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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data

Background: Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge. Results: We present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented. Conclusions: VizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/ VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Calculation of composition distribution of ultrafine ion-H2O-H2SO4 clusters using a modified binary ion nucleation theory

Thomson's ion nucleation theory was modified to include the effects of curvature dependence of the microscopic surface tension of field dependent, nonlinear, dielectric properties of the liquid; and of sulfuric acid hydrate formation in binary mixtures of water and sulfuric acid vapors. The modified theory leads to a broadening of the ion cluster spectrum, and shifts it towards larger numbers of H2O and H2SO4 molecules. Whether there is more shifting towards larger numbers of H2O or H2SO4 molecules depends on the relative humidity and relative acidity of the mixture. Usually, a broadening of the spectrum is accompanied by a lowering of the mean cluster intensity. For fixed values of relative humidity and relative acidity, a similar broadening pattern is observed when the temperature is lowered. These features of the modified theory illustrate that a trace of sulfuric acid can facilitate the formation of ultrafine, stable, prenucleation ion clusters as well as the growth of the prenucleation ion clusters towards the critical saddle point conditions, even with low values of relative humidity and relative acidity.

Singh, J. J.↗
NASA NTRS1972

Changes of multispectral soil patterns with increasing crop canopy

Multispectral data and automatic data processing were used to map surface soil patterns and to follow the changes in multispectral radiation from a field of maize (Zea mays L.) during a period from seeding to maturity. Panchromatic aerial photography was obtained in early May 1970 and multispectral scanner missions were flown on May 6, June 30, August 11 and September 5, 1970 to obtain energy measurements in 13 wavelength bands. The orange portion of the visible spectrum was used in analyzing the May and June data to cluster relative radiance of the soils into eight different radiance levels. The reflective infrared spectral band was used in analyzing the August and September data to cluster maize into different spectral categories. The computer-produced soil patterns had a striking similarity to the soil pattern of the aerial photograph. These patterns became less distinct as the maize canopy increased.

Kristof, S. J.↗
DOE OSTI2016

Genome organization of the vg1 and nodal3 gene clusters in the allotetraploid frog Xenopus laevis

Extracellular factors belonging to the TGF-β family play pivotal roles in the formation and patterning of germ layers during early Xenopus embryogenesis. Here, we show that the vg1 and nodal3 genes of Xenopus laevis are present in gene clusters on chromosomes XLA1L and XLA3L, respectively, and that both gene clusters have been completely lost from the syntenic S chromosome regions. The presence of gene clusters and chromosome-specific gene loss were confirmed by cDNA FISH analyses. Sequence and expression analyses revealed that paralogous genes in the vg1 and nodal3 clusters on the L chromosomes were also altered compared to their Xenopus tropicalis orthologs. X. laevis vg1 and nodal3 paralogs have potentially become pseudogenes or sub-functionalized genes and are expressed at different levels. As X. tropicalis has a single vg1 gene on chromosome XTR1, the ancestral vg1 gene in X. laevis appears to have been expanded on XLA1L. Of note, two reported vg1 genes, vg1(S20) and vg1(P20), reside in the cluster on XLA1L. The nodal3 gene cluster is also present on X. tropicalis chromosome XTR3, but phylogenetic analysis indicates that nodal3 genes in X. laevis and X. tropicalis were independently expanded and/or evolved in concert within each cluster by gene conversion. Lastly, these findings provide insights into the function and molecular evolution of TGF-β family genes in response to allotetraploidization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Bismuth-oxo Clusters for Next Generation Extreme Ultraviolet Light Photolithography

Photolithography is the primary technique used for the patterning of semiconducting materials for chip manufacturing; however, as requisite pattern dimensions and feature sizes continue to decrease, state-of-the-art lithographic methods now require the use of 13.5 nm extreme ultraviolet (EUV) light. The shift toward these higher energy wavelengths of light has resulted in a need for new single component materials, with high EUV absorption cross sections and high etch resistance. Herein, we report the exploration of Bi 9 O 7 (hfac) 13 as the first bismuth oxo cluster based EUV photoresist. It was determined this material has an exceptional EUV linear absorption coefficient (24 μm –1 ), nearly an order of magnitude larger than commercially available chemically amplified resists (CARs) (∼5 μm –1 ). Additionally, the resist was determined to be highly sensitive to EUV exposure and displayed a dose-to-gel of 10 mJ/cm 2 , undergoing ligand decomposition during exposure and cross-linking during the postexposure bake, which was supported by FTIR and residual gas analysis. In conclusion, this class of bismuth-oxo cluster resists can lead to the development of more efficient, effective and safe EUV resist materials required for next-generation photolithography.

