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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimization and Experimental Validation of Annular Finned PCM-HX for a Domestic Hot Water Heater Application

The load profile for domestic water heating is time-dependent and can result in high energy demand during peak operating times. Shifting this peak load can have significant environmental and economic impacts. Phase change material (PCM)-based thermal energy storage (TES) is a potentially useful technology for peak load shifting in domestic hot water (DHW) applications thanks to its high latent heat and energy density. In this study, an annular finned-tube PCM-HX design concept was optimized for a load-shifting TES unit to meet the Department of Energy standard for a medium-usage DHW heater using a resistance-capacitance model (RCM) integrated with a Multi-Objective Genetic Algorithm. The optimized design comprised 70 identical annular finned-tube PCM-HX units connected in parallel and utilizing RT62HC as the PCM. A single PCM-HX unit was prototyped and tested in a vertically oriented setup with upward heat transfer fluid (HTF) flow. The hot water supply time was defined based on a cutoff temperature of 51.7°C. The as-designed mass flow rate (1.5 g/s) was tested to assess the performance of the prototyped PCM-HX unit for RCM validation. For the experimental investigation, RTD sensor bundles measured HTF temperature at the PCM-HX inlet and outlet, and a Coriolis flow meter accurately measured the HTF mass flow rate. The simulated discharging power underpredicted the experimental result by about 12%, and the simulated hot water supply time underpredicted the experimental result by approximately 13% for the as-designed mass flow rate (1.5 g/s). The average deviation of the hot water supply temperature between the experimental and RCM results during the complete PCM solidification process was 1.3 K for the as-designed mass flow rate. The overall good agreement between the experimental and RCM results provides confidence that computationally efficient models such as RCM can be utilized for design optimization of PCM-HXs.

42 ENGINEERING↗
DOE OSTI2015

Arbitrarily High-Order-Accurate, Hermite WENO Limited, Boundary-Averaged Multi-Moment Constrained Finite-Volume (BA-MCV) Schemes for 1-D Transport

This study introduces the Boundary Averaged Multi-moment Constrained finite-Volume (BA- MCV) scheme for 1-D transport with Hermite Weighted Essentially Non-Oscillatory (HWENO) limiting using the ADER Differential Transform (ADER-DT) time discretization. The BA- MCV scheme evolves a cell average using a Finite-Volume (FV) scheme, and it adds further constraints as point wise derivatives of the state at cell boundaries, which are evolved in strong form using PDE derivatives. The resulting scheme maintains a Maximum Stable CFL (MSCFL) value of one no matter how high-order the scheme is. Also, parallel communication requirements are very low and will be described. h-refinement experiments demonstrate proper convergence order, and p-refinement experiments demonstrate expected exponential convergence. The over- all ADER-DT + BA-MCV + HWENO scheme is a scalable and larger time step alternative to Galerkin methods for multi-moment fluid simulation in climate and weather applications.

Norman, Matthew↗
DOE OSTI2023

Evaluation of Impedance Measurement Using Spread Spectrum Time Domain Reflectometry

We evaluate the feasibility of spectral time domain reflectometry (STDR) and spread spectrum time domain reflectometry (SSTDR) as a new modality for impedance measurement to test energized/noisy systems over a very broad frequency spectrum (near dc to gigahertz) as well as multiple channels in parallel. We simulate how the S/SSTDR signal parameters (signal-to-noise ratio (SNR) frequency and length of the pseudo-noise (PN) signals) affect the accuracy and usable frequency band for reflection coefficient and impedance measurement. An initial measurement validation is included. Here, we conclude with a recommendation of what will be required for a viable multichannel impedance (and reflection, transmission coefficient) measurement system for either energized or nonenergized systems, in noisy environments, that can test multiple channels simultaneously.

