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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Performance Portability of HPC Discovery Science Software: Fusion Energy Turbulence Simulations at Extreme Scale

As HPC R&D moves forward on a variety of “path to exascale” architectures today, an associated objective is to demonstrate performance portability of discovery-science-capable software. Important application domains, such as Magnetic Fusion Energy (MFE), have improved modelling of increasingly complex physical systems -- especially with respect to reducing “time-to-solution” as well as “energy to solution.” The emergence of new insights on confinement scaling in MFE systems has been aided significantly by efficient software capable of harnessing powerful supercomputers to carry out simulations with unprecedented resolution and temporal duration to address increasing problem sizes. Specifically, highly scalable particle-in-cell (PIC) programing methodology is used in this paper to demonstrate how modern scientific applications can achieve efficient architecture-dependent optimizations of performance scaling and code portability for path-to-exascale platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rates and Reversibilities in Interconnected Reaction Networks

Mathematical relations prescribing unidirectional forward and reverse rates originally derived based on single-path reaction sequences do not apply to interconnected reaction networks. The presence of branches in reaction networks, leading to alternative stable products, decreases unidirectional rates in reference to those calculated by single-path functional forms, as shown by simulated isotopic exchange rates, but impacts the unidirectional forward and reverse rates equally such that the functional form of effective reversibility remains unchanged. Regardless of stoichiometric numbers and network connectivity, the application of the pseudo-steady-state hypothesis on reactive intermediates in conjunction with consideration of unidirectional rates toward the product of interest and all alternative stable products results in mathematical expressions that accurately reflect simulated isotopic exchange rates. Further analyses based on kinetic resistance, a property akin to electrical resistance, illustrate the manifestation of nodal resistances in addition to the single-path kinetic resistance for interconnected reaction networks. The generalized formalism for assessing rates and reversibilities in interconnected networks derived herein enables us to demonstrate that unidirectional rates cannot be assessed solely from effective reversibilities and net rates of generation of stable species in such networks. Furthermore, isotopic exchange rates, under the condition that each elementary step in the overall reaction sequence forms a unique reactive intermediate that is consumed solely by the subsequent step, can be utilized to determine unidirectional rates and can serve to validate postulated reaction pathways in highly interconnected reaction networks (e.g., CO x hydrogenation).

42 ENGINEERING↗
DOE OSTI2013

Experiences Applying Data Staging Technology in Unconventional Ways

Several efforts have shown the potential of using additional compute-area resources to enhance the IO path to storage. Efforts like data staging, IO forwarding, and similar techniques can accelerate IO performance and reduce the impact of IO time to a compute application. Hybrid staging enhanced this path by adding processing functionality to locations along the data path to storage. While these efforts have been effective, they have taken a somewhat limited view of the potential benefits using some additional compute resources can offer both to enhance a compute application as well as to offering a way to exploit HPC-style resources for non-traditional tasks. Over the last few years, we have been experimenting with the potential for other sorts of activities using a staging style approach to add or enable new functionality. The efforts in this area have yielded a collection of small projects that yield some insights into both the potential and limitations of this approach for both achieving exascale computing and for enabling alternative uses for HPC resources.

Computer Science↗
DOE OSTI2015

Design and verification of a novel hollow vibrating module for laser machining

If a vibration module is added on laser machining system, the quality of surface finish and aspect ratio on metals can be significantly enhanced. In this study, a single mobility model of vibrating laser along the path of laser beam was put forward. In order to realize the desired unidirectional motion, a resonance type vibration module with optical lens was designed and manufactured. This cylindrical module was composed of curved-beam flexure elements. The cylindrical coordinate system was established to describe the relationship of a curved-beam flexure element’s motion and deformation. In addition, the stiffness matrix of the curved-beam element was obtained. Finite element method and dynamical modeling were provided to analyze the resonance frequency and the displacement of the motion. The feasibility of the design was demonstrated with the help of experiments on frequency response. Experimental results show good agreement with theoretical analysis and simulation predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Effect of realistic routing on the social burden metric

