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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 73 records · Page 4

UNH TDP - Voltsys Raw Data and Processing Scripts - Fall 2021

This submission contains raw Voltsys rectifier data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

UNH TDP - Shark Meter Raw Data and Processing Scripts - Fall 2021

This submission contains raw Shark Power Meter data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

UNH TDP - IMU Raw Data and Processing Scripts - Fall 2021

This submission contains raw Yost IMU (Inertial Measurement Unit) data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

UNH TDP - Load Cell Raw Data and Processing Scripts - Fall 2021

This submission contains raw Load Cell data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

Liquid–Liquid Equilibrium Prediction in Fast Pyrolysis Bio-Oil Systems: A Framework for Incorporating Bio-Oil Complexity

The study of mixtures of bio-oil, water and organic solvents in different proportions can serve as a cost-effective analysis of its content due to the formation of immiscible phases. This manuscript attempts to replicate experimentally determined partition coefficients (K OW ) of relevant species present in fast pyrolysis bio-oil (FPBO). A commercial flowsheeting simulator with surrogate bio-oil model representation is used. Concurrently, pyrolytic lignins in FPBO (‘pyrolignin’) do not have an agreed-upon structural representation, and the literature is ripe with wide variations of said representations. Thus, during the description of FPBO, this pyrolignin fraction was modeled using 20 possible structures (phenolic dimers to tetramers), with the goal of determining the structures for which the experimental data are best described. Two cases were considered: Case 1 normalized the reported experimental mass balance, while Case 2 included the unreported fraction in the mass balance to the total pyroligin. Please, add here a comment on the prediction of the Water oil equilibrium. The best KOW predictions for levoglucosan (LVG) were obtained when the system was modeled with no pyrolignin, presenting an MRE under 10% for both systems WO and BO. Among the possible structures, D2 (dimer), F1 (trimer) and I1, and I3 (tetramers) presented MRE ≤ 13% for both cases.

09 BIOMASS FUELS↗

Drop-on-demand sample delivery for studying biocatalysts in action at X-ray free-electron lasers

X-ray crystallography at X-ray free-electron laser (XFEL) sources is a powerful method for studying macromolecules at biologically relevant temperatures. Moreover, when combined with complementary techniques like X-ray emission spectroscopy (XES), both global structures and chemical properties of metalloenzymes can be obtained concurrently, providing new insights into the interplay between the protein structure/dynamics and chemistry at an active site. However, implementing such a multimodal approach can be compromised by conflicting requirements to optimize each individual method. In particular, the method used for sample delivery greatly impacts the data quality. We present here a new, robust way of delivering controlled sample amounts on demand using acoustic droplet ejection coupled with a conveyor belt drive that is optimized for crystallography and spectroscopy measurements of photochemical and chemical reactions over a wide range of time scales. Studies with photosystem II, the phytochrome photoreceptor, and ribonucleotide reductase R2 illustrate the power and versatility of this method.

59 BASIC BIOLOGICAL SCIENCES↗

Temporospatial shifts in the human gut microbiome and metabolome after gastric bypass surgery

Although the etiology of obesity is not well-understood, genetic, environmental, and microbiome elements are recognized as contributors to this rising pandemic. For morbid obesity, Roux-en-Y gastric bypass (RYGB) surgery alters the fecal microbiome, but data are sparse on temporal and spatial changes in the microbiome and metabolome. We characterized the structure and metabolism of the microbial communities in the gut lumen and on mucosal surfaces in morbidly obese individuals before and after RYGB surgery, and we compared our longitudinal cohort to a previously studied cross-sectional one. RYGB concurrently changed the gut microbiome and led to improvements of obesity comorbidities. Changes in the gut microbiome were reflected in the metabolome, including fermentation products and bile acids. The effects persisted 12 months post-surgery, and the microbiomes and metabolomes were similar to those found for the cross-sectional RYGB cohort. Thus, RYGB surgery had profound and persistent impacts on the intestinal microbiome and metabolome.

