Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Clustered patterns”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Vertical Structure of a Springtime Smoky and Humid Troposphere Over the Southeast Atlantic From Aircraft and Reanalysis

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is coincident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here, we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize covariations in humidity and BB smoke across the SEA. The observed plume–vapor relationship, and its agreement with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between carbon monoxide (CO) and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k-means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts as they covary. While the humidity profiles show a range in both total water vapor concentration and in vertical structure, the CO profiles primarily vary in terms of maximum concentration, with similar vertical structures in each. The distribution of profile types varies spatiotemporally across the SEA region and through the season, ranging from largely one type in the northeast and southwest to more evenly distributed between multiple types where air masses meet in the middle of the SEA. These distributions follow patterns of transport from the humid, smoky source region (greatest influence in the northeast of the SEA) and the seasonal changes in both humidity and smoke (increasing and decreasing through the season, respectively). With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA.

Kristina Pistone↗
DOE OSTI2021

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗
NASA NTRS2011

Deep Moonquake Focal Mechanisms: Recovery and Implications

A defining characteristic of deep moonquakes is their tendency to occur with tidal periodicity, prompting previous studies to infer that they are related to the buildup and release of tidal stress within the Moon. In studies of tidal forcing, a key constraint is the focal mechanism: the fault parameters describing the type of failure moonquakes represent. The quality of the lunar seismic data and the limited source/receiver geometries of the Apollo seismic network prohibit the determination of deep moonquake fault parameters using first-motion polarities, as is typically done in terrestrial seismology. Without being able to resolve tidal stress onto a known failure plane, we can examine only gross qualities of the tidal stress tensor with respect to moonquake occurrence, so we cannot fully address the role of tidal stress in moonquake generation. We will examine the extent to which shear (S) and compression (P) wave amplitude ratios can constrain moonquake fault geometry by determining whether, for a given cluster, there exists a focal mechanism that can produce a radiation pattern consistent with the amplitudes measured by the Apollo instruments. Amplitudes are read in the ray coordinate frame, directly from seismograms for which the P and S arrivals are clearly identifiable on all long-period channels of the four Apollo stations. We apply an empirical station correction to account for site effects and the differences between P- and S-wave attenuation. Instead of focusing on the best fitting solution only, we formulate the inverse problem using a falsification criterion: all source orientations that do not reproduce the observed SV/P ratios within an error margin derived from the uncertainty of amplitude readings are rejected. All others are accepted as possible solutions. The inversion is carried out using an exhaustive grid search on a regular grid with predefined step size, encompassing all possible combinations of strike, dip and slip. To assess the sensitivity of the inversion for the uncertainty of the lunar interior structure, we carry out repeated inversions with different velocity structures. Our data set consist of a total of 106 events from 25 deep moonquake clusters. The largest contribution of 37 events originates from the most active cluster, A001, while other clusters are represented by 1 to 9 events. Since the definition of a cluster implies that all events share the same source orientation, a comparison of the inversion results of all events from one cluster will reduce ambiguities of the inversion. Once we obtain a suite of fault parameters for a given source, we can attempt to further constrain the focal mechanism with refined analyses of tidal stresses and predictions based on synthetic seismograms.

Knapmeyer, Martin↗
DOE OSTI2015

Big Data Analytics for Demand Response: Clustering Over Space and Time

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

The JSC clustering program ISOCLS and its applications

The clustering program ISOCLS developed at the Johnson Space Center, Houston, Texas, has been extensively used in the pattern analysis and classification of remote sensor data collected by aircraft and by the Earth Resources Technology Satellite ERTS-1. This paper discusses the theory behind this clustering algorithm. Several new ideas that have been incorporated in ISOCLS are discussed. Among these are the novel philosophy of operation behind the procedure, which assumes that a population (i.e., a class or a cluster) can be treated as the union of an appropriate number of subpopulations, and the termination of the clustering program by a 'chaining algorithm.' Finally, this paper reports the results of the application of ISOCLS to an investigation on rangeland vegetation mapping using ERTS-1 data.

