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At least 1,531 records · Page 85

Effects of cluster expansion on the locations of phase transition boundary as a first step to quantify uncertainty in first principles statistical mechanics framework

Predicting phase diagrams from first principle calculations eliminates the need of tedious experimental trials and errors. Fully automating first principle phase diagram calculations without any sort of human intervention has been a long daunting task and troubling scientific communities for decades. This grand problem remains not fully resolved, largely due to the vastly high-dimensional parameter space associated with density functional theory, cluster expansion, lattice Monte Carlo, and the substantial uncertainty propagating through a set of complex simulations. As a first step to tackle this grand problem, we reported a first demonstration of how sensitive phase boundary locations can be to various cluster expansion fittings and input DFT training data. To the best knowledge of the authors, this study reported the first ever attempt to quantify uncertainty in first principles statistical mechanics framework. In addition, a semi-automated phase transition detection algorithm has been devised in this paper to deal with the associated statistical errors and uncertainties from Monte Carlo method and its predecessor DFT calculations and cluster expansions. This algorithm has been applied in a classical cluster expansion Mg-Cd binary alloy system to detect phase transitions at various locations of phase diagram using different cluster expansions to demonstrate its predictive power and quantify uncertainties. The results suggested that using Chebyshev basis function shifted the transition locations toward the dilute solid solution phase and expanded the phase stability of concentrated ordered phases to wider composition range. The addition of perturbed defect configurations into training data set lowered the order-disorder transition temperature to be away from true transition temperature, suggesting the transition nature is indeed configurational disorder dominated rather than defect assisted. Finally, we found that the weighting has negligible effect on the transition locations, except for the case of using Chebyshev basis function to fit all non-weighted configurations that can be susceptible to Monte Carlo sampling hysteresis.

36 MATERIALS SCIENCE↗

Emergent disorder and mechanical memory in periodic metamaterials

Ordered mechanical systems typically have one or only a few stable rest configurations, and hence are not considered useful for encoding memory. Multistable and history-dependent responses usually emerge from quenched disorder, for example in amorphous solids or crumpled sheets. In contrast, due to geometric frustration, periodic magnetic systems can create their own disorder and espouse an extensive manifold of quasi-degenerate configurations. Inspired by the topological structure of frustrated artificial spin ices, we introduce an approach to design ordered, periodic mechanical metamaterials that exhibit an extensive set of spatially disordered states. While our design exploits the correspondence between frustration in magnetism and incompatibility in meta-mechanics, our mechanical systems encompass continuous degrees of freedom, and thus generalize their magnetic counterparts. We show how such systems exhibit non-Abelian and history-dependent responses, as their state can depend on the order in which external manipulations were applied. We demonstrate how this richness of the dynamics enables to recognize, from a static measurement of the final state, the sequence of operations that an extended system underwent. Thus, multistability and potential to perform computation emerge from geometric frustration in ordered mechanical lattices that create their own disorder.

36 MATERIALS SCIENCE↗

Symmetry-specific orientational order parameters for complex structures

A comprehensive framework of characterizing complex self-assembled structures with a set of orientational order parameters is presented. It is especially relevant in the context of using anisotropic building blocks with various symmetries. Two classes of tensor order parameters are associated with polyhedral nematic and bond orientational order. For the latter, a variation of classical bond order parameters (BOPs) is introduced, which takes advantage of the symmetry of constituent particles and/or expected crystalline phases. These symmetrized BOPs can be averaged over an entire system or assigned locally to an individual bond. By combining that with the bond percolation procedure, one is able to identify coherent domains within a self-assembled structure. As a demonstration of the proposed framework, we apply it to a simulated hybrid system that combines isotropic and patchy particles with octahedral symmetry. In conclusion, not only does the methodology allow one to identify individual crystalline domains but also it detects coherent clusters of a peculiar compact amorphous structure that is not space-filling and lacks any long-range order.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A first-order global model of Late Cenozoic climatic change: Orbital forcing as a pacemaker of the ice ages

The development of a theory of the evolution of the climate of the earth over millions of years can be subdivided into three fundamental, nested, problems: (1) to establish by equilibrium climate models (e.g., general circulation models) the diagnostic relations, valid at any time, between the fast-response climate variables (i.e., the 'weather statistics') and both the prescribed external radiative forcing and the prescribed distribution of the slow response variables (e.g., the ice sheets and shelves, the deep ocean state, and the atmospheric CO2 concentration); (2) to construct, by an essentially inductive process, a model of the time-dependent evolution of the slow-response climatic variables over time scales longer than the damping times of these variables but shorter than the time scale of tectonic changes in the boundary conditions (e.g., altered geography and elevation of the continents, slow outgassing, and weathering) and ultra-slow astronomical changes such as in the solar radiative output; and (3) to determine the nature of these ultra-slow processes and their effects on the evolution of the equilibrium state of the climatic system about which the above time-dependent variations occur. All three problems are discussed in the context of the theory of the Quaternary climate, which will be incomplete unless it is embedded in a more general theory for the fuller Cenozoic that can accommodate the onset of the ice-age fluctuations. We construct a simple mathematical model for the Late Cenozoic climatic changes based on the hypothesis that forced and free variations of the concentration of atmospheric greenhouse gases (notably CO2), coupled with changes in the deep ocean state and ice mass, under the additional 'pacemaking' influence of earth-orbital forcing, are primary determinants of the climate state over this period. Our goal is to illustrate how a single model governing both very long term variations and higher frequency oscillatory variations in the Pleistocene can be formulated with relatively few adjustable parameters.

