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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Forensic Analysis of Faulted NSTX-U Inner Poloidal Field Coil

The failure of the NSTX-U PF1A upper coil suspended plasma operations during the project's first operational campaign after commissioning. Initial nondestructive testing and examination of the failed coil was followed by extensive nondestructive radiography. Destructive testing facilitated visual borescope/videoscope inspection through the cooling path, vacuum testing, and electrical testing of every conductor segment. One conductor cooling path visually evidenced a void through the sidewall of the cooling path in a layer-to-layer region. The identified void in the conductor cooling path was not proximal to a braze or joggle. Electrical testing indicated that the voided conductor segment was a member of a group of 14 conductor segments that evidenced low-resistance connectivity. Four braze joints and two lead segments were subjected to 400-lbf/in 2 hydrostatic pressure testing followed by helium leak testing and evidenced that there were no detectable leaks in the tested cooling path segments. The faulted region was proximal to the center of the coil pack and evidenced historical electrical pitting and molten conductor debris. Samples of the epoxy resin insulation system were extracted and analyzed with dynamic mechanical analysis and differential scanning calorimetry techniques. Epoxy resin insulation samples were subjected to immersion testing per ASTM D570. Metallurgical samples were extracted from the coil pack conductors and subjected to hardness testing and grain structure analysis. The base material testing results indicated no abnormalities. In conclusion, the coil incipient failure was determined to most likely have resulted from conductive material located between conductor and insulation layers.

25 ENERGY STORAGE↗
DOE OSTI2020

Multidecadal shifts in forest plant diversity and community composition across glacial landforms in northern lower Michigan, USA

Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. In this article, we tracked how diversity and composition are distributed through space and time in a midsuccessional mixed hardwood forest in northern lower Michigan, United States. This region’s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n = 87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n = 40). There were strong differences in diversity and community composition among glacial landforms, with the moraine having a 31% greater species richness in the groundcover layer compared with those of the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the 25-year period, and we found no evidence of differences in successional rates among glacial landforms. Our findings indicate that glacial landforms have a large influence on the production and maintenance of local plant diversity and community composition in this area and suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.

Forestry↗
DOE OSTI2019

The evolution of a super-swarm of foot-and-mouth disease virus in cattle

Foot-and-mouth disease (FMD) is a highly contagious viral disease that severely impacts global food security and is one of the greatest constraints on international trade of animal products. Extensive viral population diversity and rapid, continuous mutation of circulating FMD viruses (FMDVs) pose significant obstacles to the control and ultimate eradication of this important transboundary pathogen. The current study investigated mechanisms contributing to within-host evolution of FMDV in a natural host species (cattle). Specifically, vaccinated and non-vaccinated cattle were infected with FMDV under controlled, experimental conditions and subsequently sampled for up to 35 days to monitor viral genomic changes as related to phases of disease and experimental cohorts. Consensus-level genomic changes across the entire FMDV coding region were characterized through three previously defined stages of infection: early, transitional, and persistent. The overall conclusion was that viral evolution occurred via a combination of two mechanisms: emergence of full-genomic minority haplotypes from within the inoculum super-swarm, and concurrent continuous point mutations. Phylogenetic analysis indicated that individuals were infected with multiple distinct haplogroups that were pre-existent within the ancestral inoculum used to infect all animals. Multiple shifts of dominant viral haplotype took place during the early and transitional phases of infection, whereas few shifts occurred during persistent infection. Overall, this work suggests that the establishment of the carrier state is not associated with specific viral genomic characteristics. These insights into FMDV population dynamics have important implications for virus sampling methodology and molecular epidemiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Final Technical Report: DOE-Biological Ocean Margins Program. Microbial Ecology of Denitrifying Bacteria in the Coastal Ocean.

