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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 253 records · Page 14

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DOE OSTI2015

Investigation of structural heterogeneity at the SPE site using combined P –wave travel times and Rg phase velocities

Here, we present analyses of the 2D seismic structure beneath Source Physics Experiments (SPE) geophone lines that extended radially at 100 m spacing from 100 to 2000 m from the source borehole. With seismic sources at only one end of the geophone lines, standard refraction profiling methods cannot resolve seismic velocity structures unambiguously. In previous work, we demonstrated overall agreement between body-wave refraction modeling and Rg dispersion curves for the least complex of the five lines. A more detailed inspection supports a 2D reinterpretation of the structure. We obtained Rg phase velocity measurements in both the time and frequency domains, then used iterative adjustment of the initial 1D body-wave model to predict Rg dispersion curves to fit the observed values. Our method applied to the most topographically severe of the geophone lines is supplemented with a 2D ray-tracing approach, whose application to P-wave arrivals supports the Rg analysis. In addition, midline sources will allow us to refine our characterization in future work.

58 GEOSCIENCES↗

DOE OSTI2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing

Fusion energy experiments and simulations provide critical information needed to plan future fusion reactors. As next-generation devices like ITER move toward long-pulse experiments, analyses, including AI and ML, should be performed in a wide range of time and computing constraints, from near-real-time constraints, between-shot analysis, and to campaign-wide long-term analysis. However, the data volume, velocity, and variety make it extremely challenging for analyses using only local computational resources. Researchers need the ability to compose and execute workflows spanning edge resources to large-scale high-performance computing facilities.We present Delta, a system to address data analysis challenges, including AI/ML, in fusion science, by leveraging the ADIOS I/O library and middleware, to support executing science workflows over the wide area network for near-real-time streaming. We discuss the data federation challenges in performing remote workflows, focusing on on-going research work in (1) managing, reducing, and streaming data to minimize I/O and data movement overheads, (2) decompressing and reorganizing data for analysis, and (3) executing workflows for automated data analysis. We introduce examples for deep-learning based data analysis for the fusion domain and demonstrate how we use Delta to construct end-to-end workflows for a fusion device in Korea, connecting a remote DOE facility in the USA. The capability demonstrated by this project is the basis for improving the state of the art for near-real-time data federation amongst remote facilities.

Choi, Jong Youl↗

DOE OSTI2020

Tetrahedral Trees: A Family of Hierarchical Spatial Indexes for Tetrahedral Meshes

In this work, we address the problem of performing efficient spatial and topological queries on large tetrahedral meshes with arbitrary topology and complex boundaries. Such meshes arise in several application domains, such as 3D Geographic Information Systems (GISs), scientific visualization, and finite element analysis. To this aim, we propose Tetrahedral trees, a family of spatial indexes based on a nested space subdivision (an octree or a kD-tree) and defined by several different subdivision criteria. We provide efficient algorithms for spatial and topological queries on Tetrahedral trees and compare to state-of-the-art approaches. Our results indicate that Tetrahedral trees are an improvement over R*-trees for querying tetrahedral meshes; they are more compact, faster in many queries, and stable at variations of construction thresholds. They also support spatial queries on more general domains than topological data structures, which explicitly encode adjacency information for efficient navigation but have difficulties with domains with a non-trivial geometric or topological shape.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Regression Based Approach for Robust Finite Element Analysis on Arbitrary Grids. LDRD Final Report

This report summarizes the work performed under a one-year LDRD project aiming to enable accurate and robust numerical simulation of partial differential equations for meshes that are of poor quality. Traditional finite element methods use the mesh to both discretize the geometric domain and to define the finite element shape functions. The latter creates a dependence between the quality of the mesh and the properties of the finite element basis that may adversely affect the accuracy of the discretized problem. In this project, we propose a new approach for defining finite element shape functions that breaks this dependence and separates mesh quality from the discretization quality. At the core of the approach is a meshless definition of the shape functions, which limits the purpose of the mesh to representing the geometric domain and integrating the basis functions without having any role in their approximation quality. The resulting non-conforming space can be utilized within a standard discontinuous Galerkin framework providing a rigorous foundation for solving partial differential equations on low-quality meshes. We present a collection of numerical experiments demonstrating our approach in a wide range of settings: strongly coercive elliptic problems, linear elasticity in the compressible regime, and the stationary Stokes problem. We demonstrate convergence for all problems and stability for element pairs for problems which usually require inf-sup compatibility for conforming methods, also referring to a minor modification possible through the symmetric interior penalty Galerkin framework for stabilizing element pairs that would otherwise be traditionally unstable. Mesh robustness is particularly critical for elasticity, and we provide an example that our approach provides a greater than 5x improvement in accuracy and allows for taking an 8x larger stable timestep for a highly deformed mesh, compared to the continuous Galerkin finite element method. The report concludes with a brief summary of ongoing projects and collaborations that utilize or extend the products of this work.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1981

