Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical simulation of natural convection and phase‐change in a horizontal Bridgman apparatus

Purpose – The purpose of this paper is to present a 2D numerical simulation of natural convection and phase‐change of succinonitrile in a horizontal Bridgman apparatus. Three different heat transfer mechanisms are specifically studied: no growth, solidification and melting.Design/methodology/approach – The analysis is carried out with a preexisting thermally coupled fixed‐mesh finite element formulation for generalized phase‐change problems.Findings – In the three cases analyzed, the predicted steady‐state liquid‐solid interfaces are found to be highly curved due to the development of a primary shallow cell driven by the imposed furnace temperature gradient. In the no growth case, the heating and cooling jackets remain fixed and, therefore, a stagnant liquid‐solid interface is obtained. On the other hand, the phase transformation in the solidification and melting cases is, respectively, controlled by the forward and backward movement of the jackets. In these last two growth conditions, the permanent regim.
Acoustical Measurements of Static Tests of Clustered and Single‐Nozzled Rocket Engines

The predictions of the acoustic effects of the static firing of large rocket engines have usually been based upon such engine parameters as specific impulse, nozzle diameter, etc. However, the recent development of large clusters of smaller engines have introduced a new possible variant. Tests were performed using two 1.5‐million‐ pound thrust rocket systems—one with a single engine and one with a cluster of eight smaller rockets. The two systems, NASA's F‐1 and Saturn S‐1, used the same liquid fuel and were fired on the same test stand. Due to this unusual test configuration, it was possible to equate most of the engine parameters to obtain a comparison of the acoustical effects resulting from static tests of clustered and single‐nozzled rockets of similar thrust class. Acoustical data are presented in this paper showing both the over all and octave‐band acoustic power levels for both test configurations. In addition, the differences in near‐ and far‐field directivities are presented.
Design and performance of a high-resolution frictional force microscope with quantitative three-dimensional force sensitivity

In this article, the construction and initial tests of a frictional force microscope are described. The instrument makes use of a microfabricated cantilever that allows one to independently measure the lateral forces in X and Y directions as well as the normal force. We use four fiber-optic interferometers to detect the motion of the sensor in three dimensions. The properties of our cantilevers allow easy and accurate normal and lateral force calibration, making it possible to measure the lateral force on a fully quantitative basis. First experiments on highly oriented pyrolytic graphite demonstrate that the microscope is capable of measuring lateral forces with a resolution down to 15pN.
Au-assisted molecular beam epitaxy of InAs nanowires: Growth and theoretical analysis

The Au-assisted molecular beam epitaxial growth of InAs nanowires is discussed. In situ reflection high-energy electron diffraction observations of phase transitions of the catalyst particles indicate that they can be liquid below the eutectic point of the Au-In alloy. The temperature range where the catalyst can be liquid covers the range where we observed nanowire formation (380–430 °C). The variation of nanowire growth rate with temperature is investigated. Pure axial nanowire growth is observed at high temperature while mixed axial/lateral growth occurs at low temperature. The change of the InAs nanowire shape with growth duration is studied. It is shown that significant lateral growth of the lower part of the nanowire starts when its length exceeds a critical value, so that their shape presents a steplike profile along their axis. A theoretical model is proposed to explain the nanowire morphology as a result of the axial and lateral contributions of the nanowire growth.
Bow flows in water of finite depth

Free‐surface flow past the bow of a ship in water of finite depth is considered. The bow is assumed to be a semi‐infinite two‐dimensional, flat‐bottomed body with a vertical front. The problem is solved numerically by series truncation for various values of the Froude number F. It is shown that there are splashless flows for 1.22
CO (3-2) Observations of Early-Type Galaxies with the Heinrich Hertz Telescope

We present Heinrich Hertz Telescope CO (3-2) observations of a sample of 10 early-type galaxies detected both in far-infrared (IRAS) and in CO (1-0). Six of the objects (i.e., 60% of the sample) were detected in the CO (3-2) transition. Comparison of the beam-matched CO (3-2)/CO (1-0) and CO (2-1)/CO (1-0) intensity ratios with simple large velocity gradient and photodissociation region models reveals that early-type objects can be broadly classified into two categories. The majority of objects have a molecular interstellar medium of moderate density (n ≤1000 cm-3) and temperature (T ≤ 30 K). Two objects, NGC 3593 and NGC 4691, show indications of quite denser and warmer environments, as well as gradients in their physical properties, compatible with their classification as starbursts. The heating source of the molecular gas and dust in all the objects in our sample appears to be ongoing star formation.
A neural network approach to analysing multi-component mixtures