59 BASIC BIOLOGICAL SCIENCES↗

TGE: Machine Learning Based Task Graph Embedding for Large-Scale Topology Mapping

Task mapping is an important problem in parallel and distributed computing. The goal in task mapping is to find an optimal layout of the processes of an application (or a task) onto a given network topology. We target this problem in the context of staging applications. A staging application consists of two or more parallel applications (also referred to as staging tasks) which run concurrently and exchange data over the course of computation. Task mapping becomes a more challenging problem in staging applications, because not only data is exchanged between the staging tasks, but also the processes of a staging task may exchange data with each other. We propose a novel method, called Task Graph Embedding (TGE), that harnesses the observable graph structures of parallel applications and network topologies. TGE employs a machine learning based algorithm to find the best representation of a graph, called an embedding, onto a space in which the task-to-processor mapping problem can be solved. We evaluate and demonstrate the effectiveness of TGE experimentally with the communication patterns extracted from runs of XGC, a large-scale fusion simulation code, on Titan.

Choi, Jong Youl↗

Time resolved surface photovoltage measurements using a big data capture approach to KPFM

Optoelectronic behavior in materials such as organic/inorganic hybrid perovskites depend on a complex interplay between fast (electronic) and slower (ionic) processes. These processes are thought to be influenced by structural inhomogeneities (e.g. interfaces and grain boundaries) bringing forward the necessity for development of techniques capable of correlating nanostructure and photo-transport behavior. While Kelvin probe force microscopy (KPFM) is ideally suited to map surface potentials on relevant length scales, it lacks sufficient temporal resolution to extract the meaningful system dynamics. Here, we develop a time resolved surface photovoltage (SPV) measurement based on full information capture of the photodetector stream during open loop KPFM operation. G-Mode, or G-KPFM allows quantification of SPV with microsecond temporal and nanoscale spatial resolution. Using this technique, we observe concurrent spatial and fast temporal variations in the SPV generated across a methylammonium lead bromide (MAPbBr3) thin film, a possible indicator relating microstructure with heterogenous photo-transport behavior. Here, we further demonstrate the advantage of adopting big data analytics including unsupervised clustering methods to quickly discern spatial variability in the information rich SPV dataset. Beyond G-KPFM, such clustering methods will be useful for interpretation of the multidimensional datasets arising from the growing number of time resolved KPFM approaches now available.

36 MATERIALS SCIENCE↗

Structural basis of mutant-selectivity and drug-resistance related to CO-1686

Non-small-cell lung cancers (NSCLCs) caused by activating mutations in the kinase domain of epidermal growth factor receptor (EGFR) initially respond to first-generation reversible drugs gefitinib and erlotinib. However, clinical efficacy is limited due to the development of drug-resistance that in more than half of the cases are driven by the secondary T790M mutation. CO-1686 is one of the third generation irreversible inhibitors that inhibits EGFR activating mutants, including those with concurrent T790M, while avoiding the off-target toxicity owing to inhibition of wild-type EGFR in treating EGFR mutation-positive NSCLCs. Despite the remarkable success, the experimentally determined structure of this agent in complex with EGFR T790M remains unknown. In this study, we determined crystal structures of EGFR T790M or L858R mutants covalently bound by CO-1686. Based on these structural data, we can explain why CO-1686 irreversibly inhibits EGFR and selectively prefers T790M, which may help improving this or similar compounds, and explain why EGFR L718Q and L844V mutations incur resistance to this agent.

60 APPLIED LIFE SCIENCES↗

Block-Parallel Data Analysis with DIY2

DIY2 is a programming model and runtime for block-parallel analytics on distributed-memory machines. Its main abstraction is block-structured data parallelism: data are decomposed into blocks; blocks are assigned to processing elements (processes or threads); computation is described as iterations over these blocks, and communication between blocks is defined by reusable patterns. By expressing computation in this general form, the DIY2 runtime is free to optimize the movement of blocks between slow and fast memories (disk and flash vs. DRAM) and to concurrently execute blocks residing in memory with multiple threads. This enables the same program to execute in-core, out-of-core, serial, parallel, single-threaded, multithreaded, or combinations thereof. This paper describes the implementation of the main features of the DIY2 programming model and optimizations to improve performance. DIY2 is evaluated on benchmark test cases to establish baseline performance for several common patterns and on larger complete analysis codes running on large-scale HPC machines.

