Mathematical simulation and experimental verification of melting resulting from the coupled effect of natural convection and exothermic heat of mixing

When melting processes are associated with an exothermic heat of mixing, unique coupled transport phenomena take place. In this article, a mathematical model has been developed to simulate these unique coupled heat and mass transfer events. The model was based on the control-volume finite difference approach and on an enthalpy method. In order to verify the mathematical model, a low-temperature physical model was established consisting of ice and sulfuric acid solutions. In this physical model, both temperature and velocity measurements were carried out. The model predictions were compared with experimental measurements, and they were found to be in good agreement. The model was also applied to a high-temperature system, namely, the melting of silicon metal in liquid high carbon iron. The predictions distinguished two periods present in the entire melting process. In the first period, the silicon was heated up. The second period, i.e., free melting period, occurred in tandem with the exothermic reaction, and consequently, the melting process was greatly accelerated. As was the case with the low-temperature physical model, as with the high-temperature system, good agreement was obtained between the predicted results and the experimental measurements.     

Evaluating Liquefaction Strength of Partially Saturated Sand

A method is presented for evaluating the liquefaction strength of partially saturated sand using the compression wave velocity (P-wave velocity), a new indicator of saturation. Based on laboratory test results, an empirical correlation that relates the liquefaction strength with the pore pressure coefficient B is firstly proposed. The strength is defined as the cyclic stress ratio required to cause liquefaction at a specified number of cycles. With the aid of a theoretical relation between B and the P-wave velocity, an explicit correlation of more interest is then established between the liquefaction strength of sand and its P-wave velocity. A comparison of the predictions using this explicit correlation with laboratory measurements shows a satisfactory agreement. The significance of this method lies in that it makes it possible to evaluate the liquefaction strength of sand as affected by saturation through the measurement of P-wave velocity, which can be made not only in the laboratory but particularly in the field.     

Representation and uniformization of algebraic transductions

This paper explores different means of representation for algebraic transductions, i.e., word relations realized by pushdown transducers. The relevance of this work lies more in its point of view rather than any particular result. We are aiming at giving specific techniques for obtaining, or perhaps explaining, decompositions of algebraic (and incidentally, rational) relations, relying solely on their “machine” definition rather than some complex algebraic apparatus. From this point of view, we are hoping to have demystified the heavy formalism employed in the present literature. Some of the novelties of our work are: the use of “stack languages” and “embeddings,” which eliminate the need of arbitrary context-free languages in our characterizations, the study of uniformizations for algebraic transductions and the use of the so-called stack transductions for exposing the anatomy of pushdown transducers.This work was supported by the Natural Science and Engineering Research Council of Canada grants R220259 and OGP0041630.     

A STUDY ON THE SEPARATION OF DIFFUSION AND SURFACE EMISSION COEFFICIENTS IN WOOD

For a more accurate simulation of the moisture sorption process in wood, the precise separation of surface emission and diffusion coefficients is essential. In this paper, a non-linear simplex technique that was developed to obtain the optimum pair of the surface emission coefficient he, and the diffusion coefficient D from a single sorption curve is presented and tested with experimental data. An easy to use computer program was employed to carry out the evaluation. Data analysis showed that the new method resulted in a more statistically accurate calculation of b_c and D than currently existing methods.     

Collaborative virtual learning environments: design and evaluation

E-learning systems have gone through a radical change from the initial text-based environments to more stimulating multimedia systems. Such systems are Collaborative Virtual Environments, which could be used in order to support collaborative e-learning scenarios. The main aim of this paper is to aid educational designers in selecting, designing and evaluating three dimensional collaborative virtual environments in order to gain the pedagogical benefits of Computer Supported Collaborative Learning. Therefore, this paper initially discusses the potential of three dimensional networked virtual environments for supporting collaborative learning. Furthermore, based on a two-step platform selection process this paper (a) presents and compares three dimensional multi-user virtual environments for supporting collaborative learning and (b) validates the most promising solution against a set of design principles for educational virtual environments. According to these principles, an educational environment has been implemented on top of the selected platform in order to support collaborative e-learning scenarios. The design of this environment is also presented. In addition, this paper presents the results of three small scale studies carried out in a tertiary education department, to assess the educational environment. This environment has been evaluated based on a hybrid evaluation methodology for uncovering usability problems, collecting further requirements for additional functionality to support collaborative virtual learning environments, and determining the appropriateness of different kinds of learning scenarios.

