Rigorizing the use of the coefficient of variation to diagnose fracture periodicity and clustering
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02 PETROLEUM↗
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Suppression of vacancy cluster growth in concentrated solid solution alloys
Large vacancy clusters, such as stacking-fault tetrahedra, are detrimental vacancy-type defects in ion-irradiated structural alloys. Suppression of vacancy cluster formation and growth is highly desirable to improve the irradiation tolerance of these materials. In this paper, we demonstrate that vacancy cluster growth can be inhibited in concentrated solid solution alloys by modifying cluster migration pathways and diffusion kinetics. The alloying effects of Fe and Cr on the migration of vacancy clusters in Ni concentrated alloys are investigated by molecular dynamics simulations and ion irradiation experiment. While the diffusion coefficients of small vacancy clusters in Ni-based binary and ternary solid solution alloys are higher than in pure Ni, they become lower for large clusters. This observation suggests that large clusters can easily migrate and grow to very large sizes in pure Ni. In contrast, cluster growth is suppressed in solid solution alloys owing to the limited mobility of large vacancy clusters. Finally, the differences in cluster sizes and mobilities in Ni and in solid solution alloys are consistent with the results from ion irradiation experiments.
36 MATERIALS SCIENCE↗
Role of weakly bound complexes in temperature-dependence and relative rates of M x O y – + H 2 O ( M = Mo, W) reactions
Results of a systematic comparison of the Mo x O y – + H 2 O and W x O y – + H 2 O reaction rate coefficients are reported and compared to previous experimental and computational studies on these reactions. W x O y – clusters undergo more direct oxidation by water to yield W x O y+1 – + H 2 , while for Mo x O y – clusters, production of Mo x O y H 2 – (trapped intermediates in the oxidation reaction) is comparatively more prevalent. However, Mo x O y – clusters generally have higher rate coefficients than analogous W x O y – clusters if Mo x O y+1 H 2 – formation is included. Results of calculations on the M 2 O y – + H 2 O (M = Mo, W; y = 4, 5) reaction entrance channel are reported. They include charge-dipole complexes formed from long-range interactions, and the requisite conversion to a Lewis acid-base complex that leads to M x O y+1 H 2 – formation. The results predict that the Lewis acid-base complex is more strongly bound for Mo x O y – clusters than for W x O y – clusters. The calculated free energies along this portion of the reaction path are also consistent with the modest anti-Arrhenius temperature dependence measured for most Mo x O y – + H 2 O reactions, and the W x O y – + H 2 O reaction rate coefficients generally being constant over the temperature range sampled in this study. For clusters that exhibit evidence of both water addition and oxidation reactions, increasing the temperature increases the branching ratio toward oxidation for both species. In conclusion, a more direct reaction path to H 2 production may therefore become accessible at modest temperatures for certain cluster stoichiometries and structures.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ordering-mediated local nano-clustering results in unusually large Hall-Petch strengthening coefficients in high entropy alloys
This paper reports a dramatic increase in the grain boundary strengthening or Hall-Petch coefficient, K, by systematically investigating the effect of Al addition on tensile yield strength in CoFeNi and CoCrFeNi high entropy alloys (HEAs) or complex concentrated alloys (CCAs). Additionally, detailed atom probe tomography (APT) revealed a high number density of Ni-Al rich nano-clusters in the Al 0.3 CoFeNi and Al 0.3 CoCrFeNi HEAs/CCAs, which can be rationalized based on the strong chemical ordering tendency between these elements. Consequently, the huge increase in K value can be attributed to the additional stress required for overcoming coherency strain fields arising from these nano-clusters.