97 MATHEMATICS AND COMPUTING↗

The Center for Momentum Transport and Flow Organization in Plasmas - Final Scientific Report

Overview of University of Colorado Efforts: The University of Colorado group has focused on two primary fronts during the grant period: development of a variety of multi-point diagnostic and/or imaging analysis techniques, and momentum-transport related experiments on a variety of devices (NSTX at PPPL, CSDX at UCSD, LAPD at UCLA, DIII-D at GA). Experimental work has taken advantage of several diagnostic instruments, including fast-framing cameras for imaging of electron density fluctuations (either directly or using injected gas puffs), ECEI for imaging of electron temperature fluctuations, and multi-tipped Langmuir and magnetic probes for corroborating measurements of Reynolds and Maxwell stresses. Mode Characterization in CSDX: We have performed a series of experiments at the CSDX linear device at UCSD, in collaboration with Center PI G. Tynan's group. The experiments included a detailed study of velocity estimation techniques, including direct comparisons between Langmuir probes and image-based velocimetry from fast-framing camera data. We used the camera data in a second set of studies to identify the spatial and spectral structure of coherent modes, which illuminates wave behavior to a level of detail previously unavailable, and enables direct comparison of dispersion curves to theoretical estimates. In another CSDX study, similar techniques were used to demonstrate a controlled transition from nonlinearly coupled discrete eigenmodes to fully developed broadband turbulence. The axial magnetic field was varied from 40-240 mT, which drove the transition. At low magnetic fields, the plasma is dominated by drift waves. As the magnetic field is increased, a strong potential gradient at the edge introduces an ExB shear-driven instability. At the transition, another mode with signatures of a rotation-induced Rayleigh–Taylor instability appears at the central plasma region. Concurrently, large axial velocities were found in the plasma core. For larger magnetic fields, all of the instabilities co-exist, leading to rich plasma dynamics and fully developed broadband turbulence. Edge-Turbulence and Flow Experiments in NSTX: A series of Gas Puff Imaging (GPI) observations on NSTX revealed a quasi-periodic oscillation in the plasma edge preceding the L-H transition in a limited set of neutral beam heated plasmas. These ~3 kHz flow oscillations exhibit both long wavelength and long correlation lengths, suggesting they are zonal-flow-like. The flow oscillations are strongly correlated with modulations of the level of edge turbulence, thus the system appears to undergo a predator--prey-type limit-cycle preceding the L-H transition. However, a clear trigger for the L-H transition was not observed. Reynolds stress profiles were obtained directly from image velocimetry for L-mode periods ELM-Precursor Studies in NSTX: A separate study based on NSTX-GPI data captured the two-dimensional evolution of edge-localized mode (ELM) precursors. Precursor events were observed preceding ELMs and ELM-induced H–L back-transitions in radio-frequency heated H-mode plasmas, and the growth of the precursor mode through the ELM filamentation was imaged in the plane perpendicular to the local B-field. Strong edge intensity modulations appeared to propagate in the electron diamagnetic direction while steadily drifting radially outwards. Intensity fluctuations were observed at frequencies around 20 kHz and wavenumbers of 0.05-0.2 cm -1 . Upon growing to a trigger point, precursor fluctuations were seen to form filamentary structures and move into the scrape-off layer (SOL) explosively with radial velocities peaking at 8 km/s. Once in the SOL, filaments reverse their propagation direction and travel in the ion diamagnetic direction. Edge intensity fluctuations were strongly correlated with magnetic signals from Mirnov coils, and toroidally distributed coils estimated toroidal mode numbers of n=5-10. Quantitatively similar precursors have been observed in ohmic H-mode plasmas as well, though significantly fewer events are seen in the ohmic cases and none were observed in the near-threshold NBI H-modes studied. Development of Velocimetry and Image Analysis Techniques: Along with the experiments listed above, the Colorado group has continued to explore various velocimetry techniques and their range of validity. We have developed a “linear optical flow” code, which calculates smooth velocity maps while accurately assessing local regions of high curl. This is critical for separating spatial scales of velocity behavior, and thus transport. This code has recently come on-line, and we are currently using it to revisit a number of older datasets. Additionally, we have worked on developing pattern-recognition techniques for imaging diagnostics, based on established digital image compression algorithms. This has the potential to open the analysis of turbulent plasma behavior beyond the well-trodden Fourier and wavelet approaches. Finally, we have extended several of these image-analysis routines to multiple other diagnostic sets, including GPI datasets in NSTX and ECEI imaging on DIII-D. In one study, correlation maps were used to measure the full 2-D mode structure of drift-wave level structures using ECEI for the first time. This enabled direct comparison to gyrokinetic simulations using the GEM code, from which is was determined that TEM modes were being measured in DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enriched immersed finite element and isogeometric analysis: algorithms and data structures