The distance people travel to reach critical services is a key input to the Social Burden metric used by Sandia’s Resilient Node Cluster Analysis Tool (ReNCAT) in the optimization’s objective function. By default, ReNCAT utilizes Euclidian distances between population blocks and critical facilities when calculating Social Burden. However, these straight-line distances do not reflect how most residents or goods would travel throughout the area. As distance is a vital input to the burden calculation, a more realistic distance calculation will yield more realistic burden values. This work uses real road networks and calculates the shortest distance path between population centers and critical facilities using a standard graph theory approach. These realistic route distances are then used to compute Social Burden for four areas of study. It was found that distances using real road routes are generally, but not always, longer than the Euclidean distance. The increased length increases the final Social Burden metric, however, the overall burden percent change ranged between 17% and 52%, which means the impact of realistic routes relies heavily upon the area’s road topology. It was found that rural locations within an area may have larger burden increases than urban areas as more dense road networks allow routes to more closely follow a straight-line path. Additionally, using the most straight forward routing algorithms requires high computational effort for areas with large road networks. While it is believed this process can be made more performant, that task is beyond this scope of work.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

EXTINCTION DROPLET SIZING MEASUREMENTS IN DIESEL RELEVANT SPRAYS

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination (DBI) imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path-integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced. This thesis aims to extend the initial development of the SAMR technique by presenting in detail: the experimental methodologies used in the SAMR technique, including the development of an ideal DBI setup for this technique; the data processing methodologies developed by the author; two-dimensional Sauter Mean Diameter measurements within diesel sprays for various experimental conditions; a summary of the various sources of measurement uncertainty; an assessment for how the sources of uncertainty affect the quantified SMD; and paths to improve the technique moving forward. The SMD results show that for low ambient density conditions droplets decrease in size as radial and axial position increases. For high ambient density conditions, however, the droplets show a stable size near the spray centerline and steadily increase in size as distance from the centerline increases. Additionally, this work provides 2-D droplet sizing maps which are particularly useful for model validation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

EXTINCTION DROPLET SIZING MEASUREMENTS IN DIESEL RELEVANT SPRAYS

A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination (DBI) imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path-integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial resolution of the corresponding droplet field. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced. This thesis aims to extend the initial developmen of SAMR technique by presenting in detail: the experimental methodologies used in the SAMR technique, including the development of an ideal DBI setup for this technique; the data processing methodologies developed by the author; two-dimensional Sauter Mean Diameter measurements within diesel sprays for various experimental conditions; a summary of the various sources of measurement uncertainty; an assessment for how the sources of uncertainty affect the quantified SMD; and paths to improve the technique moving forward. The SMD results show that for low ambient density conditions droplets decrease in size as radial and axial position increases. For high ambient density conditions, however, the droplets show a stable size near the spray centerline and steadily increase in size as distance from the centerline increases. Additionally, this work provides 2-D droplet sizing maps which are particularly useful for model validation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

HSNMon: High-Speed Monitoring Software for Omni-Path

HSNMon is a robust high speed network monitoring daemon that provides insight into network availability, hardware failure, and network performance for switches and network cards. HSNMon collects counters, forwarding tables, and error information at high resolution using publicly available Omni-Path Management APIs. The collected data can be forwarded into multiple logging infrastructures including syslog and message queuing systems. HSNMon is only the infrastructure for collecting the network data. It does not include any collected data or proprietary LANL information

Holman, Brett↗
DOE OSTI2017

Progress Report-Keystone 3

In the second quarter of FY2017, the focus of Keystone 3 was jointly on the establishment of methods for evaluation of high energy cells both electrochemically and through the use of advanced characterization techniques and resources, establishment of methods for the preparation of 1 Ah or larger cells, and use of different models to identify cell design parameters for achieving both 300 and 500 Wh/kg. These routes directly support the fourth quarter milestone in FY17 of achieving 300 Wh/kg and the ability to cycle the cell a minimum of 50 times. To facilitate discussions between the Keystone 3 team members biweekly meetings have been held to discuss path and to ensure progress is moving forward.