Aircraft control-display analysis and design using the optimal control model of the human pilot

The use of the optimal control model (OCM) of the human pilot as a design tool is discussed. A novel procedure for the assignment and selection of model parameters in the absence of experimental data is proposed. A technique for partitioning a weakly coupled, multiaxis task into approximate state-uncoupled, single-axis tasks is introduced. The resulting modeling technique is utilized in the design and analysis of an aircraft flight-director system. This flight-director design technique differs from previous related work using the OCM in that considerable effort is devoted to ensuring that the OCM-designed director exhibits the desirable frequency-domain characteristics associated with experimentally verified classical designs (e.g., K/s 'effective vehicle' characteristics, noninteracting controls). The implications of the technique in the design of automatic flight control systems which employ the human pilot as a performance assessor and failure detector are briefly discussed.

Hess, R. A.↗

DOE OSTI2022

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Toward Linear Stability Analysis of Upper Plenum Flows

Linear stability analysis is a tool used to help identify the sensitivity of a particular domain to perturbations and evaluate the system dynamics as a transition, if any, occurs. The development of a time invariant base flow for future use in a linear stability analysis is the focus of this investigation. A test case, with a Reynolds number of 100, was brought to a steady state using the spectral element code Nek5000 and the method of selective frequency damping. The convergence criteria for this method is the volume averaged value of the forcing function which, after approximately 80,000 time-steps, decreased to 3.6x10{sup -4}. Analysis shows that the case has yet to have reached the tolerance desired, 1x10{sup -6}. With the simulation in the process of converging a preliminary perturbation analysis was conducted. Due to the low Reynolds number of this case, 100, it was hypothesized that the flow would be linearly stable. This preliminary stability analysis only focused on the largest fundamental mode and the energy growth of that perturbation over time. Upon evaluation of the perturbation energy, which was shown to be monotonically decreasing in time, it was concluded that, despite not yet being converged, the system is in fact linearly stable. Future work includes evaluating the domain at higher Reynolds numbers, solving the eigenvalue problem created when the linearized Navier-Stokes are written in operator form and calculating the energy evolution of the optimal perturbation. (authors)

42 ENGINEERING↗

DOE OSTI2017

Effects of naturally occurring charged mutations on the structure, stability, and binding of the Pin1 WW domain

Pin1 is a peptidyl-prolyl cis-trans isomerase, whose WW domain specifically recognizes the pSer/Thr-Pro motif. Pin1 is involved in multiple phosphorylation events that regulate the activities of various substrates, and Pin1 deregulation has been reported in various diseases, including cancer and Alzheimer's disease. The WW domain of Pin1 has been used as a small model protein to investigate the folding mechanisms of the β-sheet structure by studying the effect of mutations or its naturally occurring variants. However, only a few studies have investigated the structure and binding of Pin1 WW mutants. In the present work, two naturally occurring Pin1 WW variants, namely, G20D and S16R, derived from the cynomolgus monkey and African green monkey, respectively, were selected to investigate the influence of charge mutation on the structure, stability, and binding properties of the Pin1 WW domain. Analysis using a combination of nuclear magnetic resonance (NMR) and chemical shift-based calculations revealed that the G20D and S16R mutants had high structural similarity to the wild-type Pin1 WW domain. However, the presence of a charge mutation significantly decreased the stability of the Pin1 WW domain. Both the wild-type and G20D forms of the Pin1 WW domain utilized a three-site mode to bind to a phosphorylated Tau peptide, pT231, whereas the S16R mutant binds to the pT231 peptide either in a non-specific manner or through a totally different binding mechanism. Correspondingly, the wild-type and two mutant Pin1 WW domains showed different binding affinities to the Tau phosphopeptide. Considering that the WW domain participates in the catalytic activity of the Pin1 isomerase, our study represents a novel approach for studying Pin1 function through the analysis of its naturally occurring mutants. - Highlights: • G20D and S16R Pin1 WW had high structure similarity to wild-type. • Stabilities of G20D and S16R mutant Pin1 WW significantly decreased. • wild-type and G20D Pin1 WW utilized three-site mode for phosphorylated Tau binding. • wild-type and mutant Pin1 WW showed differential binding affinities to substrate.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Conceptual process design and economics for the production of high-octane gasoline blendstock via indirect liquefaction of biomass through methanol/dimethyl ether intermediates

