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At least 1,315 records · Page 73

Preliminary Designs for Criticality Safety Benchmarks—Iron/Steel/Chromium Series

The nuclear criticality safety community uses critical benchmarks extensively when analyzing nuclear systems. Having benchmarks sensitive to important materials of interest helps to ensure safety and constrain results. Critical benchmarks are also invaluable to the nuclear data community, which uses these benchmarks as a check and measure of quality of nuclear data libraries. Additionally, integral benchmarks are often used to validate the performance of computational tools for simulating nuclear systems. Many integral benchmarks have been documented in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook, the International Reactor Physics Experiment Evaluation Project (IRPhEP) handbook, and the Shielding Integral Benchmark Archive Database (SINBAD). The National Criticality Experiments Research Center (NCERC), operated by Los Alamos National Laboratory, is the only general purpose critical experiments facility in the United States of America. NCERC regularly designs and executes critical experiments and other measurements useful to a wide variety of fields including nuclear criticality safety, commercial nuclear energy, nonproliferation, and nuclear data. NCERC has recently developed tools to visualize gaps and deficiencies in existing criticality benchmarks – this work is still ongoing. Through this work and other reviews, some high priority deficiencies have been identified. This paper aims to highlight three areas where additional critical benchmarks would be useful to the nuclear criticality safety community and various other groups. Additionally, NCERC is seeking feedback in regard to these proposed measurements to make sure they are as useful to as many communities as possible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High-temperature LDV seed particle development

The feasibility of developing a method for making monodisperse, unagglomerated spherical particles greater than 50 nm in diameter was demonstrated. Carbonaceous particles were made by pyrolyzing ethylene with a pulsed CO2 laser, thereby creating a non-equilibrium mixture of carbon, hydrogen, hydrocarbon vapors, and unpyrolyzed ethylene. Via a complex series of reactions, the carbon and hydrocarbon vapors quickly condensed into the spherical particles. By cooling and dispersing them in a supersonic expansion immediately after their creation, the hot newly-formed spheres were prevented from colliding and coalescing, thus preventing the problem of agglomeration which as plagued other investigators studying laser-simulated particle formation. The cold particles could be left suspended in the residual gases indefinitely without agglomerating. Their uniform sizes and unagglomerated nature were visualized by collecting the particles on filters that were subsequently examined using electron microscopy. It was found the mean particle size can be coarsely controlled by varying the initial ethylene pressure, and can be finely controlled by varying the fluence (energy/unit area) with which the laser irradiates the gas. The motivating application for this research was to manufacture particles that could be used as laser Doppler velocimetry (LDV) seeds in high-temperature high-speed flows. Though the particles made in this program will not evaporate until heated to about 3000 K, and thus could serve as LDV seeds in some applications, they are not ideal when the hot atmosphere is also oxidizing. In that situation, ceramic materials would be preferable. Research performed elsewhere has demonstrated that selected ceramic materials can be manufactured by laser pyrolysis of appropriate supply gases. It is anticipated that, when the same gases are used in conjunction with the rapid cooling technique, unagglomerated spherical ceramic particles can be made with little difficulty. Such particles would also be valuable to manufacturers of ceramic or abrasive products, and this technique may find its greatest commercial potential in those areas.

Frish, Michael B.↗

Advanced Capability of Monte Carlo Transport and Depletion Calculation Program SuperMC for Fusion and Fission Applications

Since the advantages of high simulation accuracy and flexible geometry representation, the Monte Carlo methods have been broadly adopted in nuclear design and analysis of nuclear energy systems. However, great challenges exist for the current Monte Carlo methods including the calculation modeling of complex geometries, slow convergence of complex calculation, etc. Super Monte Carlo Simulation Program for Nuclear and Radiation Process (SuperMC), developed by FDS team, is a general purpose, intelligent and multi-functional program for the design and safety evaluation of nuclear systems, which is designed to perform the comprehensive neutronics calculation. The latest version of SuperMC can accomplish the transport calculation of n,{gamma} for criticality and shielding problems, depletion calculation of isotopes, and has been integrated with the functions of automatic modeling, visualization and cloud computing. The latest progress will be introduced in this paper. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Imaging of 3D morphological evolution of nanoporous silicon anode in lithium ion battery by X-ray nano-tomography