36 MATERIALS SCIENCE↗
Geography of cretaceous extinctions: Data base development
Data bases built from the source literature are plagued by problems of data quality. Unless the data acquisition is done by experts, working slowly, the data base may contain so much garbage that true signals and patterns cannot be detected. On the other hand, high quality data bases develop so slowly that satisfactory statistical analysis may never be possible due to the small sample sizes. Results of a test are presented of the opposite strategy: rapid data acquisition by non-experts with minimal control on data quality. A published list of 186 species and genera of fossil invertibrates of the latest Cretaceous Age (Maestrichtian) were located through a random search of the paleobiological and geological literature. The geographic location for each faunal list was then transformed electronically to Maestrichtian latitude and longitude and the lists were further digested to identify the genera occurring in each ten-degree, latitude-longitude block. The geographical lists were clustered using the Otsuka similarity coefficient and a standard unweight-pair-group method. The resulting clusters are remarkably consistent geographically, indicating that a strong biogeographic signal is visible despite low-quality data. A further test evaluated the geographic pattern of end-Cretaceaous extinctions. All genera in the data base were compared with Sepkoski's compendium of time ranges of genera to determine which of the reported genera survived the Cretaceous mass extinction. In turn, extinction rates for the ten-degree, latitude-longitude blocks were mapped. The resulting distribution is readily interpretable as a robust pattern of the geography of the mass extinction. The study demonstrates that a low-quality data base, built rapidly, can provide a basis for meaningful analysis of past biotic events.
Raup, D. M.↗
Clustering reactions of H2CN(+) ions with HCN
The rate coefficients for the first and second steps in the clustering sequence of H2CN(+) ions with HCN, H2CN(+) + HCN + M - H2CN(+) (HCN) + M and H2CN(+) (HCN) + HCN + M - H2CN(+) (HCN)2 + M, have been measured at temperatures from 189 to 296 K for M = He. The three-body association rate coefficients for both reactions are least-squares fitted for a power dependence on gas temperature. The temperature dependences of the three-body association reaction rate coefficients fitted in the range 200 to 300 K are given. The absolute values and temperature dependences are rather similar.
Chatterjee, B. K.↗
Synthesis of a laterally displaced cluster feed for a reflector antenna with application to multiple beams and contoured patterns
Two methods are described for efficiently synthesizing the excitation coefficients of a laterally displaced cluster feed in a reflector antenna subject to beam distortion. Applications are presented for rotationally symmetric paraboloids excited by an equilateral triangular array of feed elements. The basic cluster is a central element surrounded by a hexagonal ring. The first method - termed the sequential current method - determines a set of excitation coefficients which minimizes the phase distortion in the 'effective' aperture distribution of the reflector. The second method - termed the gradient optimization method - is such that the distortion in the secondary power pattern is directly minimized in a min-L2 form by a gradient optimization algorithm regarded as a systematic computer iteration procedure. Application to the synthesis of contour patterns is included.
Galindo-Israel, V.↗
M-DAS: System for multispectral data analysis
M-DAS is a ground data processing system designed for analysis of multispectral data. M-DAS operates on multispectral data from LANDSAT, S-192, M2S and other sources in CCT form. Interactive training by operator-investigators using a variable cursor on a color display was used to derive optimum processing coefficients and data on cluster separability. An advanced multivariate normal-maximum likelihood processing algorithm was used to produce output in various formats: color-coded film images, geometrically corrected map overlays, moving displays of scene sections, coverage tabulations and categorized CCTs. The analysis procedure for M-DAS involves three phases: (1) screening and training, (2) analysis of training data to compute performance predictions and processing coefficients, and (3) processing of multichannel input data into categorized results. Typical M-DAS applications involve iteration between each of these phases. A series of photographs of the M-DAS display are used to illustrate M-DAS operation.