14 SOLAR ENERGY↗
DOE OSTI2016

THE ROLE OF QUENCHING TIME IN THE EVOLUTION OF THE MASS–SIZE RELATION OF PASSIVE GALAXIES FROM THE WISP SURVEY

We analyze how passive galaxies at z ∼ 1.5 populate the mass–size plane as a function of their stellar age, to understand if the observed size growth with time can be explained with the appearance of larger quenched galaxies at lower redshift. We use a sample of 32 passive galaxies extracted from the Wide Field Camera 3 Infrared Spectroscopic Parallel (WISP) survey with spectroscopic redshift 1.3 ≲ z ≲ 2.05, specific star formation rates lower than 0.01 Gyr{sup −1}, and stellar masses above 4.5 × 10{sup 10} M {sub ⊙}. All galaxies have spectrally determined stellar ages from fitting of their rest-frame optical spectra and photometry with stellar population models. When dividing our sample into young (age ≤2.1 Gyr) and old (age >2.1 Gyr) galaxies we do not find a significant trend in the distributions of the difference between the observed radius and that predicted by the mass–size relation. This result indicates that the relation between the galaxy age and its distance from the mass–size relation, if it exists, is rather shallow, with a slope α ≳ −0.6. At face value, this finding suggests that multiple dry and/or wet minor mergers, rather than the appearance of newly quenched galaxies, are mainly responsible for the observed time evolution of the mass–size relation in passive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Large Scale Caching and Streaming of Training Data for Online Deep Learning

The training of deep neural network models on large data remains a difficult problem, despite progress towards scalable techniques. In particular, there is a mismatch between the random but predetermined order in which AI flows select training samples and the streaming I/O patterns for which traditional HPC data storage (e.g., parallel file systems) are designed. In addition, as more data are obtained, it is feasible neither simply to train learning models incrementally, due to catastrophic forgetting (i.e., bias towards new samples), nor to train frequently from scratch, due to prohibitive time and/or resource constraints. In this paper, we study data management techniques that combine caching and streaming with rehearsal support in order to enable efficient access to training samples in both offline training and continual learning. We revisit state-of-art streaming approaches based on data pipelines that transparently handle prefetching, caching, shuffling, and data augmentation, and discuss the challenges and opportunities that arise when combining these methods with data-parallel training techniques. We also report on preliminary experiments that evaluate the I/O overheads involved in accessing the training samples from a parallel file system (PFS) under several concurrency scenarios, highlighting the impact of the PFS on the design of the data pipelines.

data pipelines↗
DOE OSTI2016

CTF Parallel Performance Improvements

CTF is a modernized version of COBRA-TF (Coolant Boiling in Rod Arrays-Two Fluid), which is a thermal hydraulic (T/H) sub-channel code based on a two-phase, two-fluid model that formulates the conservation equations of mass, energy, and momentum for three fields of vapor, continuous liquid, and entrained liquid droplets. Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program sponsored by the U.S. Department of Energy, CTF is being further developed and improved for modeling and simulation of light water reactors. The code improvements for predicting T/H responses of pressurized water reactor (PWR) cores are focused on its applications to specific challenge problems deemed significant to the industry, such as departure from nucleate boiling (DNB) and crud-induced power shift. The code is also being used for T/H feedback in normal operating condition depletions in PWR and boiling water reactor designs in the reactor core simulator, Virtual Environment for Reactor Applications Core Simulator (VERA-CS), being developed by CASL. CTF modifications under the CASL program include software optimization, new closure models, and parallelization for modeling full reactor core T/H responses. The purpose of this work was to improve the parallel performance of CTF. CTF was originally parallelized via a domain-decomposition strategy using the Message Passing Interface (MPI), in which the basis of a solution domain was a physical assembly in the model. In other words, a user who wanted to perform a parallel solution with CTF had to provide the code one processor per assembly in the model (e.g., 56 cores for a 56 assembly quarter-core model, or 193 cores for a 193 assembly full-core model). This design was rigid, demanding a very specific number of processors for a model; furthermore, when CTF was run in VERA-CS-which typically uses thousands of processors- many processors sat idle during the CTF solve because CTF was unable to use any more processors than there are physical assemblies. This was not necessarily a problem if the CTF execution speed was very fast, but the average time spent in a CTF solve for prototypical PWR operating conditions was significant (i.e., over 20 % of the simulation wall time was being spent in CTF for a standard core depletion simulation). Larger, more computationally intensive simulations performed in support of the CASL DNB challenge problem demonstrated a need for improvements in this original parallelization approach. The specific goal of this work was to allow CTF to use more processors than there are physical assemblies in the model, which would not only speed up CTF and improve the overall efficiency of VERA-CS but also give users more-flexible options for executing their simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Isolation and characterization of neural stem cells from dystrophic mdx mouse