MacKenzie, Harvey K. [Univ. of Victoria, BC (Canad↗
NASA NTRS1999

Unsupervised classification of Space Acceleration Measurement System (SAMS) data using ART2-A

The Space Acceleration Measurement System (SAMS) has been developed by NASA to monitor the microgravity acceleration environment aboard the space shuttle. The amount of data collected by a SAMS unit during a shuttle mission is in the several gigabytes range. Adaptive Resonance Theory 2-A (ART2-A), an unsupervised neural network, has been used to cluster these data and to develop cause and effect relationships among disturbances and the acceleration environment. Using input patterns formed on the basis of power spectral densities (psd), data collected from two missions, STS-050 and STS-057, have been clustered.

STS-57 Shuttle Project↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2020

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Probing the Early Stages of Solvation of cis-Pinate Dianions by Water, Acetonitrile, and Methanol: A Photoelectron Spectroscopy and Theoretical Study

Cis-pinic acid is one of the most important oxidation products of α-pinene – a key monoterpene compound in biogenic emission processes affecting the atmosphere. Molecular level understanding of interactions involved in the cluster formations around cis-pinic acid is an important and necessary prerequisite toward ascertaining its role in the aerosol formation processes. In this work, we studied the structures and energetics of the solvated clusters of cis-pinate (cis-PA²⁻), the doubly deprotonated dicarboxylate of cis-pinic acid, with H₂O, CH₃OH, and CH₃CN by negative ion photoelectron spectroscopy and ab initio theoretical calculations. We found that cis-PA²⁻ prefers being solvated alternately on the two -CO₂⁻ groups with increase of solvent coverage, a well-known solvation pattern that has been observed in microhydrated linear dicarboxylate dianion (DC n ²⁻) clusters. Experiments and calculations further reveal an intriguing feature for the existence of the asymmetric type isomers for cis-PA2–(H2O)2 and cis-PA²⁻(CH₃OH)₂, in which both solvent molecules interact with only one of the -CO²⁻ groups – a phenomena that has not been observed in DCn²⁻ water clusters and exhibits the subtle effect of the rigid four-membered carbon ring brought in on the cis-PA²⁻ solvation. The dominant interactions between cis-PA²⁻ and solvent molecules are forming bidentate O–···H–O H-bonds for H₂O, O–···H–O and O–···H–C H-bonds for CH₃OH, and tridentate O–···H–C H-bonds for CH₃CN. The formation of inter-solvent H-bonds between H₂O and CH₃CN is found to be favorable in mixed solvent clusters, distinctly different from that between H₂O and CH₃OH. These findings have important implications for understanding the mechanism of cluster growth and nucleation of atmospheric organic aerosols and the nature of structure-function relationship of proteins containing carboxylate groups under various solvent environments.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2024

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

TIME EVOLUTION OF PLASMA PARAMETERS DURING THE RISE OF A SOLAR PROMINENCE INSTABILITY

We present high-spatial resolution spectropolarimetric observations of a quiescent hedgerow prominence taken in the He I 1083.0 nm triplet. The observation consisted of a time series in sit-and-stare mode of ∼36 minutes duration. The spectrograph's slit crossed the prominence body and we recorded the time evolution of individual vertical threads. Eventually, we observed the development of a dark Rayleigh-Taylor plume that propagated upward with a velocity, projected onto the plane of the sky, of 17 km s{sup –1}. Interestingly, the plume apex collided with the prominence threads pushing them aside. We inferred Doppler shifts, Doppler widths, and magnetic field strength variations by interpreting the He I Stokes profiles with the HAZEL code. The Doppler shifts show that clusters of threads move coherently while individual threads have oscillatory patterns. Regarding the plume we found strong redshifts (∼9-12 km s{sup –1}) and large Doppler widths (∼10 km s{sup –1}) at the plume apex when it passed through the prominence body and before it disintegrated. We associate the redshifts with perspective effects while the Doppler widths are more likely due to an increase in the local temperature. No local variations of the magnetic field strength associated with the passage of the plume were found; this leads us to conclude that the plumes are no more magnetized than the surroundings. Finally, we found that some of the threads' oscillations are locally damped, what allowed us to apply prominence seismology techniques to infer additional prominence physical parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Convergence in drought stress, but a divergence of climatic drivers across a latitudinal gradient in a temperate broadleaf forest