Nanostructured silicon with its high theoretical capacity and ability to accommodate volume expansion has attracted great attention as a promising anode material for Lithium ion (Li-ion) batteries. Liquid metal dealloying method, is a novel method to create nanoporous silicon (np-Si). The assembled Li-ion batteries based on such np- Si anode can be cycled beyond 1500 cycles, in 1000 mA h/g constant capacity cycling mode with consistent performance; however, it suffers from degradation after ~ 460 cycles, while being cycled under 2000 mA h/g. To reveal the failure mechanism and differences in the morphological evolution in different capacity cycling modes in the np-Si anode, we conducted synchrotron X-ray nano-tomography studies. The three dimensional (3D) morphological evolution was visualized and quantified as a function of the number of cycles and cycling capacities. By comparing the 3D morphology under each cycling condition and correlating these 3D morphological changes with cycling-life performance, we elucidate the failure mechanism of the np-Si electrodes resulting from a mesoscopic to macroscopic deformation, involving volume expansion and gradual delamination. In particular, the shorter cycling life in higher-capacity cycling mode stems from particle agglomeration. Overall, while the nanoporous structure can accommodate the volume expansion locally, these mesoscopic and macroscopic deformations ultimately result in heterogeneous stress distribution with faster delamination. As a result, the work thus sheds the light on the importance to consider the structural evolution at the mesoscopic and macroscopic scales, while designing nano-structured energy storage materials for enhanced performances, particularly for long cycling-life durability.

25 ENERGY STORAGE↗

A fresh perspective on the role of band bending, and related contributors, in light-driven production of electricity and chemicals

It is widely known that semiconductor-based solar energy conversion could power our planet. This is in part because high-quality semiconductor structures are unrivalled in their ability to separate photogenerated electrons and holes. One effective approach to achieving this photoinduced charge separation relies on a phenomenon known as “band bending”. But details to justify why band bending results in photoinduced charge separation are more complex than often appreciated. This underappreciation is an impediment to the rational, hypothesis-driven design of next-generation approaches to solar energy conversion. Herein we show, by means of derivations rooted in physical chemistry, that several phenomena – not just band bending – can facilitate photoinduced charge separation, and that each is influenced by nonequilibrium species concentration and a parameter, such as diffusion coefficient or rate coefficient, that introduces dynamics. To help visualize the impact of each phenomenon, we introduce plots that depict their contributions as free energy, force, flux, force constant, and rate. We reveal that spatial dopant distributions that define band bending are predictors of initial photogenerated species transport rates. But charge separation alone does not guarantee high-efficiency operation. A photogenerated change in energy that is freely available to do useful work is also essential, and is strongly dependent on semiconductor optical properties and reaction kinetics. Notably, this information reveals that specificity of interfacial chemical reactions – even when they are not preceded by charge separation elsewhere – can result in efficient solar energy conversion. We expect that this tutorial will guide researchers in their pursuit to uncover new mechanisms for light to perform useful work.

14 SOLAR ENERGY↗

X-ray Computed Tomography as a Metrology Technique for the Analysis of Additively Manufactured Material

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non-destructively characterize features in a variety materials like polymer, metals, composites, and explosives. It also has the capability of imaging additively manufacture, machine and assembled parts. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of the material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations due to different stimuli and assess the accuracy of material production. This study focuses on parts manufactured via metal additive manufacturing (AM). Although AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties and performance. The analysis of 3D printed objects has an asset in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e., foams) due to stochastic structures. For this study, the print accuracy of four additively manufactured cylinders will be assessed via X-ray CTto approximate the surface roughness and visualize any major morphological changes to assess the dimensional accuracy of complex additively manufactured parts. It was concluded that using X-ray CT to measure surface roughness was affective because reasonable surface roughness values were measured. Additionally, itwas determined that small-scale features can be produced via additive manufacturing with strong dimensional accuracy so long as the features are highly complex with sharp grooves.

36 MATERIALS SCIENCE↗

Evaluation of several secondary tasks in the determination of permissible time delays in simulator visual and motion cues

The effect of secondary tasks in determining permissible time delays in visual-motion simulation of a pursuit tracking task was examined. A single subject, a single set of aircraft handling qualities, and a single motion condition in tracking a target aircraft that oscillates sinusoidally in altitude were used. In addition to the basic simulator delays the results indicate that the permissible time delay is about 250 msec for either a tapping task, an adding task, or an audio task and is approximately 125 msec less than when no secondary task is involved. The magnitudes of the primary task performance measures, however, differ only for the tapping task. A power spectraldensity analysis basically confirms the result by comparing the root-mean-square performance measures. For all three secondary tasks, the total pilot workload was quite high.