Stackelberg Strategies for Selfish Routing in General Multicommodity Networks

A natural generalization of the selfish routing setting arises when some of the users obey a central coordinating authority, while the rest act selfishly. Such behavior can be modeled by dividing the users into an α fraction that are routed according to the central coordinator’s routing strategy (Stackelberg strategy), and the remaining 1−α that determine their strategy selfishly, given the routing of the coordinated users. One seeks to quantify the resulting price of anarchy, i.e., the ratio of the cost of the worst traffic equilibrium to the system optimum, as a function of α. It is well-known that for α=0 and linear latency functions the price of anarchy is at most 4/3 (J. ACM 49, 236–259, 2002). If α tends to 1, the price of anarchy should also tend to 1 for any reasonable algorithm used by the coordinator. We analyze two such algorithms for Stackelberg routing, LLF and SCALE. For general topology networks, multicommodity users, and linear latency functions, we show a price of anarchy bound for SCALE which decreases from 4/3 to 1 as α increases from 0 to 1, and depends only on α. Up to this work, such a tradeoff was known only for the case of two nodes connected with parallel links (SIAM J. Comput. 33, 332–350, 2004), while for general networks it was not clear whether such a result could be achieved, even in the single-commodity case. We show a weaker bound for LLF and also some extensions to general latency functions. The existence of a central coordinator is a rather strong requirement for a network. We show that we can do away with such a coordinator, as long as we are allowed to impose taxes (tolls) on the edges in order to steer the selfish users towards an improved system cost. As long as there is at least a fraction α of users that pay their taxes, we show the existence of taxes that lead to the simulation of SCALE by the tax-payers. The extension of the results mentioned above quantifies the improvement on the system cost as the number of tax-evaders decreases. Research of G. Karakostas supported by an NSERC Discovery Grant and MITACS. Research of S. Kolliopoulos partially supported by the University of Athens under the project Kapodistrias.     

Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands

We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination, we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15, [2004]; Karakostas and Kolliopoulos in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 268–276, [2004]; Fleischer et al. in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 277–285, [2004]) by allowing user demands to be elastic. In this setting the demand of a user is not fixed a priori but it is a function of the routing cost experienced, a most natural assumption in traffic and data networks. Research supported by MITACS and a NSERC Discovery grant.     

Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition

The K-connected Deployment and Power Assignment Problem (DPAP) in WSNs aims at deciding both the sensor locations and transmit power levels, for maximizing the network coverage and lifetime objectives under K-connectivity constraints, in a single run. Recently, it is shown that the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is a strong enough tool for dealing with unconstraint real life problems (such as DPAP), emphasizing the importance of incorporating problem-specific knowledge for increasing its efficiency. In a constrained Multi-objective Optimization Problem (such as K-connected DPAP), the search space is divided into feasible and infeasible regions. Therefore, problem-specific operators are designed for MOEA/D to direct the search into optimal, feasible regions of the space. Namely, a DPAP-specific population initialization that seeds the initial solutions into promising regions, problem-specific genetic operators (i.e. M-tournament selection, adaptive crossover and mutation) for generating good, feasible solutions and a DPAP-specific Repair Heuristic (RH) that transforms an infeasible solution into a feasible one and maintains the MOEA/D’s efficiency simultaneously. Simulation results have shown the importance of each proposed operator and their interrelation, as well as the superiority of the DPAP-specific MOEA/D against the popular constrained NSGA-II in several WSN instances.