Particle melting in high temperature supersonic low pressure plasma jets

A numerical model has been developed to predict the temperature history of particles injected into a low pressure dc plasma jet. The temperature and velocity fields of the plasma jet are predicted as a free jet by solving the parabolized compressible Navier-Stokes equations using a spatial marching scheme. Particle trajectories and heat transfer characteristics are calculated using the predicted plasma jet temperature and velocity fields. Correction factors have been introduced to take into account noncontinuum effects encountered in the low pressure environment. The exchange of energy and momentum between the injected particles and plasma flow was treated by considering the source terms in the governing equations. The plasma jet profiles as well as the particle/plasma interactions with different jet pressure ratios (from underexpanded to overexpanded) have been investigated. The effect of particle loading on the resulting jet profiles, particle trajectories, and temperature profiles is presented and discussed. This paper is based on a presentation made in the T.B. King Memorial Symposium on “Physical Chemistry in Metals Processing” presented at the Annual Meeting of The Metallurgical Society, Denver, CO, February, 1987, under the auspices of the Physical Chemistry Committee and the PTD/ISS.     

Structure and physical properties of sodium borate glasses containing nickel oxide

A series of glass samples were prepared from a mixtures of B₂O₃, Na₂O and NiO. The role of nickel oxide in a glass matrix was studied by using infrared spectra, optical absorption, magnetic susceptibility, density, and differential thermal analysis (DTA). It was shown that the addition of nickel oxide at different concentrations to the glass batches causes some deformation in the glass structure. The values of ligand field strength and Racah parameter indicated an increasing degree of covalency. The glass samples exhibited diamagnetic behaviour with NiO content up to 1 g, then paramagnetic behaviour. The densities and glass transition temperatures decreased with increase in the NiO content up to 0.2 g and then increased again. This tendency may be related to changes in the glass structure.     

The effect of variation of angle of inclination on the performance of low-concentration-ratio compound parabolic concentrating solar collectors

Thermal heat transfer in line-axis, symmetric, compound parabolic concentrating solar energy collectors (CPCs) has been investigated and a theoretical numerical model has been developed. The model allows the effect of the angle of axial inclination of an east-west aligned CPC and hence the effect of the latitudinal and tracking configuration of the CPC system on performance to be determined. The internal and external convective heat transfer correlations employed are angular dependent. The variation of convective, radiative, conductive and overall heat transfer coefficients and system efficiency for a range of angular inclinations, concentration ratios, total insolations and beam to diffuse insolation factors are presented graphically. The results demonstrate that there is a 10% variation in convective heat transfer with angle of inclination for low concentration CPCs (i.e. C = 1.5).     

Effects of particle loading on a reduced pressure inductively coupled radio frequency plasma torch

Our previous attempts in the modeling of the heat transfer and fluid flow in radio frequency (RF) plasma torches considered dilute particle-loading conditions. It was assumed that the injected particles have no effect on the plasma temperature and velocity profiles. However, in practice, the plasma deposition process is carried out under fairly high loading conditions to achieve high energy efficiency. The plasma gas experiences significant local cooling and deceleration due to high particle injection rates. To this end, a numerical model has been developed which considers the coupling effects between the plasma temperature and velocity fields and injected particles. In this study, effort has been focused on the particle-loading effect in an inductively coupled RF plasma torch under a reduced pressure environment. The temperature and flow fields in an inductively coupled RF plasma torch are solved using an axisymmetric, variable property formulation of the Navier-Stokes equations. Pseudo two-dimensional electrical and magnetic field equations were considered. In addition, an integral constraint condition is used to maintain a specified discharge power in the plasma torch. The interaction between the plasma gas and injected particles is considered using the well-known “Particle-Source-In-Cell” (PSI-Cell) method. The exchanged mass, momentum, and energy between the plasma gas and injected particles are accounted for through additional source terms in the governing equations. The effect of particle loading on the resulting torch flow, thermal profiles, and particle-melting characteristics are presented and discussed.     

The hydrochloric acid route for phosphate rock

When phosphate rock is leached with hydrochloric acid, radium can be removed by co-precipitation with Ba_0.4Ca_0.6SO₄ and uranium by extraction with a 5% solution of tributyl phosphate in hexane or Varsol. Phosphoric acid is then separated from calcium chloride solution and other impurities by extraction with undiluted tributyl phosphate. The lanthanides can be precipitated from the raffinate by NH₃, and CaSO₄.2H₂O by H₂SO₄ to regenerate HCl for recycle. The organic phase containing H₃PO₄ can be stripped by NH₃ to yield ammonium phosphate and to regenerate the tributyl phosphate for recycle. Fluorine can be precipitated from the initial leach solution as Na₂SiF₆.     

Quantum information approach to the azurite mineral frustrated quantum magnet

Quantum correlations are almost impossible to address in bulk systems. Quantum measures extended only to a few number of parties can be discussed in practice. In the present work, we study nonlocality for a cluster of spins belonging to a mineral whose structure is that of a quantum magnet. We reproduce at a much smaller scale the experimental outcomes, and then, we study the role of quantum correlations there. A macroscopic entanglement witness has been introduced in order to reveal nonlocal quantum correlations between individual constituents of the azurite mineral at nonzero temperatures. The critical point beyond which entanglement is zero is found at \(T_c < 1\,\mathrm{K}\).     

Do multipartite correlations speed up adiabatic quantum computation or quantum annealing?

Quantum correlations are thought to be the reason why certain quantum algorithms overcome their classical counterparts. Since the nature of this resource is still not fully understood, we shall investigate how multipartite entanglement and non-locality among qubits vary as the quantum computation runs. We shall encounter that quantum measures on the whole system cannot account for their corresponding speedup.     

A declarative language to support dynamic evolution of web service business protocols

We investigate the problem of web service instances migration in the context of business protocol evolution, i.e., how to convert active instances of web services from an old version of a business protocol into a new one? We propose a framework based on a declarative approach to support service providers in defining fine-grained migration strategies of active instances. While the existing approaches for instances migration force the migrated instances to reflect the original ones as accurately as possible, in our approach we give to service providers the ability to declaratively define the constraints that drive the instances migration process. A migration strategy is expressed as a set of instances migration rules which are specified using an instance mapping language made of a set of generic migration patterns. The proposed approach has been implemented in a software tool that provides useful functionalities for protocol managers.     

Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees

Many data mining applications have a large amount of data but labeling data is often di cult, expensive, or time consuming, as it requires human experts for annotation.Semi-supervised learning addresses this problem by using unlabeled data together with labeled data to improve the performance. Co-Training is a popular semi-supervised learning algorithm that has the assumptions that each example is represented by two or more redundantly su cient sets of features (views) and additionally these views are independent given the class. However, these assumptions are not satis ed in many real-world application domains. In this paper, a framework called Co-Training by Committee (CoBC) is proposed, in which an ensemble of diverse classi ers is used for semi-supervised learning that requires neither redundant and independent views nor di erent base learning algorithms. The framework is a general single-view semi-supervised learner that can be applied on any ensemble learner to build diverse committees. Experimental results of CoBC using Bagging, AdaBoost and the Random Subspace Method (RSM) as ensemble learners demonstrate that error diversity among classi ers leads to an e ective Co-Training style algorithm that maintains the diversity of the underlying ensemble.