Kan, E. P.↗
DOE OSTI2026

Simultaneous global and local clustering in multiplex networks with covariate information

Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a new model, the hierarchical multiplex stochastic blockmodel, which simultaneously detects communities within individual layers of a multiplex network while inferring a global node clustering across the layers. A stochastic blockmodel is assumed in each layer, with probabilities of layer-level group memberships determined by a node’s global group assignment. Our model uses a Bayesian framework, employing a probit stick-breaking process to construct node-specific mixing proportions over a set of shared Griffiths–Engen–McCloseky distributions. These proportions determine layer-level community assignment, allowing for an unknown and varying number of groups across layers, while incorporating nodal covariate information to inform the global clustering. We propose a scalable variational inference procedure with parallelisable updates for application to large networks. Extensive simulation studies demonstrate our model’s ability to accurately recover both global and layer-level clusters in complicated settings, and applications to real data showcase the model’s effectiveness in uncovering interesting latent network structure.

community detection↗
DOE OSTI2014

A Cluster-based Method to Map Urban Area from DMSP/OLS Nightlights

Accurate information of urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable light data (NTL) provide a potential way to map urban area and its dynamics economically and timely. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the DMSP/OLS NTL data in five major steps, including data preprocessing, urban cluster segmentation, logistic model development, threshold estimation, and urban extent delineation. Different from previous fixed threshold method with over- and under-estimation issues, in our method the optimal thresholds are estimated based on cluster size and overall nightlight magnitude in the cluster, and they vary with clusters. Two large countries of United States and China with different urbanization patterns were selected to map urban extents using the proposed method. The result indicates that the urbanized area occupies about 2% of total land area in the US ranging from lower than 0.5% to higher than 10% at the state level, and less than 1% in China, ranging from lower than 0.1% to about 5% at the province level with some municipalities as high as 10%. The derived thresholds and urban extents were evaluated using high-resolution land cover data at the cluster and regional levels. It was found that our method can map urban area in both countries efficiently and accurately. Compared to previous threshold techniques, our method reduces the over- and under-estimation issues, when mapping urban extent over a large area. More important, our method shows its potential to map global urban extents and temporal dynamics using the DMSP/OLS NTL data in a timely, cost-effective way.

Cities↗
DOE OSTI2016

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) to compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Are continuum predictions of clustering chaotic?

Gas-solid multiphase flows are prone to develop an instability known as clustering. Two-fluid models, which treat the particulate phase as a continuum, are known to reproduce the qualitative features of this instability, producing highly-dynamic, spatiotemporal patterns. However, it is unknown whether such simulations are truly aperiodic or a type of complex periodic behavior. By showing that the system possesses a sensitive dependence on initial conditions and a positive largest Lyapunov exponent, λ 1 ≈1/τ, we provide a tentative answer: continuum predictions of clustering are chaotic. We further demonstrate that the chaotic behavior is dimensionally dependent, a conclusion which unifies previous results and strongly suggests that the chaotic behavior is not a direct consequence of the fundamental kinematic instability, but requires a secondary (inherently multidimensional) instability. Granular matter is a collection of discrete, interacting solid particles which, like classic (molecular) matter, can be generally classified into one of three states:1 (i) under static conditions granular heaps or piles can sustain gravity-induced stress and behave like a solid; (ii) dense granular flows characterized by enduring and multi-particle contacts behave similarly to a fluid; and (iii) rapid granular flows characterized by instantaneous contacts described as a granular gas. However, it is worth noting that all three granular states are only superficially similar to their molecular counterparts due to the dissipative nature of particle-particle contacts (inelasticity, friction, etc.). In industrial operations, rapid (collision-dominated) granular flows are often encountered in devices in which the particles are fluidized by a gas; such gas-solid flows are the focus of this work. Rapid gas-solid flows are prone to an instability termed clustering in which particles tend to form spatially inhomogeneous patterns of high and low concentrations. Continuum or two-fluid models (TFM) have long been known to be able to predict the qualitative nature of the clustering instability and more recent quantitative assessments have also shown promising results. However, it is yet unknown whether or not such predictions are chaotic. We take a first step in answering this question by simulating fluidization in an unbounded domain and calculating a positive largest Lyapunov exponent (LLE), thereby indicating that continuum predictions of clustering are in fact chaotic. Further, we show that chaotic behavior may be reduced to periodic behavior by constraining the dimensionality of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

New Fracture Diagnostic Tool for Unconventionals: High-Resolution Distributed Strain Sensing via Rayleigh Frequency Shift during Production in Hydraulic Fracture Test 2