Miller, G. K., Jr.↗

NASA aviation safety reporting system

An analytical study of reports relating to cockpit altitude alert systems was performed. A recent change in the Federal Air Regulation permits the system to be modified so that the alerting signal approaching altitude has only a visual component; the auditory signal would continue to be heard if a deviation from an assigned altitude occurred. Failure to observe altitude alert signals and failure to reset the system were the commonest cause of altitude deviations related to this system. Cockpit crew distraction was the most frequent reason for these failures. It was noted by numerous reporters that the presence of altitude alert system made them less aware of altitude; this lack of altitude awareness is discussed. Failures of crew coordination were also noted. It is suggested that although modification of the altitude alert system may be highly desirable in short-haul aircraft, it may not be desirable for long-haul aircraft in which cockpit workloads are much lower for long periods of time. In these cockpits, the aural alert approaching altitudes is perceived as useful and helpful. If the systems are to be modified, it appears that additional emphasis on altitude awareness during recurrent training will be necessary; it is also possible that flight crew operating procedures during climb and descent may need examination with respect to monitoring responsibilities. A selection of alert bulletins and responses to them is presented.

Source record↗

Active wavefront correction in large telescopes

Astronomical progress with the MMT telescope, which attains high-resolution imaging by partial compensation for atmospheric distortion, is discussed. The small tertiary and beam combiner mirrors at the MMT bring six images to a common focus, where there is a TV system for acquisition and guiding. Individual image positions can be controlled by stepper motors driving actuators on the secondaries, each step moving an image 0.05 arc seconds in the focal plane. The instrument's correction for image jiggle due to atmospheric turbulence and drift of the relative positions of the images due to gravitational and thermal effects on the structure are described. A scheme for correcting residual structural errors is discussed. It appears that the telescope can work to about the 17th visual magnitude. For faint sky limited objects comparable performance would require a perfectly rigid single mirror of the same aperture to have 50 percent more collecting area and cost at least 1.5 times more.

Angel, J. R. P.↗

Instrumentation and telemetry systems for free-flight drop model testing

This paper presents instrumentation and telemetry system techniques used in free-flight research drop model testing at the NASA Langley Research Center. The free-flight drop model test technique is used to conduct flight dynamics research of high performance aircraft using dynamically scaled models. The free-flight drop model flight testing supplements research using computer analysis and wind tunnel testing. The drop models are scaled to approximately 20 percent of the size of the actual aircraft. This paper presents an introduction to the Free-Flight Drop Model Program which is followed by a description of the current instrumentation and telemetry systems used at the NASA Langley Research Center, Plum Tree Test Site. The paper describes three telemetry downlinks used to acquire the data, video, and radar tracking information from the model. Also described are two telemetry uplinks, one used to fly the model employing a ground-based flight control computer and a second to activate commands for visual tracking and parachute recovery of the model. The paper concludes with a discussion of free-flight drop model instrumentation and telemetry system development currently in progress for future drop model projects at the NASA Langley Research Center.

Hyde, Charles R.↗

Wake Vortex Advisory System (WakeVAS) Evaluation of Impacts on the National Airspace System

This report is one of a series that describes an ongoing effort in high-fidelity modeling/simulation, evaluation and analysis of the benefits and performance metrics of the Wake Vortex Advisory System (WakeVAS) Concept of Operations being developed as part of the Virtual Airspace Modeling and Simulation (VAMS) project. A previous study, determined the overall increases in runway arrival rates that could be achieved at 12 selected airports due to WakeVAS reduced aircraft spacing under Instrument Meteorological Conditions. This study builds on the previous work to evaluate the NAS wide impacts of equipping various numbers of airports with WakeVAS. A queuing network model of the National Airspace System, built by the Logistics Management Institute, Mclean, VA, for NASA (LMINET) was used to estimate the reduction in delay that could be achieved by using WakeVAS under non-visual meteorological conditions for the projected air traffic demand in 2010. The results from LMINET were used to estimate the total annual delay reduction that could be achieved and from this, an estimate of the air carrier variable operating cost saving was made.

Smith, Jeremy C.↗

Creating Benchmark Data for Artificial Intelligence and Machine Learning Space Biology Research

To identify an appropriate AI/ML approach for a specific problem, the best practice is to measure algorithm performance through the benchmarking process. A scientific benchmark consists of an AI-ready dataset and a reference implementation on a specific scientific question. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML to create scientific benchmark datasets in three applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. Currently, there are no standardized datasets available to benchmark AI/ML algorithms in the domain of space biology. In this work, we constructed two AI/ML-ready biological datasets from experiments in space-flown mice: cellular imaging and RNA-seq. First, radiation-exposed immune cells harbor DNA damage foci that can be fluorescently marked to visualize the amount of damage following exposure to ionizing radiation. However, such large datasets are difficult to analyze visually, due to imaging inconsistencies and human bias, and classical image processing approaches can fail on imaging artifacts. AI/ML are therefore exciting alternative, providing the speed of machines and the accuracy of humans. We have made this dataset available at https://registry.opendata.aws/bps_microscopy/. Second, high-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. However, most sequencing datasets suffer from high dimensionality and low sample count. In this work, we used a generative adversarial network to synthesize a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data with sufficient space-flown and ground control mouse liver samples from NASA GeneLab. This dataset is available at https://registry.opendata.aws/bps_rnaseq/. These datasets are now fully open the Space Biology community to test their favorite AI/ML approaches.