The focus of our research was to provide a comprehensive study of the bacterioplankton populations off the coast of New Jersey near the Rutgers University marine field station using terminal restriction fragment polymorphism analysis (TRFLP) coupled to 16S rRNA genes for large data set studies. Our three revised objectives to this study became: (1) to describe bacterioplankton population dynamics in the Mid Atlantic Bight using TRFLP analysis of 16S rRNA genes. (2) to determine whether spatial and temporal factors are driving bacterioplankton community dynamics in the MAB using monthly samping along our transect line over a 2-year period. (3) to identify dominant members of a coastal bacterioplankton population by clonal library analysis of 16S rDNA genes and sequencing of PCR product corresponding to specific TRFLP peaks in the data set. Although open ocean time-series sites have been areas of microbial research for years, relatively little was known about the population dynamics of bacterioplankton communities in the coastal ocean on kilometer spatial and seasonal temporal scales. To gain a better understanding of microbial community variability, monthly samples of bacterial biomass were collected in 1995-1996 along a 34-km transect near the Long-Term Ecosystem Observatory (LEO-15) off the New Jersey coast. Surface and bottom sampling was performed at seven stations along a transect line with depths ranging from 1 to 35m (n=178). The data revealed distinct temporal patterns among the bacterioplankton communities in the Mid-Atlantic Bight rather than grouping by sample location or depth (figure 2-next page). Principal components analysis models supported the temporal patterns. In addition, partial least squares regression modeling could not discern a significant correlation from traditional oceanographic physical and phytoplankton nutrient parameters on overall bacterial community variability patterns at LEO-15. These results suggest factors not traditionally measured during oceanographic studies are structuring coastal microbial communities.

09 BIOMASS FUELS↗
DOE OSTI2015

Spatially confined low-power optically pumped ultrafast synchrotron x-ray nanodiffraction

The combination of ultrafast optical excitation and time-resolved synchrotron x-ray nanodiffraction provides unique insight into the photoinduced dynamics of materials, with the spatial resolution required to probe individual nanostructures or small volumes within heterogeneous materials. Optically excited x-ray nanobeam experiments are challenging because the high total optical power required for experimentally relevant optical fluences leads to mechanical instability due to heating. For a given fluence, tightly focusing the optical excitation reduces the average optical power by more than three orders of magnitude and thus ensures sufficient thermal stability for x-ray nanobeam studies. Delivering optical pulses via a scannable fiber-coupled optical objective provides a well-defined excitation geometry during rotation and translation of the sample and allows the selective excitation of isolated areas within the sample. Finally, experimental studies of the photoinduced lattice dynamics of a 35 nm BiFeO 3 thin film on a SrTiO 3 substrate demonstrate the potential to excite and probe nanoscale volumes.

36 MATERIALS SCIENCE↗
DOE OSTI2014

WE-G-18C-08: Real Time Tumor Imaging Using a Novel Dynamic Keyhole MRI Reconstruction Technique

Purpose: To test the hypothesis that the novel Dynamic Keyhole MRI reconstruction technique can accelerate image acquisition whilst maintaining high image quality for lung cancer patients. Methods: 18 MRI datasets from 5 lung cancer patients were acquired using a 3T MRI scanner. These datasets were retrospectively reconstructed using (A) The novel Dynamic Keyhole technique, (B) The conventional keyhole technique and (C) the conventional zero filling technique. The dynamic keyhole technique in MRI refers to techniques in which previously acquired k-space data is used to supplement under sampled data obtained in real time. The novel Dynamic Keyhole technique utilizes a previously acquired a library of kspace datasets in conjunction with central k-space datasets acquired in realtime. A simultaneously acquired respiratory signal is utilized to sort, match and combine the two k-space streams with respect to respiratory displacement. Reconstruction performance was quantified by (1) comparing the keyhole size (which corresponds to imaging speed) required to achieve the same image quality, and (2) maintaining a constant keyhole size across the three reconstruction methods to compare the resulting image quality to the ground truth image. Results: (1) The dynamic keyhole method required a mean keyhole size which was 48% smaller than the conventional keyhole technique and 60% smaller than the zero filling technique to achieve the same image quality. This directly corresponds to faster imaging. (2) When a constant keyhole size was utilized, the Dynamic Keyhole technique resulted in the smallest difference of the tumor region compared to the ground truth. Conclusion: The dynamic keyhole is a simple and adaptable technique for clinical applications requiring real-time imaging and tumor monitoring such as MRI guided radiotherapy. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by a factor of five compared with full k-space methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

In Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter - 18423

Groundwater monitoring is critical for nuclear-related facilities as well as radioactively contaminated sites. Recent advances in sensing, data analytics and simulation capabilities provide substantial opportunities to improve and change current monitoring procedures. In particular, we need a paradigm shift from contaminant-only or compliance-only monitoring programs to comprehensive monitoring, i.e., including other ancillary environmental variables for a holistic understanding of the groundwater systems and plume behaviors. Such new approaches are needed for the effective implementation of sustainable remediation (enhanced and natural attenuation), and they have great potential for cost reduction in site monitoring. This paper reviews recent developments for improving long-term monitoring, with focus on the effective use of in situ sensors, data analytics and simulation capabilities. In particular, we highlight a recent application of the Kalman filter algorithm to estimate contaminant concentrations continuously in real time, based on in-situ measured water quality parameters (e.g. electrical conductance and pH) and sparse groundwater sampling. The results show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of short- and long-term contaminant concentration changes. Such advanced and integrated monitoring systems will be beneficial for local residents (e.g., to ensure the safety by detecting adverse events early, enabling a swift response) as well as for site operators (e.g., to gain/improve public acceptance, to be better prepared for litigations and false claims, and to reduce overall monitoring cost). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

THE INNER DYNAMICAL MASS ACROSS GALAXY MORPHOLOGY: A WEAK SCALING WITH TOTAL STELLAR MASS

We compile a sample of dispersion-supported and rotation-supported galaxies for which the dynamical mass enclosed at 500 pc can be measured. We find that this dynamical quantity increases only slowly with stellar mass (M{sub total}(<500 pc)∝M{sub stars}{sup 0.16}) over ∼9 decades in baryonic mass and ∼3 in length scale, with a sudden upturn at the highest masses (M {sub stars} ≳ 10{sup 10} M {sub ☉}). This upturn occurs for the earliest types (S0 and Sa) of disk galaxies, and is consistent with the ''extra'' mass within 500 pc being predominantly stellar. This sudden change may be indicative of different bulge formation mechanisms between early- and late-type disks. We also compare the data to the results of recent galaxy formation simulations. These broadly track the observed trend, with some tendency to put too much mass in the inner 500 pc, depending on the details of each simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Dynamic properties of different liquid states in systems with competing interactions studied with lysozyme solutions

Recent studies of colloidal systems with a short-range attraction and long-range repulsion (SALR) have been demonstrated to have a generalized phase diagram with multiple liquid states defined by their structures. In this paper, we identify the different liquid states of previous experimentally studied lysozyme samples within this proposed generalized state diagram and explore the dynamic properties of each liquid state. We show that most lysozyme samples studied here and previously at low and intermediate concentrations are dispersed fluids while a few high concentration samples are randomly percolated liquids. In the dispersed fluid region, the short-time diffusion coefficient measured by neutron spin echo agrees well with the long time diffusion coefficient estimated with the solution viscosity. This dynamic feature is maintained even for some samples in the random percolated region. However, the short-time and long-time diffusion coefficients of random percolated fluids deviate at larger concentration and attraction strength. At high enough concentrations, the mean square displacement can be as slow as those of many glassy colloidal systems at time scales near the characteristic diffusion time even though these lysozyme samples remain in liquid states at the long-time limit. Here, we thus identify the region in the generalized phase diagram where these equilibrium states with extremely slow local dynamics exist relative to bulk percolation and kinetic arrest (gel and glassy) transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Order-parameter-aided temperature-accelerated sampling for the exploration of crystal polymorphism and solid-liquid phase transitions

The problem of predicting polymorphism in atomic and molecular crystals constitutes a significant challenge both experimentally and theoretically. From the theoretical viewpoint, polymorphism prediction falls into the general class of problems characterized by an underlying rough energy landscape, and consequently, free energy based enhanced sampling approaches can be brought to bear on the problem. In this paper, we build on a scheme previously introduced by two of the authors in which the lengths and angles of the supercell are targeted for enhanced sampling via temperature accelerated adiabatic free energy dynamics [T. Q. Yu and M. E. Tuckerman, Phys. Rev. Lett. 107, 015701 (2011)]. Here, that framework is expanded to include general order parameters that distinguish different crystalline arrangements as target collective variables for enhanced sampling. The resulting free energy surface, being of quite high dimension, is nontrivial to reconstruct, and we discuss one particular strategy for performing the free energy analysis. The method is applied to the study of polymorphism in xenon crystals at high pressure and temperature using the Steinhardt order parameters without and with the supercell included in the set of collective variables. The expected fcc and bcc structures are obtained, and when the supercell parameters are included as collective variables, we also find several new structures, including fcc states with hcp stacking faults. We also apply the new method to the solid-liquid phase transition in copper at 1300 K using the same Steinhardt order parameters. Our method is able to melt and refreeze the system repeatedly, and the free energy profile can be obtained with high efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.