Fiber Optic monitoring in unconventional reservoirs has proven to be an invaluable diagnostic tool for assessing both near-wellbore stimulation effectiveness and to help describe the far-field frac geometries created by hydraulic fracture stimulation. Unfortunately, gaining any detailed qualitative and quantitative understanding of the near-wellbore frac geometry or cluster/stage productivity during production via Fiber Optic (FO) has proven to be more difficult, particularly in wells producing liquids. A new FO diagnostic method, Distributed Strain Sensing based on Rayleigh Frequency Shift (DSS-RFS), first demonstrated for oil and gas applications in the Hydraulic Test Site 2 (HFTS2) provides new insights about the characteristics of near-wellbore-region (NWR) during production. DSS-RFS is different from other FO strain measurements because it relies on accurate measurement of frequency shifts of Rayleigh backscattered spectrum obtained by scanning the fiber with a coherent optical time-domain reflectometer with a range of laser frequencies using a tunable-wavelength laser system. Changes in strain are measured with an extremely high spatial resolution of 20 cm and with high signal-to-noise ratios over long distances. In HFTS2, strain changes for the entire wellbore have been measured twice during scheduled shut-in and reopening operations (February 2020 and September 2020). After removing temperature effects, consistent strain changes have been observed at the location of most perforation clusters. These are caused by near wellbore fracture aperture changes due to pressure increases during shut-in within the near-wellbore fracture network. The strain-change patterns from the DSS-RFS during shut-in correlate very well with the location of clusters and allow for the definition of extending intervals with positive strain signals at each cluster and slightly compressing intervals with negative strain signals between the clusters and in the non stimulated intervals. The locations of the measured positive strain peaks also show good correspondence to DAS acoustic intensity measurements acquired during the stimulation. The geometry and magnitude of the strain changes differ significantly between the two tested completion designs in the same well. During shut in and reopening each cluster exhibit its own strain-change / pressure path. In addition, the September 2020 dataset also revealed the existence of small but measurable strain changes as consequence of pressure decline during production. These strain changes also correlate well with the presence of producing clusters, but the strain-rate signals are opposite to that obtained during shut-in and reopening operations. Although Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R002/2477551/urtec-2021-5408-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5408 2 we are still in the early stages of exploring the potential of this novel FO technique, we believe that the highly detailed information contained in the measurement of strain changes using DSS-RFS during production can significantly improve our understanding of near-wellbore hydraulic fracture characteristics and the relationships between stimulation and production from unconventional oil and gas wells.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2017

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

CHEMICAL ABUNDANCES IN NGC 5024 (M53): A MOSTLY FIRST GENERATION GLOBULAR CLUSTER

We present the Fe, Ca, Ti, Ni, Ba, Na, and O abundances for a sample of 53 red giant branch stars in the globular cluster (GC) NGC 5024 (M53). The abundances were measured from high signal-to-noise medium resolution spectra collected with the Hydra multi-object spectrograph on the Wisconsin–Indiana–Yale–NOAO 3.5 m telescope. M53 is of interest because previous studies based on the morphology of the cluster’s horizontal branch suggested that it might be composed primarily of first generation (FG) stars and differ from the majority of other GCs with multiple populations, which have been found to be dominated by the second generation (SG) stars. Our sample has an average [Fe/H] = −2.07 with a standard deviation of 0.07 dex. This value is consistent with previously published results. The alpha-element abundances in our sample are also consistent with the trends seen in Milky Way halo stars at similar metallicities, with enhanced [Ca/Fe] and [Ti/Fe] relative to solar. We find that the Na–O anti-correlation in M53 is not as extended as other GCs with similar masses and metallicities. The ratio of SG to the total number of stars in our sample is approximately 0.27 and the SG generation is more centrally concentrated. These findings further support that M53 might be a mostly FG cluster and could give further insight into how GCs formed the light element abundance patterns we observe in them today.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Gas phase vibrational spectroscopy of the protonated water pentamer: the role of isomers and nuclear quantum effects

We use cryogenic ion trap vibrational spectroscopy to study the structure of the protonated water pentamer, H + (H 2 O) 5 , and its fully deuterated isotopologue, D + (D 2 O) 5 , over nearly the complete infrared spectral range (220-4000 cm-1) in combination with harmonic and anharmon ic electronic structure calculations as well as RRKM modelling. Isomer-selective IR–IR double-resonance measurements on the H + (H 2 O) 5 isotopologue establish that the spectrum is due to a single constitutional isomer, thus discounting the recent analysis of the band pattern in the context of two isomers based on AIMD simulations < W. Kulig and N. Agmon, Phys. Chem. Chem. Phys., 2014, 16, 4933–4941 >. The evolution of the persistent bands in the D + (D 2 O) 5 cluster allows the assignment of the fundamentals in the spectra of both isotopologues, and the simpler pattern displayed by the heavier isotopologue is consistent with the calculated spectrum for the branched, Eigen-based structure originally proposed < J.-C. Jiang, et al., J. Am. Chem. Soc., 2000, 122, 1398–1410 >. This pattern persists in the vibrational spectra of H + (H 2 O) 5 in the temperature range from 13 K up to 250 K. The present study also underscores the importance of considering nuclear quantum effects in predicting the kinetic stability of these isomers at low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Toward Discord : Code for Simulating Continuous Spin Systems