Johnson, R. H.↗
Evacuation decision behavior for no-notice emergency events
No-notice emergency events refer to unpredictable disasters such as earthquakes, chemical spills, or terrorist attacks, where it is impracticable to forewarn the public about their occurrence and design evacuation plans for them. This calls for an in-depth investigation of people’s evacuation behavior and identifying the most influential factors in their evacuation planning process to develop policy-sensitive pre-disaster plans for such events. As a response to this need, this study investigates individuals’ evacuation decision behavior in the context of no-notice emergency events. Since it is highly expected that people will have heterogenous decision behavior in such situations, we first apply a clustering algorithm to classify them into three maximally homogeneous clusters. Then, cluster-specific multivariate ordered probit models are developed to estimate the likelihood of selecting any of the three options of ignoring the situation, seeking shelter at the place, and evacuating to a safe place. The model estimation results indicate that a wide spectrum of factors affect the evacuation decision including individuals’ socio-economic attributes, disaster characteristics, built-environment factors, and government evacuation order. Further, variations of estimated coefficients across the population clusters highlight the significant dissimilarities in decision behavior of their associated members.
99 GENERAL AND MISCELLANEOUS↗
X-ray Scattering and Coarse-Grained Simulations for Clustering and Interactions of Monoclonal Antibodies at High Concentrations
Attractive protein-protein interactions (PPI) in concentrated monoclonal antibody (mAb) solutions may lead to reversible oligomers (clusters) that impact colloidal stability and viscosity. Herein, the PPI are tuned for two mAbs via the addition of arginine (Arg), NaCl, or ZnSO 4 as characterized by the structure factor ( S eff (q)) with small angle x-ray scattering (SAXS). The SAXS data are fit with molecular dynamics simulations by placing a physically relevant short-ranged attractive interaction on selected beads in coarse-grained 12 bead models of the mAb shape. The optimized 12-bead models are then used to differentiate key microstructural properties, including center of mass radial distribution functions ( g COM (r)), coordination numbers and cluster size distributions (CSD). The addition of co-solutes results in more attractive Seff(q) relative to the no co-solute control for all systems tested, with the most attractive systems showing an upturn at low q . Only the All1 model with an attractive site in each Fab and Fc region (possessing Fab-Fab, Fab-Fc and Fc-Fc interactions) can reproduce this upturn, and the corresponding CSDs show the presence of larger clusters compared to the control. In general, for models with similar net attractions, i.e., second osmotic virial coefficients, the size of the clusters increases as the attraction is concentrated on a smaller number of evenly distributed beads. Here, the cluster size distributions from simulations are used to improve the understanding and prediction of experimental viscosities. The ability to discriminate between models with bead interactions at particular Fab and Fc bead sites from SAXS simulations, and to provide real space properties (CSD and g COM (r)), will be of interest in engineering protein sequence and formulating protein solutions for weak PPI to minimize aggregation and viscosities.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SU-E-J-272: Auto-Segmentation of Regions with Differentiating CT Numbers for Treatment Response Assessment
Purpose: It has been reported recently that the change of CT number (CTN) during and after radiation therapy (RT) may be used to assess RT response. The purpose of this work is to develop a tool to automatically segment the regions with differentiating CTN and/or with change of CTN in a series of CTs. Methods: A software tool was developed to identify regions with differentiating CTN using K-mean Cluster of CT numbers and to automatically delineate these regions using convex hull enclosing method. Pre- and Post-RT CT, PET, or MRI images acquired for sample lung and pancreatic cancer cases were used to test the software tool. K-mean cluster of CT numbers within the gross tumor volumes (GTVs) delineated based on PET SUV (standard uptake value of fludeoxyglucose) and/or MRI ADC (apparent diffusion coefficient) map was analyzed. The cluster centers with higher value were considered as active tumor volumes (ATV). The convex hull contours enclosing preset clusters were used to delineate these ATVs with color washed displays. The CTN defined ATVs were compared with the SUV- or ADC-defined ATVs. Results: CTN stability of the CT scanner used to acquire the CTs in this work is less than 1.5 Hounsfield Unit (HU) variation annually. K-mean cluster centers in the GTV have difference of ∼20 HU, much larger than variation due to CTN stability, for the lung cancer cases studied. The dice coefficient between the ATVs delineated based on convex hull enclosure of high CTN centers and the PET defined GTVs based on SUV cutoff value of 2.5 was 90(±5)%. Conclusion: A software tool was developed using K-mean cluster and convex hull contour to automatically segment high CTN regions which may not be identifiable using a simple threshold method. These CTN regions were reasonably overlapped with the PET or MRI defined GTVs.