Chemistry↗
DOE OSTI2019

Heat current fluctuations and anomalous transport in low-dimensional carbon lattices

Molecular dynamics simulations and methods of importance sampling are used to study the heat transport of low-dimensional carbon lattices. For both carbon nanotubes and graphene sheets, heat transport is found to be anomalous, violating Fourier’s law of conduction with a system size dependent thermal conductivity and concomitant nonlinear temperature profiles. For carbon nanotubes, the thermal conductivity is found to increase as the square root of the length of the nanotube, while for graphene sheets the thermal conductivity is found to increase as the logarithm of the length of the sheet over the system sizes considered. Furthermore, the particular length dependence and nonlinear temperature profiles place carbon lattices into a universality class with nonlinear lattice models, and suggest that heat transport through carbon nanostructures is better described by a Levy walk rather than simple diffusion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Large-scale experimental landscapes reveal distinctive effects of patch shape and connectivity on arthropod communities.

The size, shape, and isolation of habitat patches can affect organism behavior and population dynamics, but little is known about the relative role of shape and connectivity in affecting ecological communities at large spatial scales. Using six sampling sessions from July 2001 until August 2002, we collected 33,685 arthropods throughout seven 12-ha experimental landscapes consisting of clear-cut patches surrounded by a matrix of mature pine forest. Patches were explicitly designed to manipulate connectivity (via habitat corridors) independently of area and edge effects. We found that patch shape, rather than connectivity, affected ground-dwelling arthropod richness and beta diversity (i.e. turnover of genera among patches). Arthropod communities contained fewer genera and exhibited less turnover in high-edge connected and high-edge unconnected patches relative to low-edge unconnected patches of similar area. Connectivity, rather than patch shape, affected the evenness of ground-dwelling arthropod communities; regardless of patch shape, high-edge connected patches had lower evenness than low- or high-edge unconnected patches. Among the most abundant arthropod orders, increased richness in low-edge unconnected patches was largely due to increased richness of Coleoptera, whereas Hymenoptera played an important role in the lower evenness in connected patches and patterns of turnover. These findings suggest that anthropogenic habitat alteration can have distinct effects on ground-dwelling arthropod communities that arise due to changes in shape and connectivity. Moreover, this work suggests that corridors, which are common conservation tools that change both patch shape and connectivity, can have multiple effects on arthropod communities via different mechanisms, and each effect may alter components of community structure.

Diversity↗
DOE OSTI2016

Reactive Monte Carlo sampling with an ab initio potential

We present the first application of reactive Monte Carlo in a first-principles context. The algorithm samples in a modified NVT ensemble in which the volume, temperature, and total number of atoms of a given type are held fixed, but molecular composition is allowed to evolve through stochastic variation of chemical connectivity. We discuss general features of the method, as well as techniques needed to enhance the efficiency of Boltzmann sampling. Finally, we compare the results of simulation of NH{sub 3} to those of ab initio molecular dynamics (AIMD). We find that there are regions of state space for which RxMC sampling is much more efficient than AIMD due to the “rare-event” character of chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The combined force field-sampling problem in simulations of disordered amyloid-β peptides