Immersed finite element methods provide a convenient analysis framework for problems involving geometrically complex domains, such as those found in topology optimization and microstructures for engineered materials. However, their implementation remains a major challenge due to, among other things, the need to apply nontrivial stabilization schemes and generate custom quadrature rules. This article introduces the robust and computationally efficient algorithms and data structures comprising an immersed finite element preprocessing framework. The input to the preprocessor consists of a background mesh and one or more geometries defined on its domain. The output is structured into groups of elements with custom quadrature rules formatted such that common finite element assembly routines may be used without or with only minimal modifications. The key to the preprocessing framework is the construction of material topology information, concurrently with the generation of a quadrature rule, which is then used to perform enrichment and generate stabilization rules. While the algorithmic framework applies to a wide range of immersed finite element methods using different types of meshes, integration, and stabilization schemes, the preprocessor is presented within the context of the extended isogeometric analysis. This method utilizes a structured B-spline mesh, a generalized Heaviside enrichment strategy considering the material layout within individual basis functions’ supports, and face-oriented ghost stabilization. Using a set of examples, the effectiveness of the enrichment and stabilization strategies is demonstrated alongside the preprocessor’s robustness in geometric edge cases. Additionally, the performance and parallel scalability of the implementation are evaluated.

Computer implementation↗

ECP libraries and tools: An overview

The Exascale Computing Project (ECP) Software Technology and Co-Design teams addressed the growing complexities in high-performance computing (HPC) by developing scalable software libraries and tools that leverage exascale system capabilities. As we enter the exascale era, the need for reusable, optimized software solutions that can handle the unique challenges posed by these systems becomes increasingly important. The primary challenges the ECP teams faced were to create software libraries and tools that are performant on exascale architectures and portable and usable across diverse hardware platforms. Efforts addressed issues related to concurrent execution, memory management, and the integration of heterogeneous computing resources, such as GPUs from multiple vendors. The ECP’s strategy involved a structured development process encompassing the creation, optimization, and deployment of software in collaboration with industry, academia, and national laboratories. The project was organized into several technical areas: co-design of domain-specific suites with target applications, programming models and runtimes, development tools, mathematical libraries, data and visualization tools, and software ecosystem and delivery mechanisms. ECP has successfully developed a large portfolio of software libraries and tools that demonstrate significant improvements in performance and scalability on exascale systems. These products have been integrated into the Department of Energy’s computing facilities, supporting various scientific applications and ensuring robust performance across different hardware setups. ECP advancements in software development for exascale computing highlight the importance of a collaborative and adaptive approach to handling next-generation HPC systems complexities. The lessons learned emphasize the need for continuous engagement with end-users and vendors, and the importance of maintaining a balance between innovation and practical implementation. Future efforts will focus on ensuring scalability, keeping pace with rapid hardware advancements, and further enhancing the interoperability and usability of the software ecosystem. In conclusion, subsequent articles in this special issue provide in-depth discussions and case studies into specific library and tool efforts.