60 APPLIED LIFE SCIENCES↗
Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements
Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.
17 WIND ENERGY↗
Analyzing Malaysians’ perception of risk in developing radiological and nuclear crisis communication framework
Crisis communication is an indicator of a sustaining public normalcy that serves to control and decrease any untoward situations during disasters’ meltdown. Prior findings highlighted that 25.85 percent of arising organizational disputes can be resolved using public announcements and an enhancement of public awareness through avoiding related dissatisfactions, disorders and untoward circumstances during radiation and nuclear emergencies. Hence, in this paper, we are interrogating Malaysians on their perception of risk regarding to radiation and nuclear disasters and emergencies. The principal aim is to identify the relationship between the IAEA’s initiated risk perception characteristics and the content of the respective public acceptance reports. Those relationships are described and analyzed into a network diagram using the ATLAS.ti software consisting of Clustering and C-Coefficient analyses. This diagram identifies the main variables relating to significant characteristics of risk perception. Future studies should further evaluate the intensity of public opinion against the suggested constructs of executing a thorough and structured risk management mechanism, to advance public trust as well as crisis communication.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Soft-sphere simulations of a planar shock interaction with a granular bed
Here we consider the problem of shock propagation through a layer of spherical particles. A point particle force model is used to capture the shock-induced aerodynamic force acting upon the particles. The discrete element method (DEM) code liggghts is used to implement the shock-induced force as well as to capture the collisional forces within the system. A volume-fraction-dependent drag correction is applied using Voronoi tessellation to calculate the volume of fluid around each individual particle. A statistically stationary frame is chosen so that spatial and temporal averaging can be performed to calculate ensemble-averaged macroscopic quantities, such as the granular temperature. A parametric study is carried out by varying the coefficient of restitution for three sets of multiphase shock conditions. A self-similar profile is obtained for the granular temperature that is dependent on the coefficient of restitution. A traveling wave structure is observed in the particle concentration downstream of the shock and this instability arises from the volume-fraction-dependent drag force. The intensity of the traveling wave increases significantly as inelastic collisions are introduced. Downstream of the shock, the variance in Voronoi volume fraction is shown to have a strong dependence upon the coefficient of restitution, indicating clustering of particles induced by collisional dissipation. Statistics of the Voronoi volume are computed upstream and downstream of the shock and compared to theoretical results for randomly distributed hard spheres.
42 ENGINEERING↗
On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes
Abstract. Hillslope similarity is an active topic in hydrology because of its importance in improving our understanding of hydrologic processes and enabling comparisons and paired studies. In this study, we propose a holistic bottom-up hillslope clustering based on a region's integrative hydrodynamic response quantified by the seasonal changes in groundwater levels ΔP. The main advantage of the ΔP clustering is its ability to capture recharge and discharge processes. We test the performance of the ΔP clustering by comparing it to seven other common hillslope clustering approaches. These include clustering approaches based on the aridity index, topographic wetness index, elevation, land cover, and machine-learning that jointly integrate multiple data. We assess the ability of these clustering approaches to identify and categorize hillslopes with similar static characteristics, hydroclimate, land surface processes, and subsurface dynamics in a mountainous watershed – the East River – located in the headwaters of the Upper Colorado River Basin. The ΔP clustering performs very well in identifying hillslopes with six out of the nine characteristics studied. The variability among clusters as quantified by the coefficient of variation (0.2) is less in the ΔP and the machine learning approaches than in the others (> 0.3 for TWI, elevation, and land cover). We further demonstrate the robustness of the ΔP clustering by testing its ability to predict hillslope responses to wet and dry hydrologic conditions, of which it performs well when based on average conditions.
