A model for transitional breakage probability of droplets in agitated lean liquid-liquid dispersions

A model for transitional breakage probability of droplets in agitated lean fiquid-liquid dispersions is proposed based on the mechanism of breakage of droplets due to their oscillations resulting from relative velocity fluctuations. A universal transitional breakage probability in terms of non-dimensionalized drop diameter is derived for all dispersed phases whose density and viscosity are almost the same as that of continuous phase. The maximum stable drop diameter d_s derived from the model, shows a dependence of N_We^?0.6. It is shown that a “power law” approximation Kvⁿ is valid for transitional breakage probability for d/d_s up to 2. The exponent 2.67, predicted by this model corresponds rather well with an estimate of 2, obtained from experimental observations. A functional relation for the rate constant K in terms of the parameters and physical properties of the system is derived. A universal non-dimensionalized equilibrium drop-size distribution for agitated lean liquid-liquid dispersions is derived by analytical solution of a population balance equation simplified by order of magnitude estimates. Interestingly enough, this analytical solution is the same as the Gaussian distribution suggested empirically by Chen and Middleman.     

AVCOL: Availability-aware information aggregation in large distributed systems under uncollaborative behavior

Aggregation of system-wide information in large-scale distributed systems, such as p2p systems and Grids, can be unfairly influenced by nodes that are selfish, colluding with each other, or are offline most of the time. We present AVCOL, which uses probabilistic and gossip-style techniques to provide availability-aware aggregation. Concretely, AVCOL is the first aggregation system that: (1) implements any (arbitrary) global predicate that explicitly specifies any node’s probability of inclusion in the global aggregate, as a mathematical function of that node’s availability (i.e., percentage time online); (2) probabilistically tolerates large numbers of selfish nodes and large groups of colluders; and (3) scales well with hundreds to thousands of nodes. AVCOL uses several unique design decisions: per-aggregation tree construction where nodes are allowed a limited but flexible probabilistic choice of parents or children, probabilistic aggregation along trees, and auditing of nodes both during aggregation as well as in gossip-style (i.e., periodically). We have implemented AVCOL, and we experimentally evaluated it using real-life churn traces. Our evaluation and our mathematical analysis show that AVCOL satisfies arbitrary predicates, scales well, and withstands a variety of selfish and colluding attacks.     

A closed-loop cross-correlation method for detecting model mismatch in MIMO model-based controllers

Correlation between a dithering signal and the prediction error has been used for detecting model mismatch in univariate model based control systems. This paper extends that approach to MIMO control systems. A closed-loop cross-correlation method is presented to detect which specific input-output pairings of a model-based controller are mismatched. This method may be used in screening the complete set of models and in selecting candidate models for re-identification. The method first finds the rows and columns of the transfer function matrix that contain mismatch, and then the candidates are found by the intersection of the said rows and columns. Placing the system under partial control, whereby one or more of the manipulated variables are held constant, can be used to further reduce the set of candidate models.     

Entrance effects for power-law fluid

Entrance pressure losses for the creeping flow of a power-law fluid are calculated for an abrupt contraction of ratio 2, 4, 8 and ∞ for both the axisymmetric and planar cases using P₂P₁ and PP₁ finite elements. Contrary to some earlier findings in the literature, the entrance pressure loss obtained by using the two different types of finite elements, both of which satisfy the Babus?ka-Brezzi condition, are found to converge to the same results. The present results also confirm that the variational method of Duda and Vrentas gives excellent upper bounds for both the axisymmetric and planar cases with infinite contraction ratio.     

Recovery of sensor embedded washing machines using a multi-kanban controlled disassembly line

Product recovery involves the recovery of materials and components from returned or end-of-life products. Disassembly, an element of product recovery, is the systematic separation of an assembly into its components, subassemblies or other groupings. Stricter environmental regulations together with dramatic decrease in natural resources and landfills have increased the importance of disassembly as all product recovery options require some level of disassembly. Due to changes made during the lifetime of a product by customers or service personnel, the number and the version of components prior to disassembly is unknown. Customers may also discriminate between and demand different versions of components. The existence of non-functional components further adds to the uncertainty associated with disassembly yield. Sensors implanted into products during their production can address this uncertainty by providing information on the number, condition and version of components prior to disassembly. In this study, we evaluate the impact of sensor embedded products (SEPs) on the various performance measures of a washing machine (WM) disassembly line controlled by a multi-kanban system, which takes into consideration the highly stochastic behavior of the line while managing material and kanban flows. First, separate design of experiments studies based on orthogonal arrays are performed for conventional products and SEPs. In order to observe the response of each experiment, detailed discrete event simulation (DES) models for both types of products are developed considering the precedence relationships among the components of a WM. Then, pair-wise t-tests are conducted to compare the two cases based on different performance measures. According to the results, SEPs provide significant reductions in all costs (viz., backorder, holding, disassembly, disposal, testing and transportation) while increasing revenue and profit.     

Identification of statistical patterns in complex systems via symbolic time series analysis

Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys.     

An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains

We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log ⁴ n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms. Received July 29, 1998; revised October 5, 1999.     

Synthesis, structure, and field emission properties of sulfur-doped nanocrystalline diamond

The synthesis and properties of sulfur-doped nanocrystalline diamond films were investigated. The films were deposited by hot-filament chemical vapor deposition on Mo substrates using methane, hydrogen, and hydrogen disulfide. The nanocrystalline nature of the material arises from the induction of continuous secondary nucleation in the chemical vapor deposition environment. Complementary characterization tools were employed in order to obtain a comprehensive and coherent understanding of the correlations between the structural and electronic properties. In particular, sulfur-doped nanocrystalline diamond films show n-type Hall conductivity, enhanced field emission properties, and insensitivity to ion radiation. It was found that n-type doping of the tetragonally-bonded carbon matrix together with a nano network of trigonally-bonded carbon are crucial elements for enhanced field emission from nanocrystalline diamond. These conclusions and the corresponding supporting evidence are discussed.     

Electrodeposited carbon nanotube thin films

A successful attempt to grow carbon nanotubes (CNTs) by electrodeposition technique for the first time is reported here. Carbon nanotubes were grown on Si (001) substrate using acetonitrile (1% v/v) and water as electrolyte at an applied d.c. potential ∼20 V. The films were characterized by X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), Raman, optical absorbance, Fourier Transform Infra Red spectroscopy (FTIR) and Electron Spin Resonance (ESR) measurements. The effect of magnetic field on the growth of nanotubes was studied critically. It was found that the presence of magnetic field during electro-deposition played a crucial role on the growth of carbon nanotubes and hence the electronic properties. Photoluminescence (PL) studies indicated band edge luminescence ∼0.72-0.83 eV. Field emission studies indicated lower turn-on voltage and higher current density for films deposited with magnetic field.