The blood-brain barrier (BBB) is altered in mdx mouse, an animal model to study Duchenne muscular dystrophy (DMD). Our previous work demonstrated that perivascular glial endfeet control the selective exchanges between blood and neuropil as well as the BBB development and integrity; the alterations of dystrophin and dystrophin-associated protein complex (DAPs) in the glial cells of mdx mouse, parallel damages of the BBB and increase in vascular permeability. The aim of this study was to improve our knowledge about brain cellular components in the mdx mouse through the isolation, for the first time, of the adult neural stem cells (ANSCs). We characterized them by FACS, electron microscopy, confocal immunofluorescence microscopy, Real Time-PCR and western blotting, and we studied the expression of the DAPs aquaporin-4 (AQP4), potassium channel Kir4.1, α- and β-dystroglycan (αDG, βDG), α-syntrophin (αSyn), and short dystrophin isoform Dp71 proteins. The results showed that the mdx ANSCs expressed CD133 and Nestin receptor as the control ones, but showed a reduction in Notch receptor and altered cell proliferation with an increment in the apoptotic nuclei. Ultrastructurally, they appeared 50% size reduced compared to control ones, with a few cytoplasmic organelles. Moreover, the mdx ANSCs are devoid in full length dystrophin 427, and they expressed post-transcriptional reduction in the Dp71 in parallel with the ubiquitin proteasome activation, and decrement of DAPs proteins which appeared diffused in the cytoplasm and not polarized on the stem cells plasmamembrane, as prevalently observed in the controls. Overall, these results indicate that structural and molecular alterations affect the neural stem cells in the dystrophic brain, whose increased apoptosis and reduced Dp71 and DAPs proteins expression, together with loss in Dp427 dystrophin, could be responsible of the altered mdx glial maintenance and differentiation and consequent failure in the vessels barrier control occurring in the adult dystrophic brain.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A scalable nonlinear fluid–structure interaction solver based on a Schwarz preconditioner with isogeometric unstructured coarse spaces in 3D

Nonlinear fluid-structure interaction (FSI) problems on unstructured meshes in 3D appear many applications in science and engineering, such as vibration analysis of aircrafts and patient-specific diagnosis of cardiovascular diseases. In this work, we develop a highly scalable, parallel algorithmic and software framework for FSI problems consisting of a nonlinear fluid system and a nonlinear solid system, that are coupled monolithically. The FSI system is discretized by a stabilized finite element method in space and a fully implicit backward difference scheme in time. To solve the large, sparse system of nonlinear algebraic equations at each time step, we propose an inexact Newton-Krylov method together with a multilevel, smoothed Schwarz preconditioner with isogeometric coarse meshes generated by a geometry preserving coarsening algorithm. Here ''geometry'' includes the boundary of the computational domain and the wet interface between the fluid and the solid. We show numerically that the proposed algorithm and implementation are highly scalable in terms of the number of linear and nonlinear iterations and the total compute time on a supercomputer with more than 10,000 processor cores for several problems with hundreds of millions of unknowns.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Multiple Fused Ring-Based Near-Infrared Nonfullerene Acceptors with an Interpenetrated Charge-Transfer Network

Two small molecule acceptors with chlorinated IC as end groups and 10-ring- and 12-ring-fused cores as central units, named R10-4Cl and R12-4Cl, were designed and synthesized, which exhibit low optical band gaps of 1.43 and 1.35 eV, respectively. X-ray crystallographic analysis of R10-4Cl shows that the end groups of adjacent molecules are parallel and partially overlap with a short π-π distance of 3.32 Å, which is helpful for electron transport in this direction. At the same time, there is another type of molecular orientation that lies in these two molecules with an angle about 64.7 degrees because of the close contact of S ∙∙∙ O with a distance of 3.15 Å. The two types of molecular arrangements result in an interpenetrated network structure in R10-4Cl films, which is helpful for the rapid charge transfer either along the horizontal direction or the sloping direction. After blending with a PBDB-T polymer donor, the R10-4Cl-based device shows wide photocurrent response from the visible to near-infrared regions, resulting in the better usage of the sunlight source. Benefited from this comprehensive solar energy absorption and the interpenetrated charge transfer, the R10-4Cl-based devices show a power conversion up to 10.7% with an improved J SC of 18.9 mA cm -2 .