54 ENVIRONMENTAL SCIENCES↗
Cluster bootstrap for cosmological correlators
We show that cosmological wavefunction coefficients associated with n-site chain and loop graphs for a cubic scalar theory in de Sitter spacetime have symbol alphabets given by subsets of A 2n−2 and B 2n−1 cluster variables, respectively, and satisfy the associated cluster adjacency properties. The key step in proving this is identifying a precise connection between graph “tubings” that appear in the kinematic flow equation and polygon “triangulations” that encode the combinatorics of cluster compatibility. Our results imply that cosmological wavefunction coefficients in a general power-law FRW cosmology satisfy cluster adjacency to all orders in the ϵ expansion around the de Sitter limit. We use this information as bootstrap input to show that de Sitter symbols for n ≤ 4 are uniquely determined by simple physical constraints.
differential and algebraic geometry↗
Plasma decay in hydrocarbons and hydrocarbon- and H 2 O-containing mixtures excited by high-voltage nanosecond discharge at elevated gas temperatures
Plasma decay after a high-voltage nanosecond discharge was experimentally and numerically studied in pure hydrocarbons (C 2 H 6 and C 3 H 8 ), and H 2 O:N 2 and C 3 H 8 :O 2 mixtures for pressures in the range 2–4 Torr and gas temperatures from 300 to 600 K. In a stoichiometric C 3 H 8 :O 2 mixture, plasma decay was also studied in a repetitively pulsed discharge for varing numbers of discharge pulses (varying degrees of fuel oxidation). The rate of plasma decay was determined from the temporal evolution of electron density measured using the microwave interferometer. It was observed that gas heating to 600 K leads to a decrease in the rate of plasma decay in all cases. The effect of heating on plasma decay was most profound in the H 2 O:N 2 mixture (after a single discharge pulse) and in the C 3 H 8 :O 2 mixture for high degrees of fuel oxidation. A kinetic scheme was developed to numerically simulate the plasma decay in hydrocarbons and combustible mixtures. Numerical analysis showed that, under the conditions studied, plasma decay was controlled by dissociative electron recombination with simple molecular and cluster ions. Gas heating led to a decrease in the rate of the electron-ion recombination and the rate of conversion of molecular ions to cluster ions. As a result, the gas temperature increase caused a decrease in the fraction of cluster ions for which the recombination coefficients are an order of magnitude higher than the recombination coefficients for molecular ions. The influence of gas heating on the decrease of the amount of cluster ions was more important when the ion composition was dominated by hydrated H 3 O + (H 2 O) k ions. The rates of the formation of these ions are extremely sensitive to any variations in gas temperature. A result, in agreement with our observations, gas heating led to an anomalous decrease in the rates of plasma decay in the H 2 O:N 2 mixture, as well as in the C 3 H 8 :O 2 mixture when H 2 O molecules were produced due to fuel oxidation.
20 FOSSIL-FUELED POWER PLANTS↗
Plasma Decay in the Afterglow of High-Voltage Nanosecond Discharges in Unsaturated and Oxygenated Hydrocarbons
Results of experimental and theoretical study of plasma decay in the afterglow of high-voltage nanosecond discharges in gaseous ethylene and dimethyl ether at room temperature and pressures from 2 to 20 Torr are presented. Using a microwave interferometer, the time behavior of the electron density in the range from 2 × 10{sup 10} to 3 × 10{sup 12} cm{sup –3} during plasma decay is investigated. By processing the experimental data, the effective coefficients of electron–ion recombination as functions of the gas pressure are obtained. It is found that these coefficients substantially exceed the recombination coefficients of simple hydrocarbon ions. This distinction, as well as the increase in the effective recombination coefficient with pressure, is explained by the formation of cluster ions in three-body collisions, which recombine with electrons more efficiently than simple molecular ions. The coefficients of three-body conversion of simple molecular ions into cluster ions in the plasmas of ethylene and dimethyl ether, as well as the coefficients of recombination of electrons with cluster ions in these gases, are determined by analyzing the experimental data.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