25 ENERGY STORAGE↗
DOE OSTI2020

SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

This work examines the frame-invariance (and the lack thereof) exhibited in simulated anisotropic elasto-plastic responses generated from supervised machine learning of classical multi-layer and informed-graph-based neural networks, and proposes different remedies to fix this drawback. The inherent hierarchical relations among physical quantities and state variables in an elasto-plasticity model are first represented as informed, directed graphs, where three variations of the graph are tested. While feed-forward neural networks are used to train path-independent constitutive relations (e.g., elasticity), recurrent neural networks are used to replicate responses that depends on the deformation history, i.e. or path dependent. In dealing with the objectivity deficiency, we use the spectral form to represent tensors and, subsequently, three metrics, the Euclidean distance between the Euler Angles, the distance from the identity matrix, and geodesic on the unit sphere in Lie algebra, can be employed to constitute objective functions for the supervised machine learning. In this, the aim is to minimize the measured distance between the true and the predicted 3D rotation entities. Following this, we conduct numerical experiments on how these metrics, which are theoretically equivalent, may lead to differences in the efficiency of the supervised machine learning as well as the accuracy and robustness of the resultant models. Neural network models trained with tensors represented in component form for a given Cartesian coordinate system are used as a benchmark. Our numerical tests show that, even given the same amount of information and data, the quality of the anisotropic elasto-plasticity model is highly sensitive to the way tensors are represented and measured. The results reveal that using a loss function based on geodesic on the unit sphere in Lie algebra together with an informed, directed graph yield significantly more accurate rotation prediction than the other tested approaches.

42 ENGINEERING↗
DOE OSTI2017

HELIOS vs. DRAGON – Code-to-Code Comparison for High Temperature Gas Reactors

Full core neutronics modeling for depletion and transient analysis in commercial and test reactors requires a lattice physics code to obtain material homogenized and energy group condensed cross- sections at an assembly level. These cross-sections are then used in a full-core model for depletion and transient analysis. HELIOS and DRAGON are two popular lattice physics codes that are capable of modeling the HTGR, which is not straight forward due to the large neutron mean free path in graphite, the presence of burnable poisons, proximity to reflectors, and the double heterogeneous nature of prismatic TRISO fuel. To understand on how HELIOS and DRAGON perform, a simple hexagonal fuel pin cell based on the MHTGR design was analyzed. In total, there are three benchmark cases, with each case increasing in complexity. These cases were selected to help distinguish and identify limitations and benefits of each reactor physics code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Flow control valve

Disclosed is a flow device including an inlet, an outlet, and a plurality of fluid flow paths hydraulically connected in parallel to the inlet and the outlet, wherein the plurality of fluid flow paths forms a first ring of fluid flow paths circumferentially arranged at a first radial distance from a centerline of the fluid flow device a second ring of fluid flow patch circumferentially arranged at a second radial distance from the centerline of the fluid flow device, each of the plurality of fluid flow paths has a first hydraulic resistance in a forward flow direction and a second hydraulic resistance in a reverse flow direction, and the second hydraulic resistance is greater than the first hydraulic resistance.

Siebert, Brett W.↗
DOE OSTI2018

Unraveling electronic absorption spectra using nuclear quantum effects: Photoactive yellow protein and green fluorescent protein chromophores in water

Many physical phenomena must be accounted for to accurately model solution-phase optical spectra line shapes, from the sampling of chromophore-solvent configurations to the electronic-vibrational transitions leading to vibronic fine structure. Here we thoroughly explore the role of nuclear quantum effects, direct and indirect solvent effects, and vibronic effects in the computation of the optical spectrum of the aqueously solvated anionic chromophores of green fluorescent protein (GFP) and photoactive yellow protein (PYP). By analyzing the chromophore and solvent configurations, the distributions of vertical excitation energies, the absorption spectra computed within the ensemble approach, and the absorption spectra computed within the ensemble plus zero-temperature Franck-Condon approach, we introduce how solvent, nuclear quantum effects, and vibronic transitions alter the optical absorption spectra. We discover that including nuclear quantum effects in the sampling of chromophore-solvent configurations using ab initio path integral molecular dynamics simulations leads to improved spectral shapes through three mechanisms. The three mechanisms that lead to line shape broadening and a better description of the high-energy tail are softening of heavy atom bonds in the chromophore that couple to the optically bright state, widening the distribution of vertical excitation energies from more diverse solvation environments, and redistributing spectral weight from the 0-0 vibronic transition to higher energy vibronic transitions when computing the Franck-Condon spectrum in a frozen solvent pocket. The absorption spectra computed using the combined ensemble plus zero-temperature Franck-Condon approach yield significant improvements in spectral shape and width compared to spectra computed with the ensemble approach. Using the combined approach with configurations sampled from path integral molecular dynamics trajectories presents a significant step forward in accurately modeling the absorption spectra of aqueously solvated chromophores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Summer term 2018 work with IMC radiative transport in binary stochastic media