Abstract Aim Information about climate stressors on tree growth is needed in order to assess the impacts of global change on forest ecosystems. Broad‐scale patterns of climatic limitations on tree growth remain poorly described across eastern North American deciduous forests. We examined the response of broadleaf tree species to climate in relation to their taxonomy, functional traits and geographical location. Location Eastern North America (32–45° N; 70–88° W). Methods We used a network of 86 tree‐ring width chronologies from eight species that cover a wide range of ecological and climatic conditions. Species were analysed individually or combined according to taxa and wood anatomical functional traits. We identified climate stressors through correlations between growth and climate (from 1916 to 1996). We also explored patterns in the climate responses of these species with two clustering techniques. Results We found strong correlations between water availability and growth for all species. With few exceptions, this drought stress was independent of taxonomy or wood anatomical functional group. Depending on latitude, however, different climatic drivers governed this common drought response. In the cool, northern part of our network, forest growth was most strongly limited by precipitation variability, whereas maximum temperature was a stronger limiting factor than precipitation in the wetter and warmer southern parts. Main conclusions Our study highlights the sensitivity of broadleaf temperate forests to drought stress at annual to decadal scales, with few species‐specific differences. The roles of temperature and precipitation on drought‐sensitivity differ at opposing ends of our subcontinental‐scale network. The impact of future environmental changes on these forests will ultimately depend on the balance between temperature and precipitation changes across this latitudinal gradient.

Martin‐Benito, Dario↗
DOE OSTI2024

Can the angular scale of cosmic homogeneity be used as a cosmological test?

Abstract In standard cosmology, the cosmic homogeneity scale is the transition scale above which the patterns arising from non-uniformities – such as groups and clusters of galaxies, voids, and filaments – become indistinguishable from a random distribution of sources. Recently, different groups have investigated the feasibility of using such a scale as a cosmological test and arrived at different conclusions. In this paper, we complement and extend these studies by exploring the evolution of the spatial ( $$R_{\textrm{H}}$$ R H ) and angular ( $$\theta _{\textrm{H}}$$ θ H ) homogeneity scales with redshift, assuming a spatially flat, $$\varLambda $$ Λ -Cold Dark Matter universe and linear cosmological perturbation theory. We confirm previous results concerning the non-monotonicity of $$R_{\textrm{H}}$$ R H with the matter density parameter $$\varOmega _{\textrm{m0}}$$ Ω m0 but also show that it exhibits a monotonical behavior with the Hubble constant $$H_{0}$$ H 0 within a large redshift interval. More importantly, we find that, for $$z \gtrsim 0.6$$ z ≳ 0.6 , $$\theta _{\textrm{H}}$$ θ H presents a monotonical behavior with $$\varOmega _{\textrm{m0}}$$ Ω m0 , as well as for $$H_0$$ H 0 the entire redshift interval analyzed. We find also that the angular homogeneity scale is sensitive to $$H_{0}$$ H 0 , especially at higher redshifts. Using the currently available $$\theta _{\textrm{H}}$$ θ H measurements, we illustrate the constraints on the $$\varOmega _{\textrm{m0}}$$ Ω m0 – $$H_{0}$$ H 0 plane through a MCMC analysis and show the feasibility of using the angular homogeneity scale as a new, model-independent way to constrain cosmological parameters.