Saltzman, Barry↗

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗

Accelerating quantum optics experiments with statistical learning

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstruct time-dependent data using a small number of detected photons, allowing for fast estimates in under a minute and providing a one-to-two order of magnitude speed-up in data acquisition time. We test our approach using real experimental data to retrieve the second order intensity correlation function, G (2) ($τ$), as a function of time delay τ between detector counts, for thermal light as well as anti-bunched light emitted by a quantum dot driven by periodic laser pulses. The proposed methodology has a wide range of applicability and has the potential to impact the scientific discovery process across a multitude of domains.

36 MATERIALS SCIENCE↗

Red supergiants and neutrino emission. II.

Investigation of the variation with stellar mass of the ratio of the numbers of blue and red supergiants. Statistical data for supergiants in young open clusters and subgroups of associations are collected to supplement a more restricted list presented earlier. Improved methods are used to identify hydrogen-burning supergiants, as well as faint supergiant remnants of binary mass exchange, and to arrange the bright evolved supergiants in order of their masses. Neither of these two operations requires knowledge of stellar distances or luminosities. Relevant published work on stellar evolution, rotation, mass loss, and duplicity is used to predict upper and lower limits on the blue-to-red ratio. It is concluded that the observed paucity of very massive red supergiants (and of carbon stars) confirms and extends the trend previously observed, and thereby supports the idea of neutrino-induced acceleration of the carbon burning and later phases of evolution; the h and chi Persei association shows the same dependence of the blue-to-red-ratio on stellar mass as do other clusters and associations; and a moderate decrease of the blue-to-red ratio is observed with increasing galactocentric distance in the Galaxy (as in M33) and seems to be due to a relative scarcity of extremely young stars in distant galactic regions.

Stothers, R.↗

Flash photolysis resonance fluorescence investigation of the reaction of Cl/2P/ atoms with ClONO2

Rate constants for the removal of Cl(2P) atoms by homogeneous gas phase reaction with ClONO2 were measured using the flash photolysis resonance fluorescence technique at 224, 250, and 273 K. The values obtained have been used to derive the above Arrhenius equation. The uncertainties expressed are 95% confidence limits obtained using the statistical standard deviation of the individual rate constants plus a 15% additional estimated uncertainty attributed to difficulties in chlorine nitrate concentration measurements. The results indicate that destruction of chlorine nitrate by reaction with chlorine atoms is perhaps the least important of the atmospheric reactive channels, and is at least three orders of magnitude slower than calculated photodissociation rates at all stratospheric altitudes.

Kurylo, M. J.↗

On the timing of an interstellar communication

By considering prominent events that are observable from both earth and nearby stellar systems it is possible to establish common clocks that may be useful in estimating arrival times for signals of intelligent extraterrestrial origin. The geometry and statistics of a timing strategy are developed together with quantitative estimates of its effectiveness and limits on its application. Effectiveness is measured by comparing the timing strategy with one randomized in time. Limitations arise from inaccuracies inherent in the determination of stellar parallaxes and result in standard deviations of the order of weeks to months for time estimates. The problem can be alleviated by choosing clocks close to Sender in angular distance. Signal opportunities for several nearby sun-like stars are calculated using the bright Nova Cygni 1975 as a clock.

Mclaughlin, W. I.↗

Prediction of spacecraft potentials at geosynchronous orbit

Two relatively straightforward techniques are outlined for determining spacecraft potentials in the limit of a 'thick sheath' surrounding the spacecraft. A statistical model of the various features of the geosynchronous environment based on ATS-5 and ATS-6 data and an analytic model capable of detailed simulation of the low energy geosynchronous environment are also discussed. The results from these two environmental models are then combined with the charging models in order to provide estimates of the relationships between the geomagnetic index and spacecraft potential. The results are compared with actual potential measurements from ATS-5 and ATS-6.