14 SOLAR ENERGY↗
DOE OSTI2022

Ponderomotive force driven density modifications parallel to B on the LAPD

The ponderomotive force has previously been identified as a possible driver of observed density modifications close to radio frequency actuators during operation. This nonlinear force redistributes density in regions of gradients in the magnitude of an oscillating electric field and describes the influence of the fast time scale RF wave dynamics on slow time scale plasma transport. Depletion of the saturation current (a proxy for the density) measured at the Large Plasma Device (LAPD) was 30–35% during ion cyclotron range of frequencies operation. A coupled 1D plasma transport and cold plasma frequency domain wave solver was developed to self-consistently describe ponderomotive effects and was used to compare with results obtained from the LAPD experiment. The scaled current density driver for the wave model yielded an RF B field in close agreement with two components of the experimental data. However, the 1D parallel model did not accurately reproduce the amplitude or spatial distribution observed in experimental measurements of By. Within the limitations of the 1D model, initial simulation results showed that the ponderomotive force depleted up to 8% for high power (1 MW) and around 1% for the experimental power of 120 kW. This could suggest that the ponderomotive force is not the main driver of density modification for the LAPD experiments presented in this paper. Higher fidelity tools of at least 2D will be required to give a more realistic description of the RF E fields and the effect of the ponderomotive force on the LAPD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Entanglement engineering of optomechanical systems by reinforcement learning

Entanglement is fundamental to quantum information science and technology, yet controlling and manipulating entanglement—so-called entanglement engineering—for arbitrary quantum systems remains a formidable challenge. There are two difficulties: the fragility of quantum entanglement and its experimental characterization. We develop a model-free deep reinforcement-learning (RL) approach to entanglement engineering, in which feedback control together with weak continuous measurement and partial state observation is exploited to generate and maintain desired entanglement. We employ quantum optomechanical systems with linear or nonlinear photon–phonon interactions to demonstrate the workings of our machine-learning-based entanglement engineering protocol. In particular, the RL agent sequentially interacts with one or multiple parallel quantum optomechanical environments, collects trajectories, and updates the policy to maximize the accumulated reward to create and stabilize quantum entanglement over an arbitrary amount of time. The machine-learning-based model-free control principle is applicable to the entanglement engineering of experimental quantum systems in general.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SIMULATIONS OF THE SPATIAL AND TEMPORAL INVARIANCE IN THE SPECTRA OF GRADUAL SOLAR ENERGETIC PARTICLE EVENTS

The spatial and temporal invariance in the spectra of energetic particles in gradual solar events is reproduced in simulations. Based on a numerical solution of the focused transport equation, we obtain the intensity time profiles of solar energetic particles (SEPs) accelerated by an interplanetary shock in three-dimensional interplanetary space. The shock is treated as a moving source of energetic particles with a distribution function. The time profiles of particle fluxes with different energies are calculated in the ecliptic at 1 AU. According to our model, we find that shock acceleration strength, parallel diffusion, and adiabatic cooling are the main factors in forming the spatial invariance in SEP spectra, and perpendicular diffusion is a secondary factor. In addition, the temporal invariance in SEP spectra is mainly due to the effects of adiabatic cooling. Furthermore, a spectra invariant region, which agrees with observations but is different from the one suggested by Reames et al. is proposed based on our simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Stochastic optimization of GeantV code by use of genetic algorithms

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Evidence of the charge-density wave state in polypyrrole nanotubes

