Mathematical modelling of divided blast cupola

A pseudo 2-D mathematical model has been developed to simulate a cupola with one row and two rows of tuyere. The simulation results predicted higher spout temperature and combustion ratio for cupola with two rows of tuyere compared to that with one row. Further, the model has been used to study the effect of the distance of separation between the two rows of tuyere on cupola performance. The computed results shows that the spout temperature increases with tuyere level separation and attains the maximum at an optimum distance of separation between two rows of tuyere. Above the optimum, the spout temperature starts decreasing. The exit gas temperature and combustion ratio increases monotonously with the increase in tuyere level separation. These results agree well with the reported experimental observations. The mechanism behind the improved cupola performance with two rows of tuyere has been deduced from the computed temperature and composition profiles inside the cupola.

Steady state three-dimensional mathematical model for cupola

A three-dimensional mathematical model has been developed to simulate the gas flow, composition, and temperature profiles inside a cupola. Comparison of the model with the reported experimental data shows the presence of a zone with low combustion rate at the tuyere level. For a 24 in (610 mm) cupola with four rows of tuyeres, the combustion zones from each tuyere overlap each other, forming an overall combustion zone of cylindrical shape of height similar to 0.2 m. Using the model, it is found that the spout temperature initially increases with increasing blast velocity and attains a maximum. Further increase in blast velocity does not change the spout temperature. This suggests that smaller size tuyeres and higher permeability of the bed can give superior cupola performance. (C) 1997 The Institute of Materials.

Distributed intrusion detection in the presence of correlated sensor readings: Signal-space and communication-complexity view-point

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

Neural network based optimal routing algorithm for communication networks

This paper presents the capability of the neural networks as a computational tool for solving constrained optimization problem, arising in routing algorithms for the present day communication networks. The application of neural networks in the optimum routing problem, in case of packet switched computer networks, where the goal is to minimize the average delays in the communication have been addressed. The effectiveness of neural network is shown by the results of simulation of a neural design to solve the shortest path problem. Simulation model of neural network is shown to be utilized in an optimum routing algorithm known as flow deviation algorithm. It is also shown that the model will enable the routing algorithm to be implemented in real time and also to be adaptive to changes in link costs and network topology. (C) 2002 Elsevier Science Ltd. All rights reserved.

Mathematical model of COREX melter gasifier: Part II. Dynamic model

A dynamic model of the COREX melter gasifier is developed to study the transient behavior of the furnace. The effect of pulse disturbance and step disturbance on the process performance has been studied. This study shows that the effect of pulse disturbance decays asymptotically. The step change brings the system to a new steady state after a delay of about 5 hours. The dynamic behavior of the melter gasifier with respect to a shutdown/blow-on condition and the effect of tapping are also studied. The results show that the time response of the melter gasifier is much less than that of a blast furnace.

Mathematical model of COREX melter gasifier: Part I. Steady-state model

The COREX melter gasifier is a countercurrent reactor to produce liquid iron. Directly reduced iron (DRI), noncoking coal, and other additives are charged to the melter gasifier at their respective temperatures, and O-2 is blown through the tuyeres. Functionally, a melter gasifier is divided into three zones: a moving bed, fluidized bed, and free board. A model has been developed for the moving bed, where the tuyere region is two-dimensional (2-D) and the rest is one-dimensional (1-D). It is based on multiphase conservation of mass, momentum, and heat. The fluidized bed has been treated as 1-D. Partial equilibrium is calculated for the free board. The calculated temperature of the hot metal, the top gas, and the chemistry of the top gas agree with the reported plant data. The model has been used to study the effects of bed height, injection of impure O-2, coal chemistry, and reactivity on the process performance.

Fault-Tolerant Average Execution Time Optimization for General Purpose Multi-Processor System-on Chips

Fault-tolerance is due to the semiconductor technology development important, not only for safety-critical systems but also for general-purpose (non-safety critical) systems. However, instead of guaranteeing that deadlines always are met, it is for general-purpose systems important to minimize the average execution time (AET) while ensuring fault-tolerance. For a given job and a soft (transient) error probability, we define mathematical formulas for AET that includes bus communication overhead for both voting (active replication) and rollback-recovery with checkpointing (RRC). And, for a given multi-processor system-on-chip (MPSoC), we define integer linear programming (ILP) models that minimize AET including bus communication overhead when: (1) selecting the number of checkpoints when using RRC, (2) finding the number of processors and job-to-processor assignment when using voting, and (3) defining fault-tolerance scheme (voting or RRC) per job and defining its usage for each job. Experiments demonstrate significant savings in AET.

Mathematical Analysis of Sensor Fusion for Intrusion Detection Systems

Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.

