups were incorporated on the phenyl linker, [Ni(bpb-R)] (R = –F, –CF 3 , and –NO 2 ), 3–5. Our model predicts an increase of ~300 mV and ~500 mV for the first and second negative waves of Ni(bpb-NMe 2 ), 2, and up to ~330 mV and ~210 mV increase to the first and second positive waves in 3–5. The modeled complexes were synthesized in good yields using a modification of the literature procedure. Due to limited solubility, the differential pulse voltammetry was measured on complexes 2–5 using a drop cast technique. Comparison of the observed and predicted potentials is discussed in acetonitrile (MeCN) and dimethylformamide (DMF) solvents.

25 ENERGY STORAGE↗
DOE OSTI2023

Fast Charge Induced Phase Evolution and Element Contribution of Nickel-Rich Layered Cathode for Lithium-Ion Batteries

In nickel-rich layered cathode materials, three transition metals (TM = Ni, Co and Mn) play critical roles in Li storage performance. However, rate-dependent phase evolution and elemental contribution of nickel-rich cathode materials are not well understood, but very important for further design and development of these cathodes in high-power applications. Here, the rate-dependent phase evolution and elemental contribution of LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathode are investigated thoroughly by using time-resolved synchrotron-based in situ X-ray diffraction and absorption techniques. The increase of Ni content in NMC532 has been found to be the main cause of the complex structural changes, resulting in distortion of TM-O 6 octahedron and strong static vibration between TM and O coordination. It is revealed that the fast charge (10C and 30C) of NMC532 leads to intermediate Li-poor phases, shrinking of H2 phase region, and prolonged O1 phase. During high-rate charging, Co is oxidized easily in low voltage region, while Ni mainly dominates charge compensation in high voltage region. It is found that delithiation-induced local structure distortion transfers from Ni to Co sites in fast kinetic process. In conclusion, these findings provide in-depth understanding for the fast charge behavior of Ni-rich layered cathode materials and help to guide further development of advanced high-power lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Influence of the molecular weight and size distribution of PSS on mixed ionic-electronic transport in PEDOT:PSS

The commercially available polyelectrolyte complex poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is ubiquitous in organic and hybrid electronics. As such, it has often been used as a benchmark material for fundamental studies and the development of new electronic devices. Yet, most studies on PEDOT:PSS have focused on its electronic conductivity in dry environments, with less consideration given to its ion transport, coupled ionic-electronic transport, and charge storage properties in aqueous environments. These properties are essential for applications in bioelectronics (sensors, actuators), charge storage devices, and electrochromic displays. Importantly, past studies on mixed ionic-electronic transport in PEDOT:PSS neglected to consider how the molecular structure of PSS affects mixed ionic-electronic transport. Herein, we therefore investigated the effect of the molecular weight and size distribution of PSS on the electronic properties and morphology of PEDOT:PSS both in dry and aqueous environments, and overall performance in organic electrochemical transistors (OECTs). Using reversible addition–fragmentation chain transfer (RAFT) polymerization with two different chain transfer agents, six PSS samples with monomodal, narrow (D = 1.1) and broad (D = 1.7) size distributions and varying molecular weights were synthesized and used as matrices for PEDOT. We found that using higher molecular weight of PSS (Mn = 145 kg mol –1 ) and broad dispersity led to OECTs with the highest transconductance (up to 16 mS) and [μC*] values (~140 F cm –1 V –1 s –1 ) in PEDOT:PSS, despite having a lower volumetric capacitance (C* = 35 ± 4 F cm –3 ). The differences were best explained by studying the microstructure of the films by atomic force microscopy (AFM). We found that heterogeneities in the PEDOT:PSS films (interconnected and large PEDOT- and PSS-rich domains) obtained from high molecular weight and high dispersity PSS led to higher charge mobility (μOECT ~4 cm 2 V –1 s –1 ) and hence transconductance. Furthermore, these studies highlight the importance of considering molecular weight and size distribution in organic mixed ionic-electronic conductor, and could pave the way to designing high performance organic electronics for biological interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of MCNP, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results analysis methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1987

Evaluation of an automated karyotyping system for chromosome aberration analysis

Chromosome aberration analysis is a promising complement to conventional radiation dosimetry, particularly in the complex radiation fields encountered in the space environment. The capabilities of a recently developed automated karyotyping system were evaluated both to determine current capabilities and limitations and to suggest areas where future development should be emphasized. Cells exposed to radiometric chemicals and to photon and particulate radiation were evaluated by manual inspection and by automated karyotyping. It was demonstrated that the evaluated programs were appropriate for image digitization, storage, and transmission. However, automated and semi-automated scoring techniques must be advanced significantly if in-flight chromosome aberration analysis is to be practical. A degree of artificial intelligence may be necessary to realize this goal.

