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

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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Parallelizable microfluidic dropmakers with multilayer geometry for the generation of double emulsions

Microfluidic devices enable the production of uniform double emulsions with control over droplet size and shell thickness. However, the limited production rate of microfluidic devices precludes the use of monodisperse double emulsions for industrial-scale applications, which require large quantities of droplets. To increase throughput, devices can be parallelized to contain many dropmakers operating simultaneously in one chip, but this is challenging to do for double emulsion dropmakers. Production of double emulsions requires dropmakers to have both hydrophobic and hydrophilic channels, requiring spatially precise patterning of channel surface wettability. Precise wettability patterning is difficult for devices containing multiple dropmakers, posing a significant challenge for parallelization. In this paper, we present a multilayer dropmaker geometry that greatly simplifies the process of producing microfluidic devices with excellent spatial control over channel wettability. Wettability patterning is achieved through the independent functionalization of channels in each layer prior to device assembly, rendering the dropmaker with a precise step between hydrophobic and hydrophilic channels. We report this device geometry enables uniform wettability patterning of parallelized dropmakers, providing a scalable approach for the production of double emulsions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optically tunable mesoscale CdSe morphologies via inorganic phototropic growth

Inorganic phototropic growth using only spatially conformal illumination generated Se–Cd films that exhibited precise light-defined mesoscale morphologies including highly ordered, anisotropic, and periodic ridge and trench nanotextures over entire macroscopic substrates. Growth was accomplished via a light-induced electrochemical method using an optically and chemically isotropic solution, an unpatterned substrate, and unstructured, incoherent, low-intensity illumination in the absence of chemical directing agents or physical templates and masks. The morphologies were defined by the illumination inputs: the nanotexture long axes aligned parallel to the optical E-field vector, and the feature sizes and periods scaled with the wavelength. Optically based modeling of the growth closely reproduced the experimental results, confirming the film morphologies were fully determined by the light–matter interactions during growth. Solution processing of the Se–Cd films resulted in stoichiometric, crystalline CdSe films that also exhibited ordered nanotextures, demonstrating that inorganic phototropic growth can effect tunable, template-free generation of ordered CdSe nanostructures over macroscopic length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The reduction of magnetic reconnection outflow jets to sub-Alfvénic speeds

The outflow velocity of jets produced by collisionless magnetic reconnection is shown to be reduced by the ion exhaust temperature in fully kinetic particle in cell simulations and in situ satellite observations. We derive a scaling relationship for the outflow velocity based on the upstream Alfvén speed and the parallel ion exhaust temperature, which is verified in kinetic simulations and observations. The outflow speed reduction is shown to be due to the firehose instability criterion, and so, for large enough guide fields, this effect is suppressed and the outflow speed reaches the upstream Alfvén speed based on the reconnecting component of the magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Island model for parallel evolutionary optimization of spiking neuromorphic computing

Parallel genetic algorithms (PGAs) can be used to accelerate optimization by exploiting large-scale computational resources. In this work, we describe a PGA framework for evolving spiking neural networks (SNNs) for neuromorphic hardware implementation. The PGA framework is based on an islands model with migration. We show that using this framework, better SNNs for neuromorphic systems can be evolved faster.

Schuman, Catherine↗
DOE OSTI2018

In Situ Indexing and Query Processing of AMR Data

We have developed the first, holistic, Adaptive Mesh Refinement (AMR) capable, in situ query framework to ensure the tractability of the current- and next-generation AMR simulation analysis on the path to extreme scale. We have addressed key issues pertaining to in situ analysis, memory hierarchy, generalized parallel indexing, index-compression, and real-time access pattern detection. We have published the following research papers in high profile peer reviewed computer science conferences: (a) Parallel In Situ Detection of Connected Components in Adaptive Mesh Refinement Data; (b) AMR-aware In Situ Indexing and Scalable Querying; (c) Pattern-driven dynamic data layout optimization; (d) In situ Storage Layout Optimization for AMR Spatio-temporal Read Accesses; (e) AMRZone: A Runtime AMR Data Sharing Framework for Scientific Applications; (f) Exploring Memory Hierarchy and Network Topology for Runtime AMR Data Sharing Across Scientific Applications.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