Garrett, H. B.↗

International ultraviolet explorer observatory operations

This volume contains the Final Report for the International Ultraviolet Explorer (IUE) Observatory Operations contract, NAS5-28787. The report summarizes the activities of the IUE Observatory over the 13-month period from November 1985 through November 1986 and is arranged in sections according to the functions specified in the Statement of Work (SOW) of the contract. In order to preserve numerical correspondence between the technical SOW elements specified by the contract and the sections of this report, project management activities (SOW element 0.0.) are reported here in Section 7, following the reports of technical SOW elements 1.0 through 6.0. Routine activities have been summarized briefly whenever possible; statistical compilations, reports, and more lengthy supplementary material are contained in the Appendices.

Source record↗

Total Quality Management: Analysis, Evaluation and Implementation Within ACRV Project Teams

Total quality management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The Assured Crew Return Vehicle (ACRV) Project Office was identified as an excellent project in which to demonstrate the applications and benefits of TQM processes. As the ACRV Program moves through its various stages of development, it is vital that effectiveness and efficiency be maintained in order to provide the Space Station Freedom (SSF) crew an affordable, on-time assured return to Earth. A critical factor for the success of the ACRV is attaining the maximum benefit from the resources applied to the program. Through a series of four tutorials on various quality improvement techniques, and numerous one-on-one sessions during the SSF's 10-week term in the project office, results were obtained which are aiding the ACRV Office in implementing a disciplined, ongoing process for generating fundamental decisions and actions that shape and guide the organization. Significant advances were made in improving the processes for two particular groups - the correspondence distribution team and the WATER Test team. Numerous people from across JSC were a part of the various team activities including engineering, man systems, and safety. The work also included significant interaction with the support contractor to the ACRV Project. The results of the improvement activities can be used as models for other organizations desiring to operate under a system of continuous improvement. In particular, they have advanced the ACRV Project Teams further down the path of continuous improvement, in support of a working philosophy of TQM.

Raiman, Laura B.↗

Comparison of wind speed measurements over the oceans with the Special Sensor Microwave/Imager and the Geosat altimeter

In order to compare wind speed estimates from the Geosat altimeter and the Special Sensor Microwave/Imager (SSM/I), 25 colocated passes, within 2 hours of each other, were selected and the SSM/I estimates of wind speed and atmospheric parameters extracted along the Geosat track. Both instruments and their algorithms are described. A statistical comparison of wind speed estimates is presented and the effects of the atmospheric parameters from Geosat are analyzed. Quasi-simultaneous measurements by Geosat and SSM/I, along a Geosat track in the North-East Pacific, are also presented.

Mognard, Nelly M.↗

Comparison of wind speed measurements over the oceans with the Special Sensor Microwave/Imager and the Geosat altimeter

In order to compare wind speed estimates from the Geosat altimeter and the Special Sensor Microwave/Imager (SSM/I), 25 colocated passes, within 2 hours of each other, were selected and the SSM/I estimates of wind speed and atmospheric parameters extracted along the Geosat track. Both instruments and their algorithms are described. A statistical comparison of wind speed estimates is presented and the effects of the atmospheric parameters from Geosat are analyzed. Quasi-simultaneous measurements by Geosat and SSM/I, along a Geosat track in the North-East Pacific, are also presented.

Mognard, Nelly M.↗

Physical Characterization of the Near-Earth Object Population

Many pieces of the puzzle must be brought together in order to have a clear picture of the near-Earth object (NEO) population. Four of the pieces that can be described include: i) the taxonomic distribution of the population as measured by observational sampling, ii) the determination of albedos that can be associated with the taxonomic distribution, iii) discovery statistics for the NE0 population, and iv) the debiasing of the discovery statistics using the taxonomic and albedo information. Support from this grant enables us to address three of these four pieces. Binzel et al. (2004, submitted) presents the first piece, detailing the observations and observed characteristics of the NE0 and Mars-crossing (MC) population. For the second piece, a complementary program of albedo measurements is pursued at the Keck Observatory (Binzel, P. I.) with first results published in Delbo et al. (2003). For the third piece, the most extensive NE0 discovery statistics are provided by the LINEAR survey. Binzel has supervised the MIT Ph. D. thesis work of Stuart (2003) to bring the fourth piece, submitted for publication by Stuart and Binzel (2004). Our results provide new constraints for the NE0 population and progress for the Spaceguard Survey, illuminate asteroid and comet source regions for the NEOs, and provide new evidence for space weathering processes linking asteroids and meteorites. Further, we are identifying top priority near-Earth spacecraft mission candidates based on their spectral properties and inferred compositions.

Binzel, Richard P.↗

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗

Ensemble average and nearest particle statistics in disperse multiphase flows

A relation between the ensemble average and the nearest particle statistics is derived. The relation accounts for interactions among all the particles, not only the nearest one, and can be used to study long-range particle interactions without the difficulty of a divergent integral. As an example, this relation is applied to calculate the particle sedimentation velocity to the first order of the particle volume fraction. Using the relation, an important particle–fluid–particle stress is introduced for general multiphase flows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