Physics↗
DOE OSTI2023

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Abstract There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. However, due to bandwidth and storage constraints, the Doppler spectra are not routinely stored. This calls for the automation of cloud and rain detection in ARM Doppler lidar data so that the spectral data in clouds can be selectively saved and further analyzed. During the ARMing the Edge field experiment, a Waggle node capable of performing machine learning applications in situ was deployed at the ARM SGP site for this purpose. In this paper, we develop and test four algorithms for the Waggle node to automatically classify ARM Doppler lidar data. We demonstrate that supervised learning using a ResNet50-based classifier will classify 97.6% of the clear-air images and 94.7% of cloudy images correctly, outperforming traditional peak detection methods. We also show that a convolutional autoencoder paired with k -means clustering identifies 10 clusters in the ARM Doppler lidar data. Three clusters correspond to mostly clear conditions with scattered high clouds, and seven others correspond to cloudy conditions with varying cloud-base heights.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Influence of relative humidity on the heterogeneous oxidation of secondary organic aerosol

Abstract. Secondary organic aerosol (SOA) is a complex mixture of hundreds of semi-volatile to extremely low-volatility organic compounds that are chemically processed in the atmosphere, including via heterogeneous oxidation by gas-phase radicals. Relative humidity (RH) has a substantial impact on particle phase, which can affect how SOA evolves in the atmosphere. In this study, SOA from dark α -pinene ozonolysis is heterogeneously aged by OH radicals in a flow tube at low and high RH. At high RH (RH = 89 %) there is substantial loss of particle volume (~60 %) at an equivalent atmospheric OH exposure of 3 weeks. In contrast, at low RH (RH = 25 %) there is little mass loss (< 20 %) at the same OH exposure. Mass spectra of the SOA particles were measured as a function of OH exposure using a vacuum ultraviolet aerosol mass spectrometer (VUV-AMS). The mass spectra observed at low RH overall exhibit minor changes with oxidation and negligible further changes above an OH exposure = 2×10 12 molecule cm -3 s suggesting limited impact of oxidation on the particle composition. In contrast, the mass spectra observed at high RH exhibit substantial and continuous changes as a function of OH exposure. Further, at high RH clusters of peaks in the mass spectra exhibit unique decay patterns, suggesting different responses of various species to oxidation. A model of heterogeneous oxidation has been developed to understand the origin of the difference in aging between the low- and high-RH experiments. Differences in diffusivity of the SOA between the low- and high-RH experiments alone can explain the difference in compositional change but cannot explain the difference in mass loss. Instead, the difference in mass loss is attributable to RH-dependent differences in the OH uptake coefficient and/or the net probability of fragmentation, with either or both larger at high RH compared to low RH. These results illustrate the important impact of relative humidity on the fate of SOA in the atmosphere.

Li, Ziyue (ORCID:0000000191017737)↗
DOE OSTI2023

A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation: insights from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition

Abstract. The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019–2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January–March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Advanced Solid Rocket Motor (ASRM) communications network analysis

This paper describes the simulation of a proposed campus-wide network for a new manufacturing facility. The proposed network consists of five carrier sense multiple access with collision detection (CSMA/CD) networks connected to five ports of a VAX cluster. In Section 1 the system configuration, the projected traffic pattern, and the proposed protocols are presented. Section 2 describes the models used in constructing the network simulation, while Section 3 contains the results and an analysis of the simulations. The simulations are compared to a mathematical model in Section 4. Some conclusions are drawn in Section 5.

Thompson, Dale R.↗
NASA NTRS2000

Quantitative assessment of Hox complex expression in the indirect development of the polychaete annelid Chaetopterus sp

A prediction from the set-aside theory of bilaterian origins is that pattern formation processes such as those controlled by the Hox cluster genes are required specifically for adult body plan formation. This prediction can be tested in animals that use maximal indirect development, in which the embryonic formation of the larva and the postembryonic formation of the adult body plan are temporally and spatially distinct. To this end, we quantitatively measured the amount of transcripts for five Hox genes in embryos of a lophotrochozoan, the polychaete annelid Chaetopterus sp. The polychaete Hox complex is shown not to be expressed during embryogenesis, but transcripts of all measured Hox complex genes are detected at significant levels during the initial stages of adult body plan formation. Temporal colinearity in the sequence of their activation is observed, so that activation follows the 3'-5' arrangement of the genes. Moreover, Hox gene expression is spatially localized to the region of teloblastic set-aside cells of the later-stage embryos. This study shows that an indirectly developing lophotrochozoan shares with an indirectly developing deuterostome, the sea urchin, a common mode of Hox complex utilization: construction of the larva, whether a trochophore or dipleurula, does not involve Hox cluster expression, but in both forms the complex is expressed in the set-aside cells from which the adult body plan derives.

Non-NASA Center↗