A Parallel Computing Infrastructure for Building Energy Simulation

In order to study grid-interactive efficient buildings, Pacific Northwest National Laboratories (PNNL) needs an infrastructure for urban-scale building energy modeling. Such an infrastructure should be fast, scalable, and easy-to-use. Given a set of data from the Energy Information Administration’s Commercial Building Energy Consumption Survey (CBECS) and tool to translate survey data into simulation inputs, this project aimed to conduct the simulation of the entire dataset in parallel. Before running the simulations, the necessary software was bundled into a container for use on the PNNL supercomputing network. Then, the parallel simulation workflow was designed using GNU Make, a file creation software, and submitted to a supercomputing partition which could run hundreds of simulations simultaneously. The EnergyPlus simulations output hourly electric meter data for each CBECS sample, which represents the electricity consumption of similar commercial buildings across the United States. Analyzing and visualizing the meter data is important to the future of the work, and this project wrote code to make common analysis methods simple, fast, and accessible. Moving forwards, the model will need to be expanded to include data from other sources and its accuracy will need to be improved and eventually validated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1978

Cryogenic liquid-level detector

Detector is designed for quick assembly, fast response, and good performance under vibratory stress. Its basic parallel-plate open configuration can be adapted to any length and allows its calibration scale factor to be predicted accurately. When compared with discrete level sensors, continuous reading sensor was found to be superior if there is sloshing, boiling, or other disturbance.

Hamlet, J.↗
NASA NTRS1993

A class of hybrid finite element methods for electromagnetics: A review

Integral equation methods have generally been the workhorse for antenna and scattering computations. In the case of antennas, they continue to be the prominent computational approach, but for scattering applications the requirement for large-scale computations has turned researchers' attention to near neighbor methods such as the finite element method, which has low O(N) storage requirements and is readily adaptable in modeling complex geometrical features and material inhomogeneities. In this paper, we review three hybrid finite element methods for simulating composite scatterers, conformal microstrip antennas, and finite periodic arrays. Specifically, we discuss the finite element method and its application to electromagnetic problems when combined with the boundary integral, absorbing boundary conditions, and artificial absorbers for terminating the mesh. Particular attention is given to large-scale simulations, methods, and solvers for achieving low memory requirements and code performance on parallel computing architectures.

Volakis, J. L.↗
NASA NTRS1996

The " Swarm of Ants vs. Herd of Elephants" Debated Revisited: Performance Measurements of PVM-Overflow Across a Wide Spectrum of Architectures

The Gorden Bell Prizes given out at Supercomputing every year includes at least two catergories: performance (highest GFLOP count) and price-performance (GFLOP/million $$) for real applications. In the past five years, the winners of the price-performance categories all came from networks of work-stations. This reflects three important facts: 1. supercomputers are still too expensive for the masses; 2. achieving high performance for real applications takes real work; and, most importantly; 3. it is possible to obtain acceptable performance for certain real applications on network of work stations. With the continued advance of network technology as well as increased performance of "desktop" workstation, the "Swarm of Ants vs. Herd of Elephants" debate, which began with vector multiprocessors (VPPs) against SIMD type multiprocessors (e.g. CM2), is now recast as VPPs against Symetric Multiprocessors (SMPs, e.g. SGI PowerChallenge). This paper reports on performance studies we performed solving a large scale (2-million grid pt.s) CFD problem involving a Boeing 747 based on a parallel version of OVERFLOW that utilizes message passing on PVM. A performance monitoring tool developed under NASA HPCC, called AIMS, was used to instrument and analyze the the performance data thus obtained. We plan to compare its performance data obtained across a wide spectrum of architectures including: the Cray C90, IBM/SP2, SGI/Power Challenge Cluster, to a group of workstations connected over a simple network. The metrics of comparison includes speed-up, price-performance, throughput, and turn-around time. We also plan to present a plan of attack for various issues that will make the execution of Grand Challenge Applications across the Global Information Infrastructure a reality.