This paper describes an approach for determining the individual analyte concentrations in a mixture of analytes using sensor fusion. Sensor fusion here is considered to be a process of gathering information from many different sources and combining these data to acquire pertinent information. The research reported in this paper uses sensor fusion and simulated, partially selective sensors. Through the use of simulated sensors, this research has investigated the advantages and limitation of sensor fusion and artificial neural networks. A three-layer back-propagation network was trained on a subset of component space and it was tested for its ability to generalize, where component space is defined as all possible combinations of input analyte concentration. A learning rate of 0.1 was used and no momentum terms were used. This research has shown that sensor fusion with an artificial neural network can accurately map sensor outputs to the actual input analyte concentrations. This research has also shown that increasing the number of sensors used improves the neural network performance. The neural network approach was found to be, under most circumstances, as good as or better than a mathematical technique using a curve fitting method of addressing the problem. The neural network technique was also found to be significantly faster than the mathematical technique and to possess good noise rejection attributes.
CP element based design for 14nm node EBDW high volume manufacturing

We had previously established CP (character projection) based EBDW technology for 65nm and 45nm device production. And recently we have confirmed the resolution of 14nm L&S patterns which meets 14nm and beyond node logic requirement with CP exposure. From these production achievement and resolution potential, with multi-beam EBDW and CP function, MCC [1] could be one of the most promising technologies for future high volume manufacturing if exposure throughput was drastically enhanced. We have set target throughput as 100 WPH to meet HVM (high volume manufacturing) requirement. Our designed parameters to attain 100 WPH for 14nm result in 150 beams, 10cluster, 100 Giga shots/wafer, 250A/cm^2 and 75uC/cm^2. In addition to multi-beam, drastic exposure shot reduction is indispensable to attain 100 WPH for 14nm node. We have aggressively targeted 100 Giga shot count which is equivalent to covering 300mm wafer with 0.8um x 0.8um square fairly large tile. All device circuit blocks should be structured with only CP defined parts and we should trace back to upstream design flow to RTL. We call this methodology "CP element based design". In near future, Litho-Friendly restricted design would be commonly used [3] [4]. Our CP defined tile based regular layout would be highly compatible with these ultra-regular design approaches. The primal design factors are Logic cell, Memory macro and random interconnect. We have established concepts to accomplish high volume production with CP-based EBDW at 14nm technology node.
A study of flow characteristics of a high repetition rate dye laser gain medium

The gain medium of a high repetition rate liquid dye laser is made to flow at a sufficiently high velocity through the dye cell in order to minimize the thermal inhomogeneity. In this paper, temperature contours as a function of distance from the pump beam entrance dye cell window wall at various flow velocities in the laminar and turbulent region of gain medium flow were evaluated using computational fluid dynamics (CFD). Appreciable temperature gradients subsist at low Reynolds numbers due to inefficient heat transfer from the gain medium. However, at high Reynolds numbers >6000, the substantial effects of local density turbulent fluctuations degrade the optical quality of the gain medium. These computational studies were used to elucidate the characteristics of observed spectral fluctuations of a dye laser as a function of the Reynolds number.
Mean field theory of directed polymers in a random medium and beyond

Starting from the mean field theory of directed polymers in a random medium, one can obtain 1/d expansions, valid for hypercubic lattices in the limit d → ∞. For finite dimensional lattices, one can predict bounds for the transition temperature and show that the specific heat exponent α is always negative (α ≤ 0). The mean field theory can be extended to the case where the statistical weights of the walks are no longer all positive, giving rise to interference effects. Lastly the problem of the branched polymers in a random medium is discussed.
All sky monitoring network with amateur telescopes

We describe here a multiband all sky monitoring system under construction using amateur resources. The system consists of a data management center and a network of telescopes. The total number of telescopes in this network can be huge and all the telescopes are not affected by their local weather or their operability so this network is capable of monitoring the whole night sky simultaneously in many different bands. The telescopes in the network can be operated on an individual basis or on a coordinated mode. The data taken by the telescopes in the network are sent to the data management center via internet where calibration, data fusion, data analysis are performed.
SPHERICAL MODEL ON THE BETHE LATTICE VIA THE STATISTICS OF WALKS

We give in explicit form a very general relation between the solution of the spherical model on a graph and the statistics of walks on the same graph. Such formulation sheds light on the role of topology in the statistical behaviour of model systems, since a graph is meant as a geometrical entity with no regard to any embedding space. This includes, of course, euclidean and fractal lattices as in particular cases. In this work we also show how this relation can be exploited to actually compute the thermodynamics of the model on a class of infinite graphs by giving the exact solution on Bethe lattices, where no euclidean metrics can be defined.
Possible (bi)polaron effects in the high-Tc superconductors