A new computational tool to simulate classical spin systems with frustrated crystal structures is presented. Complementary single- and cluster-spin flip algorithms are implemented to calculate the diffuse scattering patterns, spin-pair correlations, and thermodynamic quantities. Test cases of geometrically frustrated kagome, pyrochlore, and cubic systems are detailed. Two recent scientific cases are also shown here. This new method, together with recent developments of the rmc-discord package (https://github.com/zjmorgan/rmc-discord), represent integrated and strategic step in a complete forward and reverse Monte Carlo framework discord.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-driven evaluation of HVAC operation and savings in commercial buildings

Commercial buildings consumed 36% of electricity, or 1.35 trillion kWh, in the United States in 2017, and almost 30% of this energy was wasted. Much of this loss can be attributed to inefficient heating ventilation and air con­ditioning (HVAC) systems. By improving the operational conditions of HVAC, significant savings can be achieved. However, most buildings and building equipment do not use costly sub-meters to monitor and address performance issues, and on-site auditing can be expensive and insufficient. Alternatively in this study, we propose a data-driven method to identify savings opportunities using only whole building meter data and without setting foot in the building. For this purpose, we introduced two algorithms that virtually quantify the value of a thermostat setpoint setback and HVAC rescheduling. Additionally, we developed novel methods for detecting occupancy patterns and quantifying the baseload of the HVAC operation. Using a clustering algorithm, we identified those buildings for which HVAC savings was significant and further categorized the buildings based on their potential for savings. A population study of over 432 commercial buildings demonstrated a median percentage energy savings of 1.6% from a baseload reduction and 2.1% from HVAC rescheduling. Additionally, results indicate that retail buildings have the highest potential for savings among the building types studied.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The Surface Chemistry of Methanol on Cu 3 Pd(111): Effects of Metal Alloying and Reaction with Hydrogen

Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu 3 Pd(111) model surface. The composition and morphological properties of the pristine Cu 3 Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu 3 Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with three-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd- Pd distances of 2.7-2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. Further, the valence band spectrum of Cu 3 Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu 3 Pd(111) at 300 K mainly produced CH 3 O, CO and CH x species. AP-XPS showed that most Pd atoms in the surface of the Cu 3 Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CH x , C and PdC x species from Cu 3 Pd(111) at moderate (< 450 K) temperatures and prevented a CH x → C transformation. If the stability of adsorbed CH 3 O is used as a descriptor for the hydrogenation of CO 2 to methanol, Cu 3 Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites.

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

Rapid Construction of Fe–Co–Ni Composition-Phase Map by Combinatorial Materials Chip Approach

100 nm thick Fe-Co-Ni materials chips were prepared and isothermally annealed at 500, 600 and 700oC, respectively. Pixel-by-pixel composition and structural mapping was performed by micro-beam X-ray at synchrotron light source. Diffraction images were recorded at a rate of 1 pattern/s. The XRD patterns were automatically processed, phase-identified and categorized by hierarchical clustering algorithm to construct the composition-phase map. Furthermore, the resulting maps are consistent with corresponding isothermal sections reported in the ASM Alloy Phase Diagram DatabaseTM, verifying the effectiveness of the present approach in phase diagram construction.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Chemiomics: Network Reconstruction and Kinetics of Port Wine Aging

Network reconstruction (NR) has proven to be useful in the detection and visualization of relationships among the compounds present in a Port wine aging data set. This view of the data provides a considerable amount of information with which to understand the kinetic contexts of the molecules represented by peaks in each chromatogram. The aim of this paper was to use NR together with the determination of kinetic parameters to extract more information about the mechanisms involved in Port wine aging. The volatile compounds present in samples of Port wines spanning 128 years in age were measured with the use of GC-MS. After chromatogram alignment, a peak matrix was created, and all peak vectors were compared to one another to determine their Pearson correlations over time. A correlation network was created and filtered on the basis of the resulting correlation values. Some nodes in the network were further studied in experiments on Port wines stored under different conditions of oxygen and temperature in order to determine their kinetic parameters. The resulting network can be divided into three main branches. The first branch is related to compounds that do not directly correlate to age, the second branch contains compounds affected by temperature, and the third branch contains compounds associated with oxygen. Compounds clustered in the same branch of the network have similar expression patterns over time as well as the same kinetic order, thus are likely to be dependent on the same technological parameters. Network construction and visualization provides more information with which to understand the probable kinetic contexts of the molecules represented by peaks in each chromatogram. Finally, the approach described here is a powerful tool for the study of mechanisms and kinetics in complex systems and should aid in the understanding and monitoring of wine quality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