Molecular dynamics simulations of intrinsically disordered proteins (IDPs) can provide high resolution structural ensembles if the force field is accurate enough and if the simulation sufficiently samples the conformational space of the IDP with the correct weighting of sub-populations. Here, we investigate the combined force field–sampling problem by testing a standard force field as well as newer fixed charge force fields, the latter specifically motivated for better description of unfolded states and IDPs, and comparing them with a standard temperature replica exchange (TREx) protocol and a non-equilibrium Temperature Cool Walking (TCW) sampling algorithm. The force field and sampling combinations are used to characterize the structural ensembles of the amyloid-beta peptides Aβ42 and Aβ43, which both should be random coils as shown recently by experimental nuclear magnetic resonance (NMR) and 2D Förster resonance energy transfer (FRET) experiments. The results illustrate the key importance of the sampling algorithm: while the standard force field using TREx is in poor agreement with the NMR J-coupling and nuclear Overhauser effect and 2D FRET data, when using the TCW method, the standard and optimized protein-water force field combinations are in very good agreement with the same experimental data since the TCW sampling method produces qualitatively different ensembles than TREx. Lastly, we also discuss the relative merit of the 2D FRET data when validating structural ensembles using the different force fields and sampling protocols investigated in this work for small IDPs such as the Aβ42 and Aβ43 peptides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

XPlacer/Tracer

XPlacer/Tracer is a dynamic analysis tool that finds bad memory access patterns in heterogeneous codes. XPlacer/Tracer consists of two components. (1) A configurable ROSE plugin for source code instrumentation of heterogeneous code written in the C/C++ and CUDA programming languages. (2) A sample configuration that instruments memory accesses to dynamic memory in CPU and GPU codes, and a runtime library that tracks these memory accesses at runtime. The collected information is reported in form of a textual summary or as memory map that can be converted to images.

Pirkelbauer, PeterM.↗
DOE OSTI2015

CME PROPAGATION: WHERE DOES AERODYNAMIC DRAG “TAKE OVER”?

We investigate the Sun–Earth dynamics of a set of eight well observed solar coronal mass ejections (CMEs) using data from the Solar Terrestrial Relations Observatory spacecraft. We seek to quantify the extent to which momentum coupling between these CMEs and the ambient solar wind (i.e., the aerodynamic drag) influences their dynamics. To this end, we use results from a 3D flux rope model fit to the CME data. We find that solar wind aerodynamic drag adequately accounts for the dynamics of the fastest CME in our sample. For the relatively slower CMEs, we find that drag-based models initiated below heliocentric distances ranging from 15 to 50 R{sub ⊙} cannot account for the observed CME trajectories. This is at variance with the general perception that the dynamics of slow CMEs are influenced primarily by solar wind drag from a few R{sub ⊙} onwards. Several slow CMEs propagate at roughly constant speeds above 15–50 R{sub ⊙}. Drag-based models initiated above these heights therefore require negligible aerodynamic drag to explain their observed trajectories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Accelerating Dynamic Magnetic Resonance Imaging (MRI) for Lung Tumor Tracking Based on Low-Rank Decomposition in the Spatial–Temporal Domain: A Feasibility Study Based on Simulation and Preliminary Prospective Undersampled MRI

Purpose: To evaluate a low-rank decomposition method to reconstruct down-sampled k-space data for the purpose of tumor tracking. Methods and Materials: Seven retrospective lung cancer patients were included in the simulation study. The fully-sampled k-space data were first generated from existing 2-dimensional dynamic MR images and then down-sampled by 5 × -20 × before reconstruction using a Cartesian undersampling mask. Two methods, a low-rank decomposition method using combined dynamic MR images (k-t SLR based on sparsity and low-rank penalties) and a total variation (TV) method using individual dynamic MR frames, were used to reconstruct images. The tumor trajectories were derived on the basis of autosegmentation of the resultant images. To further test its feasibility, k-t SLR was used to reconstruct prospective data of a healthy subject. An undersampled balanced steady-state free precession sequence with the same undersampling mask was used to acquire the imaging data. Results: In the simulation study, higher imaging fidelity and low noise levels were achieved with the k-t SLR compared with TV. At 10 × undersampling, the k-t SLR method resulted in an average normalized mean square error <0.05, as opposed to 0.23 by using the TV reconstruction on individual frames. Less than 6% showed tracking errors >1 mm with 10 × down-sampling using k-t SLR, as opposed to 17% using TV. In the prospective study, k-t SLR substantially reduced reconstruction artifacts and retained anatomic details. Conclusions: Magnetic resonance reconstruction using k-t SLR on highly undersampled dynamic MR imaging data results in high image quality useful for tumor tracking. The k-t SLR was superior to TV by better exploiting the intrinsic anatomic coherence of the same patient. The feasibility of k-t SLR was demonstrated by prospective imaging acquisition and reconstruction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