Containerless low gravity processing of glass forming and immiscible alloys

Under normal one-g conditions immiscible alloys segregate extensively during solidification due to sedimentation of the more dense of the immiscible liquid phases. Immiscible (hypermonotectic) gold-rhodium alloys were processed in the 100 meter drop tube under low gravity, containerless conditions to determine the feasibility of producing dispersed structures. Three alloy compositions were utilized. Alloys containing 10 percent by volume of the gold-rich hypermonotectic phase exhibited a tendency for the gold-rich liquid to wet the outer surface of the samples. This wetting tendency led to extensive segregation in several cases. Alloys containing 80 and 90 percent by volume of the gold-rich phase possessed completely different microstructures from the 10 percent samples when processed under low-g, containerless conditions. Several samples exhibited microstructures consisting of well dispersed 2 to 3 microns diameter rhodium-rich spheres in a gold-rich matrix

Asymptotic behavior of the number of Eulerian orientations of graphs

We consider the class of simple graphs with large algebraic connectivity (the second-smallest eigenvalue of the Laplacian matrix). For this class of graphs we determine the asymptotic behavior of the number of Eulerian orientations. In addition, we establish some new properties of the Laplacian matrix, as well as an estimate of a conditionality of matrices with the asymptotic diagonal predominanceComment: arXiv admin note: text overlap with arXiv:1104.304

Non-contact temperature measurement of a falling drop

The 105 meter drop tube at NASA-Marshall has been used in a number of experiments to determine the effects of containerless, microgravity processing on the undercooling and solidification behavior of metals and alloys. These experiments have been limited, however, because direct temperature measurement of the falling drops has not been available. Undercooling and nucleation temperatures are calculated from thermophysical properties based on droplet cooling models. In most cases these properties are not well known, particularly in the undercooled state. This results in a large amount of uncertainty in the determination of nucleation temperatures. If temperature measurement can be accomplished then the thermal history of the drops could be well documented. This would lead to a better understanding of the thermophysical and thermal radiative properties of undercooled melts. An effort to measure the temperature of a falling drop is under way. The technique uses two color pyrometry and high speed data acquisition. The approach is presented along with some preliminary data from drop tube experiments. The results from droplet cooling models is compared with noncontact temperature measurements

Method and apparatus for supercooling and solidifying substances

An enclosure provides a containerless environment in which a sample specimen is positioned. The specimen is heated in the containerless environment, and the specimen melt is dropped through the tube in which it cools by radiation. The tube is alternatively backfilled with an inert gas whereby the specimen melt cools by both radiation and convection during its free fall. During the free fall, the sample is in a containerless, low-gravity environment which enhances supercooling in the sample and prevents sedimentation and thermal convection influences. The sample continues to supercool until nucleation occurs which is detected by silicon photovoltaic detectors. The sample solidifies after nucleation and becomes completely solid before entering the detachable catcher. The amount of supercooling of the specimen can be measured by knowing the cooling ratio and determining the time for nucleation to occur

Polynomial Cointegration among Stationary Processes with Long Memory

n this paper we consider polynomial cointegrating relationships among stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zeroComment: 25 pages, 7 figures. Submitted in August 200

The SPAR thermal analyzer: Present and future

The SPAR thermal analyzer, a system of finite-element processors for performing steady-state and transient thermal analyses, is described. The processors communicate with each other through the SPAR random access data base. As each processor is executed, all pertinent source data is extracted from the data base and results are stored in the data base. Steady state temperature distributions are determined by a direct solution method for linear problems and a modified Newton-Raphson method for nonlinear problems. An explicit and several implicit methods are available for the solution of transient heat transfer problems. Finite element plotting capability is available for model checkout and verification