Drag models, solids concentration and velocity distribution in a stirred tank

Drag force influences both the particle suspension and solids concentration distribution in a stirred tank. The influence of drag models on the prediction of solids suspension in a tank stirred by a hydrofoil impeller was studied in the present work using computational fluid dynamics (CFD) and experimental techniques. A comparison was made between the drag models based on Reynolds number only and those that take solid volume fraction into account or those that account for the effect of the free stream turbulence. One of the drag models investigated was a function of the energy dissipation rate, and therefore, the influence of the methods of determining the energy dissipation rate on the prediction of solids suspension was investigated. It was shown that a better agreement between the CFD simulation and experimental results can be obtained using drag models based on solids volume fraction than those that are based on Reynolds number only.     

Plasma Sprayed Dense MgO-Y2O3 Nanocomposite Coatings Using Sol-Gel Combustion Synthesized Powder

MgO-Y₂O₃ nanostructured composite powder (volume ratio of 50:50) was synthesized by a sol-gel combustion process which generated crystal sizes in the 10-20 nm range. The MgO-Y₂O₃ nanopowder was plasma sprayed using a conventional, DC arc plasma spray system. X-ray diffraction analysis shows that the as-sprayed MgO-Y₂O₃ coating is composed of cubic MgO and Y₂O₃ phases and has ~95% density. Microstructure characterization by SEM reveals that the as-sprayed coating has fine grain sizes of 100-300 nm as a result of rapid solidification. The hardness of the coating, 7.5 ± 0.6 GPa, is higher than that of coarse-grained, dense MgO, and Y₂O₃ ceramics. This approach demonstrates the potential of plasma spray processes for making thick, dense MgO-Y₂O₃ nanocomposite performs for applications as durable, infrared windows.     

Exploring the ERTMS/ETCS full moving block specification: an experience with formal methods

International Journal on Software Tools for Technology Transfer - Shift2Rail is a joint undertaking funded by the EU via its Horizon 2020 program and by main railway stakeholders. Several...     

Reconstructing (h,v)-convex 2-dimensional patterns of objects from approximate horizontal and vertical projections

The problem of reconstructing a pattern of an object from its approximate discrete orthogonal projections in a 2-dimensional grid, may have no solution because the inaccuracy in the measurements of the projections may generate an inconsistent problem. To attempt to overcome this difficulty, one seeks to reconstruct a pattern with projection values having possibly some bounded differences with the given projection values and minimizing the sum of the absolute differences.

This paper addresses the problem of reconstructing a pattern with a difference at most equal to +1 or −1 between each of its projection values and the corresponding given projection value. We deal with the case of patterns which have to be horizontally and vertically convex and the case of patterns which have to be moreover connected, the so-called convex polyominoes. We show that in both cases, the problem of reconstructing a pattern can be transformed into a Satisfiability (SAT) Problem. This is done in order to take advantage of the recent advances in the design of solvers for the SAT Problem. We show, experimentally, that by adding two important features to CSAT (an efficient SAT solver), optimal patterns can be found if there exist feasible ones. These two features are: first, a method that extracts in linear time an optimal pattern from a set of feasible patterns grouped in a generic pattern (obtaining a generic pattern may be exponential in the worst case) and second, a method that computes actively a lower bound of the sum of absolute differences that can be obtained from a partially defined pattern. This allows to prune the search tree if this lower bound exceeds the best sum of absolute differences found so far.     

Synchronizations in Team Automata for Groupware Systems

Team automata have been proposed in Ellis (1997) as a formal framework for modeling both the conceptual and the architectural level of groupware systems. Here we define team automata in a mathematically precise way in terms of component automata which synchronizeon certain executions of actions.At the conceptual level, our model serves as a formal framework in whichbasic groupware notions can be rigorously defined and studied.At the architectural level, team automata can be used as building blocksin the design of groupware systems.     