In the present paper, the theory of the large bipolaron is reviewed and the possibility of bipolaron formation in the high-Tc superconductors is indicated. Operator and path-integral formulations of the large bipolaron problem are compared. In the strong-coupling limit, the effect of non-optimal upperbounds to the single-polaron groundstate energy is emphasized. The fact that the interaction with multiple phonon branches enhances the electron–photon interaction and might result in a larger stability region for bipolaron formation is indicated. Experimental values for the static and high-frequency dielectric constants are used to discuss the relevance of bipolaron formation as a pair-forming mechanism in the high-Tc superconductors.
Analysis of scanning tunneling microscopy feedback system: Experimental determination of parameters

We describe the experimental work necessary on a scanning tunneling microscopy (STM) system to obtain some important feedback parameters—to have stability and good imaging conditions—such as the mechanical resonance frequency ω0, the delay time τ, and the damping factor ζ. We study and analyze each one of the main components involved on the STM such as the feedback system, the piezoelectric elements, the rigidity of the mechanical structure (the mechanical resonance), and its relation with the scanning rate for imaging. We conclude that it is necessary to obtain these parameters with the STM in tunnel conditions, in order to consider the effects of the tip, surface contamination, and tip sample interaction. We also conclude that tripod based STM can be better than STM based on piezo tubes scanners.
A topological optimization method for flexible multi-body dynamic system using epsilon algorithm

In a flexible multi-body dynamic system the typical topological optimization method for structures cannot be directly applied, as the stiffness varies with position. In this paper, the topological optimization of the flexible multi-body dynamic system is converted into structural optimization using the equivalent static load method. First, the actual boundary conditions of the control system and the approximate stiffness curve of the mechanism are obtained from a flexible multi-body dynamical simulation. Second, the finite element models are built using the absolute nodal coordination for different positions according to the stiffness curve. For efficiency, the static reanalysis method is utilized to solve these finite element equilibrium equations. Specifically, the finite element equilibrium equations of key points in the stiffness curve are fully solved as the initial solution, and the following equilibrium equations are solved using a reanalysis method with an error controlled epsilon algorithm. In order to identify the efficiency of the elements, a non-dimensional measurement is introduced. Finally, an improved evolutional structural optimization (ESO) method is used to solve the optimization problem. The presented method is applied to the optimal design of a die bonder. The numerical results show that the presented method is practical and efficient when optimizing the design of the mechanism.
Parameterization of the Condensation Process: A Theoretical Approach

Abstract A theoretical formulation is given that allows separate consideration of the major factors governing cloud droplet spectra in nonprecipitating cumulus clouds: activation of nuclei, condensational growth, and turbulent mixing. Broad spectra are treated as combinations of elementary droplet populations, each of which is characterized by its spectrum of activated nuclei (f0) and its degree of condensational growth (b2). The broadening of the spectra is described in terms of density functions of f0 and b2.
An optimisation of the Metropolis algorithm for multibit Markov random fields

The author presents a version of the Metropolis algorithm which is suitable for rapidly updating multibit Markov random fields. The fundamental objects on which the algorithm operates are the constituent binary digits of the field variables. A speed enhancement factor of O(2N/N) (for an N-bit representation) is obtained in comparison with a conventional Metropolis algorithm.
Non-linear primary-multiple separation with directional curvelet frames

SUMMARY Predictive multiple suppression methods consist of two main steps: a prediction step, during which multiples are predicted from seismic data, and a primary-multiple separation step, during which the predicted multiples are ‘matched’ with the true multiples in the data and subsequently removed. This second separation step, which we will call the estimation step, is crucial in practice: an incorrect separation will cause residual multiple energy in the result or may lead to a distortion of the primaries, or both. To reduce these adverse effects, a new transformed-domain method is proposed where primaries and multiples are separated rather than matched. This separation is carried out on the basis of differences in the multiscale and multidirectional characteristics of these two signal components. Our method uses the curvelet transform, which maps multidimensional data volumes into almost orthogonal localized multidimensional prototype waveforms that vary in directional and spatio-temporal content. Primaries-only and multiples-only signal components are recovered from the total data volume by a non-linear optimization scheme that is stable under noisy input data. During the optimization, the two signal components are separated by enhancing sparseness (through weighted l1-norms) in the transformed domain subject to fitting the observed data as the sum of the separated components to within a user-defined tolerance level. Whenever, during the optimization, the estimates for the primaries in the transformed domain correlate with the predictions for the multiples, the recovery of the coefficients for the estimated primaries will be suppressed while for regions where the correlation is small the method seeks the sparsest set of coefficients that represent the estimation for the primaries. Our algorithm does not seek a matched filter and as such it differs fundamentally from traditional adaptive subtraction methods. The method derives its stability from the sparseness obtained by a non-parametric (i.e. not depending on a parametrized physical model) multiscale and multidirectional overcomplete signal representation. This sparsity serves as prior information and allows for a Bayesian interpretation of our method during which the log-likelihood function is minimized while the two signal components are assumed to be given by a superposition of prototype waveforms, drawn independently from a probability function that is weighted by the predicted primaries and multiples. In this paper, the predictions are based on the data-driven surface-related multiple elimination method. Synthetic and field data examples show a clean separation leading to a considerable improvement in multiple suppression compared to the conventional method of adaptive matched filtering. This improved separation translates into an improved stack.
Three estimators of the Mahalanobis distance in high-dimensional data