James Casaletto↗

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Influence of crystal allomorph and crystallinity on the products and behavior of cellulose during fast pyrolysis

Here, cellulose is the primary biopolymer responsible for maintaining the structural and mechanical integrity of cell walls and, during the fast pyrolysis of biomass, may be restricting cell wall expansion and inhibiting phase transitions that would otherwise facilitate efficient escape of pyrolysis products. Here, we test whether modifications in two physical properties of cellulose, its crystalline allomorph and degree of crystallinity, alter its performance during fast pyrolysis. We show that both crystal allomorph and relative crystallinity of cellulose impact the slate of primary products produced by fast pyrolysis. For both cellulose-I and cellulose-II, changes in crystallinity dramatically impact the fast pyrolysis product portfolio. In both cases, only the most highly crystalline samples produced vapors dominated by levoglucosan. Cellulose-III, on the other hand, produces largely the same slate of products regardless of its relative crystallinity and produced as much or more levoglucosan at all crystallinity levels compared to cellulose-I or II. In addition to changes in products, the different cellulose allomorphs affected the viscoelastic properties of cellulose during rapid heating. Real-time hot-stage pyrolysis was used to visualize the transition of the solid material through a molten phase and particle shrinkage. SEM analysis of the chars revealed additional differences in viscoelastic properties and molten phase behavior impacted by cellulose crystallinity and allomorph. Regardless of relative crystallinity, the cellulose-III samples displayed the most obvious evidence of having transitioned through a molten phase.

09 BIOMASS FUELS↗

Spatiotemporal mapping of mesoscopic liquid dynamics

The study of liquid dynamics at mesoscopic scales is still strewn with difficulty due to limitations in theory and experiment. Historically, significant attention has been given to the analysis of space-time correlation functions and their frequency-Fourier transforms at a few discrete wave numbers. The massive computing power afforded by modern high performance computing clusters and the advent of a wide-angle neutron spin-echo spectrometer, however, have unlocked a more intuitive and fruitful approach to this problem. Using molecular dynamics simulations, here we demonstrate the benefits of spatiotemporally mapping intermediate scattering functions on a dense grid of correlation times and wave numbers. Four model systems are investigated: a Lennard-Jones liquid, a coarse-grained bead-spring polymer, a molten sodium chloride, and a poly(ethylene oxide) melt. We show that the spatiotemporal mapping approach is particularly useful for elucidating the mesoscopic dynamics in these liquids, where several underlying mechanisms, such as molecular relaxations, hydrodynamic modes, and nonhydrodynamic excitations, are potentially at play. Therefore, compared to the traditional method, direct visualization of density space-time correlation functions on two-dimensional color maps permits appraisals of complicated dynamical behavior at mesoscales in a global manner. For example, the scaling relations between space and time for different types of molecular motions can be straightforwardly identified on these plots, without any model-dependent analysis. Additionally, we show how theoretical ideas regarding collective mesoscopic dynamics, such as the classical hydrodynamic theory, the convolution approximation, and a recently proposed phenomenological model, can be discussed in terms of the global features of spatiotemporal maps of intermediate scattering functions. The new perspective offered by the spatiotemporal mapping method should prove useful for the study of liquid dynamics in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions

High-order finite element methods (HO-FEM) are gaining popularity in the simulation community due to their success in solving complex flow dynamics. There is an increasing need to analyze the data produced as output by these simulations. Simultaneously, topological analysis tools are emerging as powerful methods for investigating simulation data. Yet, most of the current approaches to topological analysis have had limited application to HO-FEM simulation data for two reasons. First, the current topological tools are designed for linear data (polynomial degree one), but the polynomial degree of the data output by these simulations is typically higher (routinely up to polynomial degree six). Second, the simulation data and derived quantities of the simulation data have discontinuities at element boundaries, and these discontinuities do not match the input requirements for the topological tools. One solution to both issues is to transform the high-order data to achieve low-order, continuous inputs for topological analysis. Nevertheless, there has been little work evaluating the possible transformation choices and their downstream effect on the topological analysis. We perform an empirical study to evaluate two commonly used data transformation methodologies along with the recently introduced L-SIAC filter for processing high-order simulation data. Our findings indicate diverse behaviors are possible. We offer some guidance about how best to consider a pipeline of topological analysis of HO-FEM simulations with the currently available implementations of topological analysis.

97 MATHEMATICS AND COMPUTING↗