This paper describes in detail one potential conversion process for the production of high-octane gasoline blendstock via indirect liquefaction of biomass. The processing steps of this pathway include the conversion of biomass to synthesis gas via indirect gasification, gas clean-up via reforming of tars and other hydrocarbons, catalytic conversion of syngas to methanol, methanol dehydration to dimethyl ether (DME), and the homologation of DME over a zeolite catalyst to high-octane gasoline-range hydrocarbon products. The current process configuration has similarities to conventional methanol-to-gasoline (MTG) technologies, but there are key distinctions, specifically regarding the product slate, catalysts, and reactor conditions. A techno-economic analysis is performed to investigate the production of high-octane gasoline blendstock. The design features a processing daily capacity of 2000 tonnes (2205 short tons) of dry biomass. The process yields 271 liters of liquid fuel per dry tonne of biomass (65 gal/dry ton), for an annual fuel production rate of 178 million liters (47 MM gal) at 90% on-stream time. The estimated total capital investment for an nth-plant is $438 million. The resulting minimum fuel selling price (MFSP) is $0.86 per liter or $3.25 per gallon in 2011 US dollars. A rigorous sensitivity analysis captures uncertainties in costs and plant performance. Sustainability metrics for the conversion process are quantified and assessed. The potential premium value of the high-octane gasoline blendstock is examined and found to be at least as competitive as fossil-derived blendstocks. A simple blending strategy is proposed to demonstrate the potential for blending the biomass-derived blendstock with petroleum-derived intermediates. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗

DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Coupled SAM/Griffin Model of a Reference Fluoride-Salt-Cooled High-Temperature Reactor for Multi-Physics Simulations

A multi-physics coupled simulation model of a reference pebble bed fluoride-salt-cooled high-temperature reactor (PB-FHR) has been developed with SAM and Griffin computer codes for transient safety analysis. The reference problem of a prototypical reactor design serves as the foundation for the U.S. NRC (Nuclear Regulatory Commission) to verify the adequacy of computer codes and evaluation models for specific reactor types. In this work, the previously developed SAM model for PB-FHR primary loop has been updated for the coupled simulation. The updated SAM PB-FHR model includes a 2-D axial symmetric core region and external core components in 0-D/1-D. In addition to the primary loop, a detailed model of the RCCS (reactor cavity cooling system) is added. The 2-D and 1-D domains are tightly coupled using the single-solve approach developed in SAM. In the pebble bed region, the SAM multiscale explicit pebble model is applied to calculate the pebble and TRISO fuel kernel temperatures. The Griffin model used in this work is based on a model developed at Idaho National Laboratory in collaboration with the U.S. NRC. The Griffin neutronics model and SAM thermal hydraulics model is coupled with the Comprehensive Reactor Analysis Bundle (CRAB or alternately BlueCRAB) application. Both steady-state and transient scenarios are simulated to demonstrate the model's suitability for multi-physics simulations of PB-FHR transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2001

Toward an Efficient Icing CFD Process Using an Interactive Software Toolkit: Smagglce 2D

Two-dimensional CID analysis for iced airfoils can be a labor-intensive task. The software toolkit SmaggIce 2D is being developed to help streamline the CID process and provide the unique features needed for icing. When complete, it will include a combination of partially automated and fully interactive tools for all aspects of the tasks leading up to the flow analysis: geometry preparation, domain decomposition. block boundary demoralization. gridding, and linking with a flow solver. It also includes tools to perform ice shape characterization, an important aid in determining the relationship between ice characteristics and their effects on aerodynamic performance. Completed tools, work-in-progress, and planned features of the software toolkit are presented here.

Vickerman, Mary B.↗

NASA NTRS2002

Toward an Efficient Icing CFD Process Using an Interactive Software Toolkit--SmaggIce 2D

Two-dimensional CFD analysis for iced airfoils can be a labor-intensive task. The software toolkit SmaggIce 2D is being developed to help streamline the CFD process and provide the unique features needed for icing. When complete, it will include a combination of partially automated and fully interactive tools for all aspects of the tasks leading up to the flow analysis: geometry preparation, domain decomposition, block boundary discretization. gridding, and linking with a flow solver. It also includes tools to perform ice shape characterization, an important aid in determining the relationship between ice characteristics and their effects on aerodynamic performance. Completed tools, work-in-progress, and planned features of the software toolkit are presented here.