This paper treats the problem of estimating the Mahalanobis distance for the purpose of detecting outliers in high-dimensional data. Three ridge-type estimators are proposed and risk functions for deciding an appropriate value of the ridge coefficient are developed. It is argued that one of the ridge estimator has particularly tractable properties, which is demonstrated through outlier analysis of real and simulated data.
Optimal classification of highly-reliable products whose degradation paths satisfy Wiener processes [1]

At the research and development stage of a product, the manufacturer usually faces the problem of classifying the better and worse designs among several competing designs for each of these parts (or components). It is a great challenge for the manufacturer if these completing designs are highly reliable, since there are few (or even no) failures that would be obtained by ruing traditional life tests or accelerated life tests. In such cases, if there exist product characteristics whose degradation over time can be related to reliability, then collecting “degradation data” can provide information about product reliability. This paper proposes a systematic approach to the classification problem where the products’ degradation paths satisfy Wiener processes. First, an intuitively appealing classification rule is proposed and, then, the optimal test plan is derived by using the criterion of minimizing the total experimental cost The sample size, inspection frequency, and the termination time needed by the clas.
Anatomy of a merger : CO in Arp 299 (IC 694-NGC 3690)

High-resolution (2.4-arcsec) CO observations of the interacting system Arp 299 (Mrk 171: IC 694 and NGC 3690) reveal major gas condensations at the nuclei of both galaxies and in the disk overlap region. The 0.9 x 10 to the 9th solar masses of H2 at the nucleus of NGC 3690 extends to radii of 310 pc and probably sustains a starburst. A compact source (radius not greater than 250 pc) of mass 3.9 x 10 to the 9th solar masses is found at the nucleus of IC 694; this galaxy may harbor an AGN. At least three discrete subcondensations, probably active star-forming knots, are detected in the 1800 x 640 pc overlap region. 24 refs.
A class of multivanate failure time distributions

SUMMARY A class- of continuous multivariate lifetime distributions is proposed. The dependence between individuals in a group is modelled by a group specific quantity, which can be interpreted as an unobserved covariate common to the individuals in the group and assumed to follow a positive stable distribution. It is possible to include covariates in the model and discuss whether the dependence is still present after specific covariates are taken into account. If the conditional hazards are proportional, then the hazards in the marginal distributions are also proportional, but with different constants of proportionality. Also the hazard for the minimum in a group is proportional to the marginal hazards. If the conditional distributions given the group quantity are Weibull then the marginal distributions are also Weibull. This class can be used to test the hypothesis of independence of litter mates in the proportional hazards model.
Robust Closed-Loop Control on a 2D-High-Lift-Device

This work shows the application of robust closed-loop strategies on a 2D high-lift configuration. The aim is to control the amount of lift achieved, instead of maximising that amount as it is usually done with open-loop set-ups. A way to model a 2D high-lift-device will be outlined, based on linear black-box-models of the lift as a function of the actuation amplitude. This model will be examined with respect to needed complexity and sensitivity to experimental parameters. In an experimental implementation the disturbance rejection and tracking capability of a synthesized closed-loop-controller will be shown and its possible use in aviation pointed out.
Learning Generic Local Shape Properties for Adaptive Super-Sampling

We propose a novel encoder/decoder-based neural network architecture that learns view-dependent shape and appearance of geometry represented by voxel representations. Since the network is trained on local geometry patches, it generalizes to arbitrary models. A geometry model is first encoded into a sparse voxel octree of features learned by a network, and this model representation can then be decoded by another network in-turn for the intended task. We utilize the network for adaptive super-sampling in ray-tracing, to predict super-sampling patterns when seeing coarse-scale geometry. We discuss and evaluate the proposed network design, and demonstrate that the decoder network is compact and can be integrated seamlessly into on-chip ray-tracing kernels. We compare the results to previous screen-space super-sampling strategies as well as non-network-based world-space approaches.