In the quest for new and improved methods to solve thermal radiation transport in stochastic media, this summer project was to characterize radation transport in a deterministic lattice problem that represents a real, binary stochastic media. A representative geometry for a binary stochastic media consisting of a cube of a high volume fraction media containing constant-diameter non-overlappying spheres randomly distributed within was run previously. Previous thermal radiation wave problems in binary stochastic media displayed three characteristic thermal energy deposition wavefronts in the following order, front of the spheres, bulk material, and the backs of the spheres. Several physical aspects of the representative geometry for a stochastic binary media using an optically thin background with optically thick spheres were analyzed. This analysis includes wave speed propagation using a one dimensional diffusion approximation, energy fluence transmission, and material energy deposition. The approaches to analysis included representing one sphere of the high opacity material in a diffusive background of the low opacity material, as well as repeating spheres in a column con guration with reflective boundary conditions to approximate a lattice. Additionally, both atomic mix and Levermore-Pomraning homogenization schemes were compared against the representative cube geometry as well as the sphere column lattice geometry. The wave speed analysis with a one dimensional Marshak diffusion wave was largely ineffective at determining an effective opacity value to which a problem could be homogenized, likely due to low mean free path resolution within the problem. However, the sphere column lattice geometry showed promising results for approximating the energy fluence transmitted through the problem domain. One concern with the sphere column lattice geometry indicated the high forward-bias effect of fluence reaching the problem boundary due to streaming paths around the spheres in the case of small mean free path resolution of the background material.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Beyond Hosting Capacity: Using Shortest-Path Methods to Minimize Upgrade Cost Pathways

This paper presents a graph-based forward looking algorithm applied to distribution planning in the context of distributed photovoltaic penetration. We study the target hosting capacity problem where the objective is to find the least-cost sequence of system upgrades to reach a predefined hosting capacity target value. We show that commonly used short-term cost minimization approaches often lead to suboptimal long-term solutions. By comparing our method against such myopic techniques on real distribution systems, we show that our algorithm is able to reduce the overall integration costs by looking at future decisions. Because hosting capacity is hard to compute, this problem requires efficient methods to search the space. We demonstrate that heuristics using domain-specific knowledge can be efficiently used to improve the algorithm performance, such that real distribution systems can be studied.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

SSAGES: Software Suite for Advanced General Ensemble Simulations

Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods, and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques—including adaptive biasing force, string methods, and forward flux sampling—that extract meaningful free energy and transition path data from all-atom and coarse grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this study, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Identifying the Root Causes of Wait States in Large-Scale Parallel Applications

Driven by growing application requirements and accelerated by current trends in microprocessor design, the number of processor cores on modern supercomputers is increasing from generation to generation. However, load or communication imbalance prevents many codes from taking advantage of the available parallelism, as delays of single processes may spread wait states across the entire machine. Moreover, when employing complex point-to-point communication patterns, wait states may propagate along far-reaching cause-effect chains that are hard to track manually and that complicate an assessment of the actual costs of an imbalance. Building on earlier work by Meira Jr. et al., we present a scalable approach that identifies program wait states and attributes their costs in terms of resource waste to their original cause. Ultimately, by replaying event traces in parallel both forward and backward, we can identify the processes and call paths responsible for the most severe imbalances even for runs with hundreds of thousands of processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Ground-Based Remote Retrievals of Cumulus Entrainment Rates

While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available data sets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the United States Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility as inputs into a Gauss-Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled liquid water path and cloud droplet effective radius to their observed counterparts. The forward model in this algorithm is the Explicit Mixing Parcel Model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for measurement uncertainty is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on three months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km-¹ for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.

Wagner, Timothy J.↗