Prichard, Howard M.↗
DOE OSTI2023

Hydrophobic, Thermal Shock-and-Corrosion-Resistant XSBR Latex-Modified Lightweight Class G Cement Composites in Geothermal Well Energy Storage Systems

Energy losses can be significantly reduced if thermally insulating cement is used for energy storage and recovery. The thermal conductivity (TC) of the currently used cement is between 1 and 1.2 W/mK. In this study we assessed the ability of polystyrene (PS)–polybutadiene (PB)–polyacrylic acid (PAA) terpolymer (cross-linked styrene–butadiene rubber, XSBR) latex to improve thermal insulating properties and thermal shock (TS) resistance of class G ordinary Portland cement (OPC) and fly ash cenosphere (FCSs) composites in the temperature range of 100–175 °C. The composites autoclaved at 100 °C were subjected to three cycles, one cycle: 175 °C heat → 25 °C water quenching). In hydrothermal and thermal (TS) environments at elevated temperatures in cement slurries the XSBR latex formed acrylic calcium complexes through acid–base reactions, and the number of such complexes increased at higher temperatures due to the XSBR degradation with formation of additional acrylic groups. As a result, these complexes offered the following five advanced properties to the OPC-based composites: (1) enhanced hydrophobicity; (2) decreased water-fillable porosity; (3) reduced TC for water-saturated composites; (4) minimized loss of compressive strength, Young’s modulus, and compressive fracture toughness after TS; and (5) abated pozzolanic activity of FCSs, which allowed FCSs to persist as thermal insulators under strongly alkaline conditions of cement slurries. Additionally, XSBR-modified slurries possessed improved workability and decreased slurry density due to the air-entraining effect of latex, which resulted in further improvement of thermal insulation performance of the modified composites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Impact of biomass ash content on biocomposite properties

Owing to its low cost and sustainable nature, lignocellulosic biomass has been utilized for reinforcing polymers, but it is crucial to understand the impact of high-ash concentrations in biomass on composite strength and processing. Biomass is not only desirable for biofuel production but could also have a strong market, if high-ash biomass is acceptable, for biocomposites. In this work, natural fibers (switchgrass and corn stover) were used to reinforce polylactic acid (PLA) to produce biocomposites. Natural fibers were pretreated to obtain fibers that contain different percentages of ash. The mechanical properties (such as Young's modulus, tensile strength, failure strain, storage modulus) of corn stover/PLA composites remained largely unaffected by the ash concentration of the biomass fibers, despite the large range of ash contents (2.2–11.9 wt%). Furthermore, the tensile strengths of switchgrass/PLA composites were slightly negatively affected by the ash concentration of the switchgrass fibers (0.7–2.1 wt%). Both the switchgrass/PLA and the corn stover/PLA composites exhibited a high-enough tensile strength (49–57 MPa) and suitable complex viscosity (2.0–7.0 kPa·s at the frequency of 3.2 rad/s). They are expected to be 3D-printable through an extrusion-based additive manufacturing process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Compression of tokamak boundary plasma simulation data using a maximum volume algorithm for matrix skeleton decomposition

This report demonstrates satisfactory data compression of SOLPS-ITER simulation output ranging from 2D fields, 1D profiles, and 0D scalar variables with a novel matrix decomposition approach. The singular value decomposition (SVD) scales poorly for large matrix sizes and is unsuited to the application on high dimensional data common to fusion plasma physics simulation. In this work, we employ the columns-submatrix-rows (CUR) matrix factorization technique in order to compute a low-rank approximation up to two orders of magnitude faster than the SVD, but within a nominal L2-norm relative error of ε = 10 –2 . In addition, the CUR approach maintains the original format of the data, in its extracted columns and rows, allowing for interpretable data storage at the original resolution of the simulation. We utilize an iterative algorithm to compute the CUR decomposition of simulation output by maximizing the volume, or linearly independent information content, of a low-rank submatrix contained within the data. Experiments over $\textit{n} × \textit{n}$ randomized test matrices with embedded rank-deficient features show that this maximum volume implementation of CUR matrix approximation has reduced asymptotic computational complexity on the order of n compared to the SVD, which scales approximately as $n^3$. These results show that the CUR technique can be used to effectively select time step snapshots (columns) of over 140 SOLPS-ITER output variables and the associated discretized coordinate timeseries (rows) allowing for reconstruction of the complete simulation dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