Yan, Jerry C.↗
NASA NTRS2001

Arthropod phylogeny based on eight molecular loci and morphology

The interrelationships of major clades within the Arthropoda remain one of the most contentious issues in systematics, which has traditionally been the domain of morphologists. A growing body of DNA sequences and other types of molecular data has revitalized study of arthropod phylogeny and has inspired new considerations of character evolution. Novel hypotheses such as a crustacean-hexapod affinity were based on analyses of single or few genes and limited taxon sampling, but have received recent support from mitochondrial gene order, and eye and brain ultrastructure and neurogenesis. Here we assess relationships within Arthropoda based on a synthesis of all well sampled molecular loci together with a comprehensive data set of morphological, developmental, ultrastructural and gene-order characters. The molecular data include sequences of three nuclear ribosomal genes, three nuclear protein-coding genes, and two mitochondrial genes (one protein coding, one ribosomal). We devised new optimization procedures and constructed a parallel computer cluster with 256 central processing units to analyse molecular data on a scale not previously possible. The optimal 'total evidence' cladogram supports the crustacean-hexapod clade, recognizes pycnogonids as sister to other euarthropods, and indicates monophyly of Myriapoda and Mandibulata.

Non-NASA Center↗
DOE OSTI2021

Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence

We use a stable parallel approach to train Wasserstein Conditional Generative Adversarial Neural Networks (W-CGANs). The parallel training reduces the risk of mode collapse and enhances scalability by using multiple generators that are concurrently trained, each one of them focusing on a single data label. The use of the Wasserstein metric reduces the risk of cycling by stabilizing the training of each generator. We apply the approach on the CIFAR10 and the CIFAR100 datasets, two standard benchmark datasets with images of the same resolution, but different number of classes. Performance is assessed using the inception score, the Fréchet inception distance, and image quality. An improvement in inception score and Fréchet inception distance is shown in comparison to previous results obtained by performing the parallel approach on deep convolutional conditional generative adversarial neural networks (DC-CGANs). Weak scaling is attained on both datasets using up to 100 NVIDIA V100 GPUs on the OLCF supercomputer Summit.

Lupo Pasini, Massimiliano↗
DOE OSTI2025

Real-Time Bayesian Inference at Extreme Scale: A Digital Twin for Tsunami Early Warning Applied to the Cascadia Subduction Zone

We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic–gravity wave equations, to infer earthquake-induced spatiotemporal seafloor motion in real time and forecast tsunami propagation toward coastlines for early warning with quantified uncertainties. Our target is the Cascadia subduction zone, with one billion parameters. Computing the posterior mean alone would require 50 years on a 512 GPU machine. Instead, exploiting the shift invariance of the parameter-to-observable map and devising novel parallel algorithms, we induce a fast offline–online decomposition. The offline component requires just one adjoint wave propagation per sensor; using MFEM, we scale this part of the computation to the full El Capitan system (43,520 GPUs) with 92% weak parallel efficiency. Moreover, given real-time data, the online component exactly solves the Bayesian inverse and forecasting problems in 0.2 seconds on a modest GPU system, a ten-billion-fold speedup.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Cyclotron breaking: a mechanism for parallel ion cyclotron waves to heat the fast solar wind