Portfolio Management in Double Unknown Situations: Technological Platforms and the Role of Cross‐Application Managers

This article investigates portfolio management in double unknown situations. Double unknown refers to a situation in which the level of uncertainty is high and both technology and markets are as yet unknown. This situation can be an opportunity for new discoveries, creation of new performance solutions and giving direction to portfolio structuring. The literature highlights that the double unknown situation is a prerequisite to designing generic technologies that are able to address many existing and emerging markets and create value across a broad range of applications. The purpose of this paper is to investigate the initial phases of generic technology governance and associated portfolio structuring in multi‐project firms. We studied three empirical contexts of portfolio structuring at the European semiconductor provider STMicroelectronics. The results demonstrate that (1) portfolio management for generic technologies is highly transversal and comprises creating both modules to address market complementarities and the core element of a technological system – the platform, and (2) the design of generic technologies requires ‘cross‐application’ managers who are able to supervise the interactions among innovative concepts developed in different business and research groups and who are responsible for structuring and managing technological and marketing exploration portfolios within the organizational structures of a company.     

Atomic snapshots using lattice agreement

Summary Thesnapshot object is an important tool for constructing wait-free asynchronous algorithms. We relate the snapshot object to thelattice agreement decision problem. It is shown that any algorithm for solving lattice agreement can be transformed into an implementation of a snapshot object. The overhead cost of this transformation is only a linear number of read and write operations on atomic single-writer multi-reader registers. The transformation uses an unbounded amount of shared memory. We present a deterministic algorithm for lattice agreement that usedO (log² n) operations on 2-processorTest & Set registers, plusO (n) operations on atomic single-writer multi-reader registers. The shared objects are used by the algorithm in adynamic mode, that is, the identity of the processors that access each of the shared objects is determined dynamically during the execution of the algorithm. By a randomized implementation of 2-processorsTest & Set registers from atomic registers, this algorithm implies a randomized algorthm for lattice agreement that uses an expected number ofO (n) operations on (dynamic) atomic single-writer multi-reader registers. Combined with our transformation this yields implementations of atomic snapshots with the same complexity.Cambridge Research Laboratory, Digital Equipment Corporation Hagit Attiya received the B.Sc. degreeiin Mathematics and Computer Science from the Hebrew University of Jerusalem, in 1981, the M.Sc. and Ph.D. degrees in Computer Science from the Hebrew University of Jerusalem, in 1983 and 1987, respectively. She is presently a senior lecturer at the departtment of Computer Science at the Technion, Israel Institute of Technology. Prior to this, she has been a post-doctoral research associate at the Laboratory for Computer Science at M.I.T. Her general research interests are distributed computation and theoretical computer science. More specific interests include fault-tolerance, timing-based and asynchronous algorithms. Maurice Herlihy received the A.B. degree in Mathematics from Harvard University, and the M.S. and the Ph.D. degrees in Computer Science from M.I.T. From 1984 to 1989 he was a faculty member in the Computer Science Department at Carnegie Mellon University in Pittsburgh, PA. In 1989 he joined the research staff at the Digital Equipment Corporation's Cambridge Research Laboratory in Cambridge MA. Since 1994, he has been on the faculty at the Computer Science Department at Brown University. Dr. Herlihy's research interests encompass practical and theoretical aspects of distributed and concurrent computation. Ophir achman received a B.A. in computer science from the Technion, Haifa, Israel in 1989 and M.Sc. in computer science from the Technion, Haifa, Israel, in 1992. He is now studying for a D.Sc. in computer science at the Technion. His currentarea of research is distributed computing, and in particular, asynchronous shared memory systems.This work appeared in preliminary form in proceedings ofthe 6th International Workshop on Distributed Algorithms [12]. This research was partially supported by grant No. 92-0233 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Technion V.P.R. funds — B. and G. Greenberg Research Fund (Ottawa), and the fund for the promotion of research in the TechnionPart of the work of this author was performed while visiting DEC Cambridge Research Laboratory     

A polynomial time computable metric between point sets

Measuring the similarity or distance between sets of points in a metric space is an important problem in machine learning and has also applications in other disciplines e.g. in computational geometry, philosophy of science, methods for updating or changing theories, . Recently Eiter and Mannila have proposed a new measure which is computable in polynomial time. However, it is not a distance function in the mathematical sense because it does not satisfy the trian gle inequality. We introduce a new measure which is a metric while being computable in polynomial time. We also present a variant which computes a normalised metric and a variant which can associate different weights with the points in the set. Received: 18 October 1999 / 8 January 2001     

A survey of parallel execution strategies for transitive closure and logic programs

An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods. Recommended by: Patrick Valduriez