Here, we present a detailed investigation of the low-frequency dielectric and conductivity properties of conducting polymer nanowires. Our results, obtained by connecting ~10 7 nanowires in parallel, show that these polypyrrole nanowires behave like conventional charge-density wave (CDW) materials, in their nonlinear and dynamic response, together with scaling of relaxation time and conductivity. The observed Arrhenius law for both these quantities gives a CDW gap of 3.5 meV in the regime of temperature (~40 K) in which the CDW state survives. We find good agreement with a theory of weakly pinned CDW, screened by thermally excited carriers across the CDW gap. The identification of polymer nanowires as CDW provides us a model system to investigate charge ordering owing to electrostatic interaction, relevant to a variety of systems from dusty plasma to molecular biology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Efficient Delaunay Tessellation through K-D Tree Decomposition

Delaunay tessellations are fundamental data structures in computational geometry. They are important in data analysis, where they can represent the geometry of a point set or approximate its density. The algorithms for computing these tessellations at scale perform poorly when the input data is unbalanced. We investigate the use of k-d trees to evenly distribute points among processes and compare two strategies for picking split points between domain regions. Because resulting point distributions no longer satisfy the assumptions of existing parallel Delaunay algorithms, we develop a new parallel algorithm that adapts to its input and prove its correctness. We evaluate the new algorithm using two late-stage cosmology datasets. The new running times are up to 50 times faster using k-d tree compared with regular grid decomposition. Moreover, in the unbalanced data sets, decomposing the domain into a k-d tree is up to five times faster than decomposing it into a regular grid.

Morozov, Dmitriy↗
DOE OSTI2022

Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles

Visualizing the uncertainty of ensemble simulations is challenging due to the large size and multivariate and temporal features of en-semble data sets. One popular approach to studying the uncertainty of ensembles is analyzing the positional uncertainty of the level sets. Probabilistic marching cubes is a technique that performs Monte Carlo sampling of multivariate Gaussian noise distributions for positional uncertainty visualization of level sets. However, the technique suffers from high computational time, making interactive visualization and analysis impossible to achieve. This paper introduces a deep-learning-based approach to learning the level-set uncertainty for two-dimensional ensemble data with a multivariate Gaussian noise assumption. We train the model using the first few time steps from time-varying ensemble data in our workflow. We demonstrate that our trained model accurately infers uncertainty in level sets for new time steps and is up to 170X faster than that of the original probabilistic model with serial computation and 10X faster than that of the original parallel computation.

Han, Mengjiao↗
DOE OSTI2025

Deer Vigilance and Movement Behavior Are Affected by Edge Density and Connectivity

ABSTRACT Animal behavior is an important component of individual, population, and community responses to anthropogenic habitat alteration. For example, antipredator behavior (e.g., vigilance) and animal movement behavior may both be important behavioral responses to the increased density of habitat edges and changes in patch connectivity that characterize highly modified habitats. Importantly, edge density and connectivity might interact, and this interaction is likely to mediate animal behavior: linear, edge‐rich landscape features often provide structural connectivity between patches, but the functional connectedness of patches for animal use could depend upon how edge density modifies animal vigilance and movement. Using remote cameras in large‐scale experimental landscapes that manipulate edge density (high‐ vs. low‐density edges) and patch connectivity (isolated or connected patches), we examined the effects of edge density and connectivity on the antipredator behavior and movement behavior of white‐tailed deer ( Odocoileus virginianus ). Deer vigilance was 1.38 times greater near high‐density edges compared to low‐density edges, regardless of whether patches were connected or isolated. Deer were also more likely to move parallel to connected high‐density edges than all other edge types, suggesting that connectivity promotes movement along high‐density edges. These results suggest that increases in edge density that accompany human fragmentation of existing habitats may give rise to large‐scale changes in the antipredator behavior of deer. These results also suggest that conservation strategies that simultaneously manipulate edge density and connectivity (i.e., habitat corridors) may have multiple effects on different aspects of deer behavior: linear habitat corridors were areas of high vigilance, but also areas where deer movement behavior implied increased movement along the habitat edge.

Bartel, Savannah L. [University of Wisconsin‐Madis↗