97 MATHEMATICS AND COMPUTING↗

Efficient Synthesis of Graph Methods: a Dynamically Scheduled Architecture

RDF databases naturally map to a graph representation and employ languages, such as SPARQL, that implements queries as graph pattern matching routines. Graph methods exhibit an irregular behavior: they present unpredictable, fine-grained data accesses, and are synchronization inten- sive. Graph data structures expose large amounts of dy- namic parallelism, but are difficult to partition without gen- erating load unbalance. In this paper, we present a novel ar- chitecture to improve the synthesis of graph methods. Our design addresses the issues of these algorithms with two com- ponents: a Dynamic Task Scheduler (DTS), which reduces load unbalance and maximize resource utilization, and a Hi- erarchical Memory Interface controller (HMI), which pro- vides support for concurrent memory operations on multi- ported/multi-banked shared memories. We evaluate our ap- proach by generating the accelerators for a set of SPARQL queries from the Lehigh University Benchmark (LUBM). We first analyze the load unbalance of these queries, showing that execution time among tasks can differ even of order of magnitudes. We then synthesize the queries and com- pare the performance of the resulting accelerators against the current state of the art. Experimental results show that our solution provides a speedup over the serial implementa- tion close to the theoretical maximum and a speedup up to 3.45 over a baseline parallel implementation. We conclude our study by exploring the design space to achieve maximum memory channels utilization. The best design used at least three of the four memory channels for more than 90% of the execution time.

architecture↗

High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind

The data was generated with ExaWind (https://github.com/Exawind) which couples AMR-Wind (https://github.com/Exawind/amr-wind/), Nalu-Wind (https://github.com/Exawind/nalu-wind), TIOGA (https://github.com/Exawind/tioga), and OpenFAST (https://github.com/OpenFAST/openfast). This is a large-scale simulation of a blade-resolved wind farm using the ExaWind software stack. ExaWind couples together a background flow solver, AMR-Wind, and a near-body solver, Nalu-Wind, through an overset technique from the TIOGA application. Another application, OpenFAST, handles the structural dynamics of the turbine blades and towers, which informs the fluid-structure interaction of the wind turbines with the flow solvers. This particular simulation includes four blade-resolved wind turbines operating in a turbulent atmospheric boundary layer. The AMR-Wind solver uses 500 million cells and is being solved on 256 AMD GPUs of the Oakridge Leadership Computing Facility Frontier supercomputer. Each turbine is assigned its own Nalu-Wind solver with over 13 million elements per turbine and solved using 448 CPU cores, for a total of 1792 CPU cores. For each node, 56 cores contain Nalu-Wind, while 8 cores correspond to AMR-Wind operations on the GPUs. Consequently, ExaWind is entirely utilizing the CPUs and the GPUs of the nodes concurrently. The data used in the visualization is full flow field data output from the simulation. It is lossy-compressed to a specific accuracy using ZFP and written to disk every 16 time-steps to enable real-time flow visualization. The flow fields are sampled at a high temporal frequency to enable real-time, 24fps visualization. The flow fields are sampled every 12 simulation time steps (every 0.04132s).

17 WIND ENERGY↗

Coordination Sphere of Lanthanide Aqua Ions Resolved with Ab Initio Molecular Dynamics and X-ray Absorption Spectroscopy

To resolve the fleeting structures of lanthanide Ln 3+ aqua ions in solution, we (i) performed the first ab initio molecular dynamics (AIMD) simulations of the entire series of Ln 3+ aqua ions in explicit water solvent using pseudopotentials and basis sets recently optimized for lanthanides and (ii) measured the symmetry of the hydrating waters about Ln 3+ ions (Nd 3+ , Dy 3+ , Er 3+ , Lu 3+ ) for the first time with extended X-ray absorption fine structure (EXAFS). EXAFS spectra were measured experimentally and generated from AIMD trajectories to directly compare simulation, which concurrently considers the electronic structure and the atomic dynamics in solution, with experiment. In this study, we performed a comprehensive evaluation of EXAFS multiple-scattering analysis (up to 6.5 Å) to measure Ln–O distances and angular correlations (i.e., symmetry) and elucidate the molecular geometry of the first hydration shell. This evaluation, in combination with symmetry-dependent L 3 - and L 1 -edge spectral analysis, shows that the AIMD simulations remarkably reproduces the experimental EXAFS data. The error in the predicted Ln–O distances is less than 0.07 Å for the later lanthanides, while we observed excellent agreement with predicted distances within experimental uncertainty for the early lanthanides. Our analysis revealed a dynamic, symmetrically disordered first coordination shell, which does not conform to a single molecular geometry for most lanthanides. This work sheds critical light on the highly elusive coordination geometry of the Ln 3+ aqua ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of mobility data to build contact networks for COVID-19

As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.

60 APPLIED LIFE SCIENCES↗