The Parker Solar Probe mission has observed near-continuous power in parallel ion cyclotron waves (PICWs) in the young, fast solar wind. These waves are unlikely to be directly produced by the turbulent cascade and are likely born of a local instability; yet, they are observed to both cool – and heat – the plasma. We propose that these observations can be self-consistently explained as the natural consequence of PICWs propagating in the inhomogeneous solar wind after they have been driven unstable. In this work, we argue that strong proton heating by a turbulent cascade of oblique ICWs will result in PICWs being driven unstable in a process known as quasi-linear focusing. Because the power in the turbulent cascade is concentrated at scales above the turbulent transition region, PICWs will be driven unstable within a range of wavenumbers parallel to the background magnetic field, 𝑘 ∥ , that is bounded from above by 𝑘$^{∗}_{∥P}$, corresponding to the start of the transition region. As unstable PICWs propagate away from the Sun to regions of lower proton density, their 𝑘 ∥ , multiplied by the proton inertial length 𝑑 p , increases. Eventually, 𝑘$^{∗}_{∥P}$ of the PICWs becomes larger than 𝑘$^{∗}_{∥P}$⁢𝑑 p and the waves damp, heating the solar wind. We call this effect ‘cyclotron breaking’, in analogy with ocean waves breaking on the shore. We then discuss the testable predictions of the theory, including a distinct heating signature in which PICWs cool fast protons and heat slow protons at any given heliocentric distance 𝑟. Finally, we conjecture that cyclotron breaking can lead to net heating by PICWs if the power emitted as PICWs decreases sufficiently rapidly with 𝑟 that local emission of PICWs is overwhelmed by the local damping of PICWs generated closer to the Sun.

plasma heating↗
DOE OSTI2025

Low-Energy Backgrounds in Solid-State Phonon and Charge Detectors

Solid-state phonon and charge detectors probe the scattering of weakly interacting particles, such as dark matter and neutrinos, through their low recoil thresholds. Recent advancements have pushed sensitivity to eV-scale energy depositions, uncovering previously unseen low-energy excess backgrounds. While some arise from known processes such as thermal radiation, luminescence, and stress, others remain unexplained. This review examines these backgrounds, their possible origins, and parallels to low-energy effects in solids, an understanding of which is essential for interpreting particle interactions at and below the eV scale.

coherent neutrino–nucleus scattering↗
DOE OSTI2025

Direct numerical simulations for hybrid rocket boundary layers: Performance modeling and scaling

This paper presents a comprehensive performance and scaling analysis of direct numerical simulations for reacting boundary layers, focusing on slab burner configurations. Using a PETSc-based finite volume CFD framework, the study evaluates the scalability and computational cost of flow, chemistry, and radiation evaluations across 2D and 3D simulations. Polymethyl methacrylate (PMMA) is the fuel with pure O 2 as the oxidizer, modeled using a detailed chemical kinetics mechanism with 113 species and 660 reactions. A ray-tracing-based radiation solver, designed for distributed memory applications, is implemented to model radiation heat transfer. Parallel scalability is analyzed for the coupled flow, chemistry, and radiation heat transfer processes. Weak and strong scaling studies are conducted on up to 15,000 computational ranks, revealing robust performance when flow cells exceed 200 per rank. Chemistry evaluations dominate the computational cost in large 3D simulations, accounting for approximately 40% of the total runtime, while flow processes contribute around 35%, and radiation solver contributions remain below 10% due to reduced evaluation frequencies. GPU accelerated chemistry evaluation, implemented with Zero-RK, demonstrates significant promise, achieving up to a 4x speedup for workloads exceeding 30,000 cells per GPU. However, diminishing returns are observed for smaller workloads due to CPU-GPU communication overhead. This study identifies key challenges, including memory bottlenecks and the effects of domain partitioning on flow scalability, while highlighting the potential of GPU-accelerated chemistry to reduce computational costs. In conclusion, these findings provide realizable run configurations for 2D, 3D, and GPU-accelerated cases, offering insights for optimizing reactive flow solvers.

CFD Scalability↗
DOE OSTI2017

Mixed Presence Collaboration using Scalable Visualizations in Heterogeneous Display Spaces

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronized sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.

data-conferencing↗
DOE OSTI2017

Parasitic momentum flux in the tokamak core

A geometrical correction to the E × B drift causes an outward flux of co-current momentum whenever electrostatic potential energy is transferred to ion parallel flows. The robust, fully nonlinear symmetry breaking follows from the free-energy flow in phase space and does not depend on any assumed linear eigenmode structure. The resulting rotation peaking is counter-current and scales as temperature over plasma current. Lastly, this peaking mechanism can only act when fluctuations are low-frequency enough to excite ion parallel flows, which may explain some recent experimental observations related to rotation reversals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