On the Limits of Spatial Reuse and Cooperative Communication for Dense Wireless Networks

We consider a dense ad hoc wireless network comprising n nodes confined to a given two dimensional region of fixed area. For the Gupta-Kumar random traffic model and a realistic interference and path loss model (i.e., the channel power gains are bounded above, and are bounded below by a strictly positive number), we study the scaling of the aggregate end-to-end throughput with respect to the network average power constraint, P macr, and the number of nodes, n. The network power constraint P macr is related to the per node power constraint, P macr, as P macr = np. For large P, we show that the throughput saturates as Theta(log(P macr)), irrespective of the number of nodes in the network. For moderate P, which can accommodate spatial reuse to improve end-to-end throughput, we observe that the amount of spatial reuse feasible in the network is limited by the diameter of the network. In fact, we observe that the end-to-end path loss in the network and the amount of spatial reuse feasible in the network are inversely proportional. This puts a restriction on the gains achievable using the cooperative communication techniques studied in and, as these rely on direct long distance communication over the network.

On the fundamentally asynchronous nature of interference in cooperative base station systems

Cooperative transmission by base stations can significantly improve the spectral efficiency of multiuser, multi-cell multiple input multiple output systems. We show that in such systems the multiuser interference is asynchronous by nature, even when perfect timing-advance mechanisms ensure that the desired signal components arrive synchronously. We establish an accurate mathematical model for the asynchronism, and use it to show that the asynchronism leads to a significant performance degradation of existing linear preceding designs that assumed synchronous interference. We consider three different previously proposed precoding designs, and show how to modify them to effectively mitigate asynchronous interference.

D-MG Tradeoff and Optimal Codes for a Class of AF and DF Cooperative Communication Protocols

Cooperative relay communication in a fading channel environment under the orthogonal amplify-and-forward (OAF), non-orthogonal and orthogonal selection decode-and-forward (NSDF and OSDF) protocols is considered here. The diversity-multiplexing gain tradeoff (DMT) of the three protocols is determined and DMT-optimal distributed space-time code constructions are provided. The codes constructed are sphere decodable and in some instances incur minimum possible delay. Included in our results is the perhaps surprising finding that the OAF and NAF protocols have identical DMT when the time durations of the broadcast and cooperative phases are optimally chosen to suit the respective protocol. Two variants of the NSDF protocol are considered: fixed-NSDF and variable-NSDF protocol. In the variable-NSDF protocol, the fraction of time occupied by the broadcast phase is allowed to vary with multiplexing gain. In the two-relay case, the variable-NSDF protocol is shown to improve on the DMT of the best previously-known static protocol for higher values of multiplexing gain. Our results also establish that the fixed-NSDF protocol has a better DMT than the NAF protocol for any number of relays.

Sequences for Phase-Encoded Optical CDMA

In phase-encoded optical CDMA (OCDMA) spreading is achieved by encoding the phase of signal spectrum. Here, a mathematical model for the output signal of a phase-encoded OCDMA system is first derived. This is shown to lead to a performance metric for the design of spreading sequences for asynchronous transmission. Generalized bent functions are used to construct a family of efficient phase-encoding sequences. It is shown how M-ary modulation of these spreading sequences is possible. The problem of designing efficient phaseencoded sequences is then related to the problem of minimizing PMEPR (peak-to-mean envelope power ratio) in an OFDM communication system.

On four-group ML decodable distributed space time codes for cooperative communication

A construction of a new family of distributed space time codes (DSTCs) having full diversity and low Maximum Likelihood (ML) decoding complexity is provided for the two phase based cooperative diversity protocols of Jing-Hassibi and the recently proposed Generalized Non-orthogonal Amplify and Forward (GNAF) protocol of Rajan et al. The salient feature of the proposed DSTCs is that they satisfy the extra constraints imposed by the protocols and are also four-group ML decodable which leads to significant reduction in ML decoding complexity compared to all existing DSTC constructions. Moreover these codes have uniform distribution of power among the relays as well as in time. Also, simulations results indicate that these codes perform better in comparison with the only known DSTC with the same rate and decoding complexity, namely the Coordinate Interleaved Orthogonal Design (CIOD). Furthermore, they perform very close to DSTCs from field extensions which have same rate but higher decoding complexity.

The Mathematical modeling of inhomogeneites in ventricular tissue

Cardiac arrhythmias such as ventricular tachycardia (VT) or ventricular fibrillation (VF) are the leading cause of death in the industrialised world. There is a growing consensus that these arrhythmias arise because of the formation of spiral waves of electrical activation in cardiac tissue; unbroken spiral waves are associated with VT and broken ones with VF. Several experimental studies have been carried out to determine the effects of inhomogeneities in cardiac tissue on such arrhythmias. We give a brief overview of such experiments, and then an introduction to partial-differential-equation models for ventricular tissue. We show how different types of inhomogeneities can be included in such models, and then discuss various numerical studies, including our own, of the effects of these inhomogeneities on spiral-wave dynamics. The most remarkable qualitative conclusion of our studies is that the spiral-wave dynamics in such systems depends very sensitively on the positions of these inhomogeneities.