Vickerman, Mary B.↗

NASA NTRS2001

Development of an Aeroelastic Analysis Including a Viscous Flow Model

Under this grant, Version 4 of the three-dimensional Navier-Stokes aeroelastic code (TURBO-AE) has been developed and verified. The TURBO-AE Version 4 aeroelastic code allows flutter calculations for a fan, compressor, or turbine blade row. This code models a vibrating three-dimensional bladed disk configuration and the associated unsteady flow (including shocks, and viscous effects) to calculate the aeroelastic instability using a work-per-cycle approach. Phase-lagged (time-shift) periodic boundary conditions are used to model the phase lag between adjacent vibrating blades. The direct-store approach is used for this purpose to reduce the computational domain to a single interblade passage. A disk storage option, implemented using direct access files, is available to reduce the large memory requirements of the direct-store approach. Other researchers have implemented 3D inlet/exit boundary conditions based on eigen-analysis. Appendix A: Aeroelastic calculations based on three-dimensional euler analysis. Appendix B: Unsteady aerodynamic modeling of blade vibration using the turbo-V3.1 code.

Keith, Theo G., Jr.↗

DOE OSTI2016

Roadmap to the multidisciplinary design analysis and optimisation of wind energy systems

Here, a research agenda is described to further encourage the application of Multidisciplinary Design Analysis and Optimisation (MDAO) methodologies to wind energy systems. As a group of researchers closely collaborating within the International Energy Agency (IEA) Wind Task 37 for Wind Energy Systems Engineering: Integrated Research, Design and Development, we have identified challenges that will be encountered by users building an MDAO framework. This roadmap comprises 17 research questions and activities recognised to belong to three research directions: model fidelity, system scope and workflow architecture. It is foreseen that sensible answers to all these questions will enable to more easily apply MDAO in the wind energy domain. Beyond the agenda, this work also promotes the use of systems engineering to design, analyse and optimise wind turbines and wind farms, to complement existing compartmentalised research and design paradigms.

17 WIND ENERGY↗

DOE OSTI2023

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression

With the scaling up of simulation-based scientific discovery on high-performance computing systems, the disparity between compute and I/O has increased, forcing domain scientists to save only a small amount of simulation data to persistent storage. This can result in the loss of essential physics fields that are needed for data analysis. While error-bounded lossy compression has made tremendous progress in bridging the gap between compute and I/O, the lack of understanding of compression performance remains a key hurdle to its wide adoption. Here, in this work, we present zPerf, a statistical gray-box performance modeling approach for scientific lossy compression. Our contributions are threefold: 1) We develop zPerf to estimate the performance of lossy compression techniques, based on in-depth understanding and statistical modeling for data features and core compression metrics; 2) We demonstrate the in-detailed implementation of zPerf using two case studies, where we derive the performance modeling for SZ and ZFP, two leading lossy compressors; 3) We evaluate the effectiveness of zPerf on real-world datasets across various domains. Based on the evaluation, we demonstrate the efficacy of the zPerf performance model; 4) We further discuss three case studies where zPerf is applied to extrapolate the compression ratio of SZ and ZFP with alternative encoding schemes as well as ZFP with an alternative transform scheme. Through the case studies, we demonstrate the potential of zPerf for exploring the design space of lossy compression, which has hardly been studied in the literature.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models

Modern machine learning and autonomous experimentation schemes in materials science rely on accurate analysis of the data ingested by these models. Unfortunately, accurate analysis of the underlying data can be difficult, even for domain experts, complicating the training of the models intended to drive experiments. This is especially true when the goal is to identify the presence of weak signatures in diffraction or spectroscopic datasets. In this work, we examine a set of as-obtained diffraction data that track the phase transition from monoclinic to tetragonal in a Nb-doped VO2 film as a function of temperature and dopant concentration. We then task a set of domain experts and a set of machine learning experts with identifying which phase is present in each diffraction pattern manually and algorithmically, respectively; in both cases, the labels can vary dramatically, especially at the phase boundaries. We use the mode of the labels and the Shannon entropy as a method to capture, preserve and propagate consensus labels and their variance. Further we use the expert labels as a benchmark and demonstrate the use of Shannon entropy weighted scoring to test the performance of machine learning generated labels. Finally, we propose a material data challenge centered around generating improved labeling algorithms. This real-world dataset curated with expert labels can act as test bed for new algorithms. The raw data, annotations and code used in this study are all available online at data.gov and the interested reader is encouraged to replicate and improve the existing models

97 MATHEMATICS AND COMPUTING↗